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1 -HRAF Advanced Research Centres [EU]
1 +HRAF Advanced Research Centers
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4 4  
5 5  = About hrafARC =
6 6  
7 -HRAF Advanced Research Centers (hrafARC) is a research division of the Human Relations Area Files at Yale University. hrafARC aims to promote basic and applied research in anthropology and to encourage and support comparative and cross-cultural research. More specifically, hrafARC aims to further the development of anthropology through comparative knowledge based on testable theory, sound research design and systematic methods for the collection and analysis of data. We seek to fulfill the historic mission of anthropology to describe and explain the range of variation in human biology, society, and culture across time and space.
7 +The HRAF Advanced Research Centers (hrafARC) aim to promote basic and applied research in anthropology and to encourage and support comparative and cross-cultural research. More specifically, hrafARC aims to further the development of anthropology through comparative knowledge based on testable theory, sound research design and systematic methods for the collection and analysis of data. We seek to fulfill the historic mission of anthropology to describe and explain the range of variation in human biology, society, and culture across time and space.
8 8  
9 9  The main headquarters is at the Human Relations Area Files (HRAF) building in New Haven, CT (755 Prospect Street). [[HRAF>>url:http://hraf.yale.edu||rel="__blank"]] is a nonprofit membership consortium affiliated with Yale University. [[Carol R. Ember>>url:http://hraf.yale.edu/about/staff/carol-r-ember/||rel="__blank"]] directs hrafARC in New Haven and Michael Fischer directs hrafARC in the UK~-~-see [[http:~~/~~/hrafarc.eu/>>url:http://hrafarc.eu/]].
10 10  
11 -{{html}}
11 +== hrafARC Projects ==
12 12  
13 -<button value="Donate to hrafARC" style="font-size:14px;color:darkred;weight:bold" title="Donate to hrafARC" type="button" onclick="js:window.location='/Payments/Donate';">Donate to hrafARC </button>
14 -{{/html}}
13 +==== Natural Hazards and Cultural Transformations. (2015-2019) ====
15 15  
16 -== hrafARC Current Research ==
15 +Researchers from cultural anthropology, archaeology, psychology, geography and climatology conducted three types of comparisons~-~-a worldwide cross-cultural comparison using ethnographic data, an diachronic archaeological comparison of 32 traditions before and after major severe climate events, and a comparison of countries. We are looking at a broad variety of possible cultural transformations in response to hazards. These range from diet and subsistence diversity, property systems, mutual aid, political economy, general cultural “tightness" and beliefs about gods involvement with weather. All of these domains have been newly coded for this project.[[ Read more>>url:http://hrafarc.org/bin/hrafARC+Research+-+Chacult]] ...
17 17  
18 -We are currently working on a 5-year NSF-funded interdisciplinary project “Natural Hazards and Cultural Transformations.” Researchers from cultural anthropology, archaeology, psychology, geography and climatology, are conducting three types of comparisons~-~-a worldwide cross-cultural comparison using ethnographic data, an diachronic archaeological comparison of twelve traditions before and after major severe climate events, and a comparison of countries. We are looking at a broad variety of possible cultural transformations in response to hazards. These range from diet and subsistence diversity, property systems, mutual aid, political economy, and general cultural “tightness." All of these domains have been newly coded for this project[[. Read more>>url:http://hrafarc.org/bin/hrafARC+Research+-+Chacult]] ...
17 +==== Social Resilience to Nuclear Winter. (2018-2020) ====
19 19  
19 +This project employs archaeological and historical information to examine societal resilience to a catastrophic atmospheric event that block the sun and cooled the Northern Hemisphere by roughly 1 degree centigrade, creating widespread social disruption. Peregrine uses this event as a proxy for the expected atmospheric impact of a limited nuclear war in Europe and seeks to identify strategies of resilience by examining those societies that survived, and failed to survive, the A.D. 536 event. [[Read more...>>doc:Peregrine ARO grant.Peregrine ARO grant]]
20 +
20 20  == hrafARC Data Repository ==
21 21  
22 -Peregrine, Peter N. 2017. “Political Participation and Long-Term Resilience in Pre-Columbian Societies.” //Disaster Prevention and Management// 26(3). DOI: 10.1108/DPM-01-2017-0013
23 +==== **2017** ====
23 23  
25 +Peregrine, Peter N. 2017. “Political Participation and Long-Term Resilience in Pre-Columbian Societies.” //Disaster Prevention and Management// 26(3). [[https:~~/~~/doi.org/10.1108/DPM-01-2017-0013>>url:https://doi.org/10.1108/DPM-01-2017-0013]]
26 +
24 24  * [[Codebook>>attach:CSP-AR-Codebook_and_Notes_V5-2.docx||rel="__blank"]]
25 25  * [[Social Transformation Data (SPSS)>>attach:AR-DA-ST-V5-NW-PP.sav||rel="__blank"]]
26 26  * [[Raw Data (SPSS)>>attach:AR-DA-V5-NW-PP.sav||rel="__blank"]] and [[Index Commands (SPSS)>>attach:IBSS_indices_final.sps||rel="__blank"]]
... ... @@ -27,8 +27,18 @@
27 27  * [[Social Transformation Data (csv)>>attach:AR-DA-ST-V5-NW-PP.csv||rel="__blank"]]
28 28  * [[Raw Data (csv)>>attach:AR-DA-V5-NW-PP.csv]]
29 29  
30 -Peregrine, Peter N. n.d. "Social Resilience to Climate-Related Disasters in Ancient Societies: A Test of Two Hypotheses" (under review)
33 +==== **2018** ====
31 31  
35 +Ember, Carol R., Ian Skoggard, Erik J. Ringen, and Megan Farrer. 2018. "Our Better Nature: Does Resource Stress Predict Beyond-Household Sharing?" //Evolution & Human Behavior// 39 (4): 380-391.[[ https:~~/~~/www.sciencedirect.com/science/article/pii/S1090513817302489>>url:https://www.sciencedirect.com/science/article/pii/S1090513817302489]]
36 +
37 +* [[Codebook>>url:http://hrafarc.org/download/Main/WebHome/Supplementary%20data%20ReadMeRevised2.pdf]]
38 +* [[Data >>url:http://hrafarc.org/download/Main/WebHome/Supplement_Data_April2018.sav]](SPSS)
39 +* [[Data >>url:http://hrafarc.org/download/Main/WebHome/Supplement_Data_April2018.csv]](csv)
40 +
41 +Peregrine, Peter N. 2018 "Social Resilience to Climate-Related Disasters in Ancient Societies: A Test of Two Hypotheses." //Weather, Climate and Society// 10(1): 145-161. [[https:~~/~~/doi.org/10.1175/WCAS-D-17-0052.1>>url:https://doi.org/10.1175/WCAS-D-17-0052.1]]
42 +
43 +Peregrine, Peter N. 2019. "Reducing Post-Disaster Conflict: A Cross-Cultural Analysis Using Archaeological Data." //Environmental Hazards//, 18:2, 93-110, DOI: [[10.1080/17477891.2018.1476317>>url:https://doi.org/10.1080/17477891.2018.1476317]]
44 +
32 32  * [[Codebook>>attach:CSP-AR-Codebook_and_Notes_V5-2.docx||rel="__blank"]]
33 33  * [[Social Transformation Data (SPSS)>>attach:AR-DA-ST-V5-PP.sav||rel="__blank"]]
34 34  * [[Raw Data (SPSS)>>attach:AR-DA-V5-PP.sav||rel="__blank"]] and [[Index Commands (SPSS)>>attach:IBSS_indices_final.sps||rel="__blank"]]
... ... @@ -35,8 +35,123 @@
35 35  * [[Social Transformation Data (csv)>>attach:AR-DA-ST-V5-PP.csv]]
36 36  * [[Raw Data (csv)>>attach:AR-DA-V5-PP.csv]]
37 37  
38 -----
51 +==== **2019** ====
39 39  
40 -== HRAF Services Platform ==
53 +Ember, Carol R., Eric C. Jones, Ian Skoggard and Teferi Abate Adem. (% style="font-size: 14px; background-color: rgb(245, 245, 245);" %)2019. "Warfare, Atrocities, and Political Participation: Eastern Africa."(%%)
54 +//Journal of Aggression, Conflict and Peace Research// [[11(1):11-23, >>url:https://doi.org/10.1108/JACPR-05-2017-0290]][[https:~~/~~/doi.org/10.1108/JACPR-05-2017-0290>>url:https://doi.org/10.1108/JACPR-05-2017-0290]]
41 41  
42 -HRAF is working on a services platform to support the next generation of eHRAF applications to support teaching and research [[Read more …>> eServices.demos]]
56 +* [[Codebook>>attach:Ember_JACPR_Codebook_22Dec2017.pdf]]
57 +* Data for [[Eastern African Sample (SPSS>>attach:Ember_et_al_EAFrica_PolPart_Codes_JACPR2017.sav]]) and [[Worldwide Sample (SPSS)>>attach:Ember_et_al_Worldwide_PolPart_Codes_JACPR2017_SHort.sav]]
58 +* Data for [[Eastern African Sample (csv)>>attach:Ember_et_al_EAFrica_PolPart_Codes_JACPR2017.csv]] and [[Worldwide Sample (csv)>>attach:Ember_et_al_Worldwide_PolPart_Codes_JACPR2017_SHort.csv]]
59 +
60 +Felzer, B.S., Ember, C.R., Chiang, R., and Jiang, M. 2019.** **The relationships of extreme precipitation and temperature events with ethnographic reports of droughts and floods in nonindustrial societies. Weather, Climate, and Society. Early release at: //[[https:~~/~~/doi.org/10.1175/WCAS-D-19-0045.1>>url:https://doi.org/10.1175/WCAS-D-19-0045.1]]//
61 +
62 +* [[readme_final_excel.docx>>url:http://hrafarc.org/download/Main/WebHome/readme_final_excel.docx]]
63 +* [[ThrIndS_Combined_ann.xlsx>>url:http://hrafarc.org/download/Main/WebHome/ThrIndS_Combined_ann.xlsx]]
64 +* [[rx5s_Combined_ann.xlsx>>url:http://hrafarc.org/download/Main/WebHome/rx5s_Combined_ann.xlsx]]
65 +* [[rx1s_Combined_ann.xlsx>>url:http://hrafarc.org/download/Main/WebHome/rx1s_Combined_ann.xlsx]]
66 +* [[SDIIS_Combined_ann.xlsx>>url:http://hrafarc.org/download/Main/WebHome/SDIIS_Combined_ann.xlsx]]
67 +* [[ThrIndS_tmin_combined.xlsx>>url:http://hrafarc.org/download/Main/WebHome/ThrIndS_tmin_combined.xlsx]]
68 +* [[csdi_combined_ann.xlsx>>url:http://hrafarc.org/download/Main/WebHome/csdi_combined_ann.xlsx]]
69 +* [[CDS_Combined_ann.xlsx>>url:http://hrafarc.org/download/Main/WebHome/CDS_Combined_ann.xlsx]]
70 +* [[CDD_CWD_Combined.xlsx>>url:http://hrafarc.org/download/Main/WebHome/CDD_CWD_Combined.xlsx]]
71 +* [[CSDI_Combined.xlsx>>url:http://hrafarc.org/download/Main/WebHome/CSDI_Combined.xlsx]]
72 +* [[tmax_combined.xlsx>>url:http://hrafarc.org/download/Main/WebHome/tmax_combined.xlsx]]
73 +* [[SPSS_indices.xlsx>>url:http://hrafarc.org/download/Main/WebHome/SPSS_indices.xlsx]]
74 +* [[SPSS_PCM.xlsx>>url:http://hrafarc.org/download/Main/WebHome/SPSS_PCM.xlsx]]
75 +* [[coef_var.xlsx>>url:http://hrafarc.org/download/Main/WebHome/coef_var.xlsx]]
76 +* [[allfactors.xlsx>>url:http://hrafarc.org/download/Main/WebHome/allfactors.xlsx]]
77 +
78 +==== **2020** ====
79 +
80 +Ember, Carol R., Teferi Abate Adem, Tahlisa Brougham, and Emily Pitek. 2020. “Predictors of land privatization: Cross-cultural tests of defendability and resource stress theory” //American Anthropologist//. [[Forthcoming>>url:https://www.researchgate.net/publication/336749932_Ember-AbateAdem-Brougham-Pitek-Land-Defendability]].
81 +
82 +* [[EmberEtAl-2019-LandTenure-Supplement.docx>>attach:EmberEtAl-2019-LandTenure-Supplement.docx]]
83 +* [[Data (SPSS)>>attach:EmberEtAl-2019-LandTenureDataSet.sav]]
84 +* [[Data (csv)>>attach:EmberEtAl-2019-LandTenureDataSet.csv]]
85 +
86 +(((
87 +Ember, Carol R., Erik Ringen, Jack Dunnington, and Emily Pitek, 2020. "(% style="font-size: 14px; background-color: rgb(245, 245, 245);" %)Resource Stress and Subsistence Diversification Across Societies" //Nature Sustainability//: 1-9. [[DOI>>url:https://doi.org/10.1038/s41893-020-0542-5]]
88 +
89 +* [[Codebook>>attach:Variables in subdiv_data_rev2020.xlsx]]
90 +* [[Data (csv)>>attach:subdiv_data_rev2020.csv]]
91 +
92 +Peregrine, Peter N. 2020. "Climate and social change at the start of the Late Antique Little Ice Age" //The Holocene//.
93 +DOI: [[10.1177/0959683620941079>>url:https://doi.org/10.1177/0959683620941079]]
94 +
95 +* [[Codebook>>attach:ARO Codebook_5.pdf]]
96 +* [[Social Change Data (csv)>>attach:climaterawdata.csv]]
97 +* [[Social Change Data (SPSS)>>attach:Climate_Raw_Data.sav]]
98 +* [[Cultural Evolution Data, Atlas of Cultural Evolution (csv)>>attach:CulturalEvolution_ACEdata.csv]]
99 +* [[Cultural Evolution Data, Atlas of Cultural Evolution (SPSS)>>attach:CulturalEvolution_ACEdata.sav]]
100 +* [[Cultural Evolution Data, Turchin et al. (csv)>>attach:CulturalEvolution_PNASdata.csv]]
101 +* [[Cultural Evolution Data, Turchin et al. (SPSS)>>attach:CulturalEvolution_PNASdata.sav]]
102 +* [[Temperature Data (csv)>>attach:climatetemperature.csv]]
103 +* [[Temperature Data (SPSS)>>attach:Climate_Temperature.sav]]
104 +* [[GIS package (ArcMap)>>attach:Climate.mpk]]
105 +
106 +(((
107 +Peregrine, Peter N. "Social Resilience to climate change during the Late Antique Little Ice Age: A replication study" //Weather, Climate, and Society//. DOI: [[10.1175/WCAS-D-20-0023.1>>url:https://doi.org/10.1175/WCAS-D-20-0023.1]]
108 +
109 +* [[readme>>url:http://hrafarc.org/download/Main/WebHome/WCS_readme.txt]]
110 +* [[Codebook>>url:http://hrafarc.org/download/Main/WebHome/ARO%20Codebook_5.pdf]]
111 +* [[Social Change Data (csv)>>url:http://hrafarc.org/download/Main/WebHome/Social%20resilience.csv]]
112 +* [[Social Change Data (SPSS)>>url:http://hrafarc.org/download/Main/WebHome/Social%20Resilience%20ARO%2DDA.sav]]
113 +* [[SPSS Output (pdf)>>url:http://hrafarc.org/download/Main/WebHome/WCS_ARO.spv%20%5BDocument1%5D.pdf]]
114 +* [[SPSS Output (SPSS)>>url:http://hrafarc.org/download/Main/WebHome/WCS_ARO.spv]]
115 +* Raw coding data (Excel)
116 +* Raw coding data bibliography (Excel)
117 +* Raw coding data (RDF file)
118 +* Raw coding data (RDF ontology)
119 +
120 +Skoggard, Ian. Carol R. Ember, Emily Pitek, Joshua Conrad Jackson, Christina Carolus. 2020. "Resource Stress Predicts Changes in Religious Beliefs and Increases in Sharing Behavior." //Human Nature, //pp. 1-23//. //[[DOI>>url:https://doi.org/10.1007/s12110-020-09371-8]]//
121 +//
122 +
123 +* [[Codebook>>attach:Codebook.pdf]]
124 +* [[Data-ResourceStressGods-short (csv)>>attach:DT-GodsAndResourceStress.csv]]
125 +* [[Data-ResourceStressGods-long (csv)>>attach:DT-GodsAndResourceStress_Long.csv]]
126 +* [[Data-MoralHighGods-short (csv)>>attach:DT-MoralHighGods_EP(2).csv]]
127 +* [[Data-MoralHighGods-long (csv)>>attach:DT-MoralHighGods_Long_EP(1).csv]]
128 +* [[R code>>attach:Ranalysis_StressReligionSharing2020-1.R]]
129 +
130 +==== 2021 ====
131 +
132 +Ember, C., Skoggard, I., Felzer, B., Pitek, E., and Jiang, M. "Climate variability, drought, and the belief that high gods are associated with weather in nonindustrial societies." //Weather, Climate, and Society vol. 13, no. 2. //[[DOI>>url:http://10.1175/WCAS-D-20-0080.1]]
133 +
134 +
135 +[[readme_final_excel_sens.txt>>attach:readme_final_excel_sens.txt]]
136 +
137 +[[gap_fill_sens.zip>>attach:gap_fill_sens.zip]]
138 +
139 +[[Factors_revised_2020.xlsx>>attach:Factors_revised_2020.xlsx]]
140 +
141 +
142 +Peregrine, Peter N. 2021. "Social Resilience to Nuclear Winter: Lessons from the Late Antique Little Ice Age." //Global Security// 6(1): 57-67. https:~/~/doi.org/10.1080/23779497.2021.1963808
143 +
144 +* [[Codebook>>url:http://hrafarc.org/download/Main/WebHome/ARO%20Codebook_5.pdf]]
145 +* [[Social Change Data (csv)>>url:http://hrafarc.org/download/Main/WebHome/Social%20resilience.csv]]
146 +* [[Social Change Data (SPSS)>>url:http://hrafarc.org/download/Main/WebHome/Social%20Resilience%20ARO%2DDA.sav]]
147 +* SPSS Output (pdf)
148 +* SPSS Output (SPSS)
149 +* Raw coding data (Excel)
150 +* Raw coding data bibliography (Excel)
151 +* Raw coding data (RDF file)
152 +* Raw coding data (RDF ontology)
153 +
154 +(((
155 +
156 +)))
157 +
158 +(((
159 +
160 +)))
161 +)))
162 +)))
163 +
164 +(((
165 +== hrafArc Development ==
166 +
167 +[[Development Team Notes>>doc:Design.vDoc||rel="__blank"]] (Internal only)
168 +
169 +[[Development Summary >>doc:Design.vAppSummary]](Internal Only)
170 +)))
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4 +ABP-E,ABP-F,ABE-3,.729267149343859,1,-.037554981515316,-.231024683101504,.790160752140833,.000563859810984345,2,3,800,2,1,3,4,2,1,1,1,3,1,2,1,1,3,2,5,1,1.85714285714286,2,1.75,2.25,2,1
5 +EGP-1,EGP-2,EGE-1,-1.24244675543348,0,-1.19954368851681,-.150252490441696,.894881180735555,.284467283755023,9,1,3200,1,4,4,99,99,4,4,4,2,2,99,99,2,2,2,2,0,2,2,2,2,2,4
6 +EGP-2,EGP-3,EGE-2,.894881180735555,1,.284467283755023,.409128310618853,1.16635197976562,.844618281741013,9,2,2200,1,99,2,99,3,2,2,3, ,2,99,1,2,2,1,4,1,1.6,2,1.5,1.66666666666667,1.66666666666667,2.33333333333333
7 +GLP-A,GLP-B,GLE-1,-1.0834758803323,0,-1.11255148220705,-1.25333090609294,-1.0834758803323,-1.29210985304672,1,1,1300,9,4,3,3,2,3,2,2,2,1,1,1,2,1,1,2,0,1.28571428571429,1.33333333333333,1.25,1.5,1.33333333333333,2.33333333333333
8 +GLP-B,GLP-C,GLE-2,-1.0834758803323,0,-1.29210985304672,-.724299141308939,-1.0834758803323,-.276257380955877,1,2,1100,9,4,3,4,3,3,2,2,2,1,2,3,2,1,1,2,0,1.71428571428571,1.66666666666667,1.75,1.5,1.33333333333333,2.33333333333333
9 +GLP-C,GLP-D,GLE-3,-1.0834758803323,0,-.276257380955877,-.116565370775631,-.530004110043804,-.493881681999875,1,3,750,9,4,3,3,2,1,2,2,2,1,1,1,2,1,1,2,0,1.28571428571429,1.33333333333333,1.25,1.5,1.33333333333333,1.66666666666667
10 +IRP-1,IRP-2,IRE-1,.0500324014720803,1,.148286632933635,-.011962358835962,.0500324014720803,.275902420888867,6,1,2200,1,3,3,99,3,3,3,3,1,1,99,1,1,1,1,3,0,1,1,1,1,1,3
11 +MOP-A,MOP-B,MOE-1,.715965461770866,1,.844618281741013,.845495857697821,.632957030161735,.844618281741013,5,1,300,5,4,3,3,2,3,3,3,2,1,1,1,2,2,2,4,1,1.57142857142857,1.33333333333333,1.75,2,2,3
12 +MOP-B,MOP-C,MOE-2,.632957030161735,1,.844618281741013,1.13308909032358,.444533296659401,.998264552706763,5,2,550,5,2,3,4,2,3,2,2,2,1,2,1,3,2,3,4,1,2,1.66666666666667,2.25,2.5,2.66666666666667,2.33333333333333
13 +MOP-C,MOP-D,MOE-3,.444533296659401,1,.998264552706763,1.30943301191825,1.02068279223744,.844618281741013,5,3,1000,5,3,3,2,2,3,3,2,1,1,2,2,1,1,2,5,1,1.42857142857143,1.33333333333333,1.5,1.25,1.33333333333333,2.66666666666667
14 +MYP-A,MYP-B,MYE-1,.590202484187587,1,.368987291293523,.323024461107048,.815043514571968,.583194962820368,4,1,550,1,4,3,3,2,3,3,3,2,1,1,1,3,3,3,4,1,2,1.33333333333333,2.5,2.75,3,3
15 +MYP-B,MYP-C,MYE-2,.815043514571968,1,.583194962820368,.196928868040488,.616329920695494,.583194962820368,4,2,800,1,1,3,3,3,1,1,1,3,1,1,1,3,3,2,5,1,2,1.66666666666667,2.25,2.75,2.66666666666667,1
16 +MYP-C,MYP-D,MYE-3,.616329920695494,1,.583194962820368,.139495826712512,.553978652409579,.258191366612197,4,3,1050,1,3,3,4,3,3,3,1,1,1,2,1,1,1,3,4,1,1.42857142857143,1.33333333333333,1.5,1.5,1.66666666666667,2.33333333333333
17 +NEP-1,NEP-2,NEE-1,-1.24244675543348,0,-.807594384713811,-.0492601842688896,.102561854903987,-.113310856479496,7,1,3100,9,3,3,3,3,3,3,3,1,1,1,1,1,1,1,2,0,1,1,1,1,1,3
18 +NEP-2,NEP-3,NEE-2,.102561854903987,1,-.113310856479496,.504743247459502,1.05385205583673,.729949188656915,7,2,1450,9,3,3,4,3,4,4,4,1,1,2,1,2,2,2,2,0,1.57142857142857,1.33333333333333,1.75,1.75,2,4
19 +NMP-1,NMP-2,NME-1,.924470926040548,1,-.244646188673646,-.602533519831392,.749173359288767,.539661313876887,8,1,5200,1,4,3,4,3,4,4,4,2,1,2,1,2,2,2,4,1,1.71428571428571,1.66666666666667,1.75,2,2,4
20 +NMP-3,NMP-3,NME-2,1.19018383956698,1,.0640303234293974,-.322474473300953,1.19018383956698,.0640303234293974,8,2,4200,1,2,3,99,2,1,1,1,2,1,99,2,3,3,3,5,1,2.33333333333333,1.5,2.75,2.75,3,1
21 +SWP-A,SWP-A,SWE-1,-1.0834758803323,0,-1.45477526442727,-.292909292370296,-1.0834758803323,-1.45477526442727,3,1,1500,2,3,3,3,2,3,3,2,1,1,1,1,2,2,2,2,0,1.42857142857143,1,1.75,1.75,2,2.66666666666667
22 +SWP-A,SWP-B,SWE-2,-1.0834758803323,0,-1.45477526442727,-.292909292370296,.0309965762288839,.148286632933635,3,2,1250,2,4,3,3,3,2,3,3,2,1,1,2,2,2,3,2,0,1.85714285714286,1.33333333333333,2.25,2.25,2.33333333333333,2.66666666666667
23 +SWP-B,SWP-C,SWE-3,.0309965762288839,1,.148286632933635,-.292909292370296,.574820048798118,.0332014937648257,3,3,900,2,2,1,3,3,3,1,1,2,3,1,3,3,3,3,3,0,2.57142857142857,2,3,2.75,3,1.66666666666667
24 +
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AR-DA-V5-NW-PP.csv
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1 +ID,Name,IN_1,IN_2b,End,Sequence,SV_1,SV_1_Q,SV_1_R,SV_3,SV_3_Q,SV_3_R,SV_5,SV_5_Q,SV_5_R,SV_7,SV_7_Q,SV_7_R,SV_9,SV_9_Q,SV_9_R,SV_11,SV_11_Q,SV_11_R,SV_12,SV_12_Q,SV_12_R,SV_13,SV_13_Q,SV_13_R,PE_1,PE_1_Q,PE_1_R,PE_3,PE_3_Q,PE_3_R,PE_4,PE_4_Q,PE_4_R,PE_6,PE_6_Q,PE_6_R,PE_9,PE_9_Q,PE_9_R,PE_10,PE_10_Q,PE_10_R,PE_11,PE_11_Q,PE_11_R,PE_12,PE_12_Q,PE_12_R,PE_13,PE_13_Q,PE_13_R,PE_14,PE_14_Q,PE_14_R,PE_15,PE_15_Q,PE_15_R,PE_16,PE_16_Q,PE_16_R,PE_17,PE_17_Q,PE_17_R,PE_18,PE_18_Q,PE_18_R,PE_19,PE_19_Q,PE_19_R,TL_1,TL_1_Q,TL_1_R,TL_2,TL_2_Q,TL_2_R,TL_3,TL_3_Q,TL_3_R,TL_4,TL_4_Q,TL_4_R,TL_5,TL_5_Q,TL_5_R,TL_6,TL_6_Q,TL_6_R,TL_7,TL_7_Q,TL_7_R,TL_8,TL_8_Q,TL_8_R,TL_9,TL_9_Q,TL_9_R,TL_10,TL_10_Q,TL_10_R,TL_11,TL_11_Q,TL_11_R,TL_13,TL_13_Q,TL_13_R,TL_15,TL_15_Q,TL_15_R,TL_16,TL_16_Q,TL_16_R,TL_19,TL_19_Q,TL_19_R,TL_20,TL_20_Q,TL_20_R,TL_21,TL_21_Q,TL_21_R
2 +GLP-A,Point Peninsula,-.91801802575238,-1.04702404759072,1300,1,1,1,0,0,1,0,0,1,0,4,1,0,5,1,0,3,1,0,2,1,0,3,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,1,3,0,1,1,0,0,1,0,0,1,0,0,1,0,0,3,0,1,1,0,4,1,0,4,1,0,1,1,0,3,1,0,4,3,0,3,1,0,99,99,0,2,1,0, ,99,0, ,99,0,200,3,0,1,1,0,0,1,0,2,1,0,2,1,0,0,1,0,2,1,0
3 +GLP-B,Princess Point,-.91801802575238,-.900468338687846,1000,1,1,1,0,3,1,0,0,1,0,4,1,0,5,1,0,3,1,0,2,1,0,3,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,1,3,0,99,99,0,0,1,0,0,1,0,0,1,0,0,3,0,1,1,0,4,1,1,4,1,0,1,1,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0,Grand Banks,1,0,10,1,0,200,1,0,2,2,0,0,1,0,2,1,0,99,99,0,99,99,0,99,99,0
4 +GLP-C,Early Ontario Iroquois,-.91801802575238,-.106812472907335,750,1,4,2,1,4,1,0,0,1,0,4,1,0,5,1,0,1,1,0,2,1,0,3,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,1,3,1,1,3,1,0,1,0,0,1,0,0,1,0,0,3,0,1,1,0,4,1,1,4,1,1,1,1,1,2,1,0,4,3,0,99,99,0,99,99,0,2,1,0,Kraus,1,0,2,1,0,500,1,0,2,1,0,0,1,0,2,1,0,3,1,0,3,1,0,99,99,0
5 +GLP-D,Middle Ontario Iroquois,-.35856308446424,-.343753522089249,550,1,4,1,0,4,1,0,0,1,0,4,1,0,5,1,0,1,1,0,2,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,3,0,99,99,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,6,1,0,4,1,0,1,1,0,2,1,0,4,3,0,3,1,0,99,99,0,3,3,1,Laurenssen,1,0,2,1,1,720,1,0,2,1,0,0,1,0,2,1,0,3,1,0,3,1,0,99,99,0
6 +ABP-A,Havana Hopewell,-1.10394247609329,-1.2671836139135,1700,2,1,1,0,2,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,3,2,0,4,1,0,3,1,0,99,99,0,3,1,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,1,1,0,0,1,0,2,1,0,1,2,0,0,1,0,2,1,0
7 +ABP-B,Rosewood,-1.10394247609329,-.854983656653947,1550,2,1,1,0,2,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,99,99,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,2,1,0,1,1,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,2,1,0,0,1,0,2,1,0,2,1,0,0,1,0,2,1,0
8 +ABP-C,Mund,-1.10394247609329,-.854983656653947,1400,2,1,1,0,2,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,99,99,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,2,1,0,1,1,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,2,1,0,0,1,0,2,1,0,2,1,0,0,1,0,2,1,0
9 +ABP-D,Patrick,-1.10394247609329,-.463226915673791,1250,2,1,1,0,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,99,99,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,4,1,0,3,3,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,2,1,0,0,1,0,2,1,0,2,1,0,2,1,0,2,1,0
10 +ABP-E,Lohmann-Stirling,.939187279129317,-.056726992927785,800,2,77,1,0,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,4,3,0,1,1,0,4,1,0,4,1,0,2,3,0,2,1,0,99,99,0,4,3,0,5,3,0,1,3,0,99,99,0,1,3,0,4,1,0,3,1,0,2,1,0,2,3,0,3,3,0,6,1,0,4,1,0,7,1,0,3,1,0,8,3,0,6,3,0,8,1,0,5,1,0,Cahokia,1,0,1400,1,0,15000,1,0,3,1,0,0,1,0,2,1,0,2,1,0,2,1,0,2,1,0
11 +ABP-F,Moorehead,.96287589255106,.0496017095031256,725,2,77,1,0,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,4,1,0,1,1,0,4,1,0,4,1,0,2,3,0,2,1,0,99,99,0,4,3,0,5,3,0,99,99,0,99,99,0,99,99,0,4,1,0,3,1,0,2,1,0,99,99,0,3,3,0,6,1,0,4,3,0,7,1,0,3,1,0,8,3,0,6,3,0,8,3,0,2,1,0,Cahokia,1,0,1400,1,0,3000,1,0,3,1,0,0,1,0,2,1,0,2,1,0,2,1,0,99,99,0
12 +SWP-A,Pioneer/Formative,-.91801802575238,-1.46378648869071,1250,3,4,2,1,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,0,1,0,0,1,0,1,1,0,4,1,0,4,1,0,7,3,0,3,1,0,4,1,0,3,1,0,99,99,0,2,1,0, ,99,0, ,99,0, ,99,0,2,1,0,0,1,0,2,1,0,2,1,0,0,1,0,0,1,0
13 +SWP-B,Colonial/Preclassic,.213072806524376,.180521212165556,900,3,4,2,1,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,2,3,0,1,1,0,2,1,0,2,1,0,99,99,0,99,99,0,3,3,0,2,1,0,99,99,0,99,99,0,2,1,0,99,99,0,99,99,0,99,99,0,2,3,1,6,1,0,4,1,0,4,1,0,3,1,0,9,3,0,3,1,0,3,1,0,3,1,0,Snaketown,1,0,100,1,0,2000,1,0,2,1,0,2,1,1,3,1,0,2,1,0,3,1,0,3,1,0
14 +SWP-C,Classic,.687905367513675,.0576422099991029,550,3,4,2,1,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,6,2,1,1,1,0,88,2,1,1,1,0,2,1,0,2,1,0,99,99,0,2,1,0,4,3,0,4,3,0,99,99,0,99,99,0,4,1,0,3,1,0,3,3,0,99,99,0,1,3,0,6,1,0,3,1,1,7,1,0,2,1,0,8,1,0,99,99,0,99,99,0,5,1,0,Marana,1,0,600,1,0,1000,1,0,2,1,0,2,1,1,2,1,0,1,1,1,3,1,0,3,1,0
15 +MYP-A,Early Classic Maya,.788643787703707,.384291230700842,1400,4,4,1,0,4,1,0,1,1,0,5,1,1,5,1,0,2,1,0,2,1,0,1,3,0,3,1,0,3,1,0,3,1,0,4,1,0,2,1,0,4,1,0,4,1,0,99,99,0,3,1,0,99,99,0,3,1,0,3,1,0,3,1,0,2,3,0,2,3,1,6,1,0,3,1,0,7,1,0,3,1,1,8,3,0,5,1,0,8,1,0,4,2,0,Tikal,2,0,12000,1,0,45000,2,0,2,1,0,2,2,0,3,2,0,2,1,0,3,2,0,3,2,1
16 +MYP-B,Middle Classic May,1.00710209119518,.582502825393933,1100,4,4,1,0,4,1,0,2,1,0,4,1,0,5,2,0,3,2,0,2,1,0,1,3,0,4,1,1,3,1,0,3,1,0,4,1,0,2,3,0,4,1,0,4,1,1,99,99,0,99,99,1,3,1,0,3,1,0,3,1,0,3,1,0,99,99,0,3,3,0,6,1,0,3,1,0,8,1,0,88,3,1,9,1,0,5,1,1,8,1,0,5,2,0,Tikal,1,0,12000,1,0,62000,1,0,2,1,0,3,2,1,99,99,0,2,1,0,3,3,0,3,1,0
17 +MYP-C,Late Classic Maya,.774696528269047,.582502825393933,1000,4,4,2,1,4,2,0,1,2,0,4,3,0,5,3,0,1,3,0,3,2,1,1,3,0,3,2,0,3,1,0,3,3,0,4,2,0,2,3,0,4,1,1,4,2,0,3,3,1,4,2,0,99,99,1,3,1,0,3,1,0,3,1,0,99,99,0,2,3,0,6,1,0,3,1,0,8,1,0,3,2,0,9,2,0,5,3,0,8,2,0,4,2,0,Tikal,2,0,99,99,0,10000,2,0,2,3,0,3,1,0,3,3,0,2,1,0,3,1,1,3,2,0
18 +MYP-D,Postclassic Maya,.728538315594679,.24901059432736,750,4,4,1,0,4,1,0,1,2,0,4,2,0,5,1,0,2,3,1,3,2,1,1,1,0,2,2,0,2,2,0,3,2,0,5,2,1,3,3,0,99,99,0,2,1,0,99,99,1,99,99,0,3,3,0,3,1,0,99,99,0,3,3,1,99,99,0,2,3,0,6,1,0,3,1,0,8,1,0,99,99,0,99,99,0,5,2,0,8,2,0,4,2,0,Coba,2,0,7000,3,0,21000,3,0,3,1,1,2,3,0,99,99,0,2,1,0,2,1,0,3,1,1
19 +MOP-A,Early Moche,.905135309440315,.853247112749737,1700,5,2,1,0,4,1,0,3,1,0,5,1,0,5,1,0,3,1,0,7,1,0,1,1,0,4,1,0,4,1,0,3,1,0,2,3,0,2,3,1,4,1,0,3,2,1,3,2,0,2,2,1,2,2,0,4,1,0,3,3,0,3,3,0,2,2,1,2,2,0,6,1,0,88,88,0,8,1,0,3,2,0,9,1,0,5,1,0,8,1,0,4,1,0, ,99,0,99,99,0,10000,3,0,3,1,0,3,1,0,2,1,0,3,2,0,3,1,0,3,1,0
20 +MOP-B,Middle Moche,.817261490380301,.853247112749737,1450,5,4,3,0,4,1,0,3,1,0,5,1,0,5,1,0,2,1,0,7,2,0,1,1,0,4,1,0,3,1,0,3,2,0,4,2,0,3,3,1,4,1,0,4,1,0,2,2,0,2,2,0,2,2,0,3,2,0,3,2,0,2,1,0,99,99,0,3,1,0,6,1,0,88,88,0,8,1,0,3,1,0,9,1,0,5,1,0,8,1,0,4,1,0,Moche,1,0,300,1,0,10000,1,0,3,1,0,3,1,0,2,1,0,3,1,0,3,2,1,3,1,0
21 +MOP-C,Late Moche,.636771307051804,.993629473490705,1250,5,4,3,0,5,1,0,3,1,0,5,1,0,5,1,0,2,1,0,7,1,0,1,1,0,4,1,0,3,2,0,3,2,0,4,2,0,3,2,0,3,2,1,3,2,0,2,2,0,3,3,1,2,2,0,3,2,0,3,2,0,2,2,0,2,2,0,2,3,0,6,1,0,88,88,0,8,1,0,3,1,0,9,1,0,6,1,0,8,1,0,5,1,0,Galindo,1,0,600,1,0,99,99,0,3,1,0,3,1,0,2,1,0,3,1,0,3,1,0,3,1,0
22 +MOP-D,Chimu,1.25444220062779,.853247112749737,480,5,4,1,0,5,1,0,2,1,0,5,1,0,1,3,0,1,2,0,7,1,0,4,1,0,4,1,0,4,1,0,4,1,0,2,1,0,4,1,0,3,1,0,5,1,0,3,2,0,2,1,0,3,3,0,4,1,0,3,1,0,2,1,0,4,3,0,3,3,0,6,1,0,88,88,0,8,1,0,3,1,1,9,1,0,5,2,1,8,1,0,4,1,0,Chan-Chan,1,0,2000,1,0,30000,1,0,2,1,0,3,1,1,3,1,0,3,1,0,3,1,0,3,1,1
23 + , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
24 +
AR-DA-V5-NW-PP.sav
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Content
AR-DA-V5-PP.csv
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1 +Preceding_Period,Name,Start,End,Sequence,SV_1,SV_1_Q,SV_1_R,SV_3,SV_3_Q,SV_3_R,SV_5,SV_5_Q,SV_5_R,SV_7,SV_7_Q,SV_7_R,SV_9,SV_9_Q,SV_9_R,SV_11,SV_11_Q,SV_11_R,SV_12,SV_12_Q,SV_12_R,SV_13,SV_13_Q,SV_13_R,PE_1,PE_1_Q,PE_1_R,PE_3,PE_3_Q,PE_3_R,PE_4,PE_4_Q,PE_4_R,PE_6,PE_6_Q,PE_6_R,PE_9,PE_9_Q,PE_9_R,PE_10,PE_10_Q,PE_10_R,PE_11,PE_11_Q,PE_11_R,PE_12,PE_12_Q,PE_12_R,PE_13,PE_13_Q,PE_13_R,PE_14,PE_14_Q,PE_14_R,PE_15,PE_15_Q,PE_15_R,PE_16,PE_16_Q,PE_16_R,PE_17,PE_17_Q,PE_17_R,PE_18,PE_18_Q,PE_18_R,PE_19,PE_19_Q,PE_19_R,TL_1,TL_1_Q,TL_1_R,TL_2,TL_2_Q,TL_2_R,TL_3,TL_3_Q,TL_3_R,TL_4,TL_4_Q,TL_4_R,TL_5,TL_5_Q,TL_5_R,TL_6,TL_6_Q,TL_6_R,TL_7,TL_7_Q,TL_7_R,TL_8,TL_8_Q,TL_8_R,TL_9,TL_9_Q,TL_9_R,TL_10,TL_10_Q,TL_10_R,TL_11,TL_11_Q,TL_11_R,TL_13,TL_13_Q,TL_13_R,TL_15,TL_15_Q,TL_15_R,TL_16,TL_16_Q,TL_16_R,TL_19,TL_19_Q,TL_19_R,TL_20,TL_20_Q,TL_20_R,TL_21,TL_21_Q,TL_21_R
2 +GLP-A,Point Peninsula,2300,1300,1,1,1,0,0,1,0,0,1,0,4,1,0,5,1,0,3,1,0,2,1,0,3,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,1,3,0,1,1,0,0,1,0,0,1,0,0,1,0,0,3,0,1,1,0,4,1,0,4,1,0,1,1,0,3,1,0,4,3,0,3,1,0,99,99,0,2,1,0, ,99,0, ,99,0,200,3,0,1,1,0,0,1,0,2,1,0,2,1,0,0,1,0,2,1,0
3 +GLP-B,Princess Point,1300,1000,1,1,1,0,3,1,0,0,1,0,4,1,0,5,1,0,3,1,0,2,1,0,3,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,1,3,0,99,99,0,0,1,0,0,1,0,0,1,0,0,3,0,1,1,0,4,1,1,4,1,0,1,1,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0,Grand Banks,1,0,10,1,0,200,1,0,2,2,0,0,1,0,2,1,0,99,99,0,99,99,0,99,99,0
4 +GLP-C,Early Ontario Iroquois,1000,750,1,4,2,1,4,1,0,0,1,0,4,1,0,5,1,0,1,1,0,2,1,0,3,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,1,3,1,1,3,1,0,1,0,0,1,0,0,1,0,0,3,0,1,1,0,4,1,1,4,1,1,1,1,1,2,1,0,4,3,0,99,99,0,99,99,0,2,1,0,Kraus,1,0,2,1,0,500,1,0,2,1,0,0,1,0,2,1,0,3,1,0,3,1,0,99,99,0
5 +GLP-D,Middle Ontario Iroquois,750,550,1,4,1,0,4,1,0,0,1,0,4,1,0,5,1,0,1,1,0,2,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,1,3,0,99,99,0,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,6,1,0,4,1,0,1,1,0,2,1,0,4,3,0,3,1,0,99,99,0,3,3,1,Laurenssen,1,0,2,1,1,720,1,0,2,1,0,0,1,0,2,1,0,3,1,0,3,1,0,99,99,0
6 +ABP-A,Havana Hopewell,2150,1700,2,1,1,0,2,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,3,2,0,4,1,0,3,1,0,99,99,0,3,1,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,1,1,0,0,1,0,2,1,0,1,2,0,0,1,0,2,1,0
7 +ABP-B,Rosewood,1700,1550,2,1,1,0,2,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,99,99,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,2,1,0,1,1,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,2,1,0,0,1,0,2,1,0,2,1,0,0,1,0,2,1,0
8 +ABP-C,Mund,1550,1400,2,1,1,0,2,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,99,99,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,2,1,0,1,1,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,2,1,0,0,1,0,2,1,0,2,1,0,0,1,0,2,1,0
9 +ABP-D,Patrick,1400,1250,2,1,1,0,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,99,99,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,0,5,1,0,4,1,0,3,3,0,3,1,0,99,99,0,99,99,0,99,99,0,2,1,0, ,99,0,2,2,0,200,2,0,2,1,0,0,1,0,2,1,0,2,1,0,2,1,0,2,1,0
10 +ABP-E,Lohmann-Stirling,950,800,2,77,1,0,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,4,3,0,1,1,0,4,1,0,4,1,0,2,3,0,2,1,0,99,99,0,4,3,0,5,3,0,1,3,0,99,99,0,1,3,0,4,1,0,3,1,0,2,1,0,2,3,0,3,3,0,6,1,0,4,1,0,7,1,0,3,1,0,8,3,0,6,3,0,8,1,0,5,1,0,Cahokia,1,0,1400,1,0,15000,1,0,3,1,0,0,1,0,2,1,0,2,1,0,2,1,0,2,1,0
11 +ABP-F,Moorehead,800,725,2,77,1,0,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,4,1,0,1,1,0,4,1,0,4,1,0,2,3,0,2,1,0,99,99,0,4,3,0,5,3,0,99,99,0,99,99,0,99,99,0,4,1,0,3,1,0,2,1,0,99,99,0,3,3,0,6,1,0,4,3,0,7,1,0,3,1,0,8,3,0,6,3,0,8,3,0,2,1,0,Cahokia,1,0,1400,1,0,3000,1,0,3,1,0,0,1,0,2,1,0,2,1,0,2,1,0,99,99,0
12 +SWP-A,Pioneer/Formative,2000,1250,3,4,2,1,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,0,1,0,0,1,0,1,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1,0,0,1,0,0,1,0,1,1,0,4,1,0,4,1,0,7,3,0,3,1,0,4,1,0,3,1,0,99,99,0,2,1,0, ,99,0, ,99,0, ,99,0,2,1,0,0,1,0,2,1,0,2,1,0,0,1,0,0,1,0
13 +SWP-B,Colonial/Preclassic,1250,900,3,4,2,1,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,2,1,0,1,1,0,2,3,0,1,1,0,2,1,0,2,1,0,99,99,0,99,99,0,3,3,0,2,1,0,99,99,0,99,99,0,2,1,0,99,99,0,99,99,0,99,99,0,2,3,1,6,1,0,4,1,0,4,1,0,3,1,0,9,3,0,3,1,0,3,1,0,3,1,0,Snaketown,1,0,100,1,0,2000,1,0,2,1,0,2,1,1,3,1,0,2,1,0,3,1,0,3,1,0
14 +SWP-C,Classic,900,550,3,4,2,1,3,1,0,0,1,0,4,1,0,5,1,0,2,1,0,6,2,1,1,1,0,88,2,1,1,1,0,2,1,0,2,1,0,99,99,0,2,1,0,4,3,0,4,3,0,99,99,0,99,99,0,4,1,0,3,1,0,3,3,0,99,99,0,1,3,0,6,1,0,3,1,1,7,1,0,2,1,0,8,1,0,99,99,0,99,99,0,5,1,0,Marana,1,0,600,1,0,1000,1,0,2,1,0,2,1,1,2,1,0,1,1,1,3,1,0,3,1,0
15 +MYP-A,Early Classic Maya,1750,1400,4,4,1,0,4,1,0,1,1,0,5,1,1,5,1,0,2,1,0,2,1,0,1,3,0,3,1,0,3,1,0,3,1,0,4,1,0,2,1,0,4,1,0,4,1,0,99,99,0,3,1,0,99,99,0,3,1,0,3,1,0,3,1,0,2,3,0,2,3,1,6,1,0,3,1,0,7,1,0,3,1,1,8,3,0,5,1,0,8,1,0,4,2,0,Tikal,2,0,12000,1,0,45000,2,0,2,1,0,2,2,0,3,2,0,2,1,0,3,2,0,3,2,1
16 +MYP-B,Middle Classic May,1400,1100,4,4,1,0,4,1,0,2,1,0,4,1,0,5,2,0,3,2,0,2,1,0,1,3,0,4,1,1,3,1,0,3,1,0,4,1,0,2,3,0,4,1,0,4,1,1,99,99,0,99,99,1,3,1,0,3,1,0,3,1,0,3,1,0,99,99,0,3,3,0,6,1,0,3,1,0,8,1,0,88,3,1,9,1,0,5,1,1,8,1,0,5,2,0,Tikal,1,0,12000,1,0,62000,1,0,2,1,0,3,2,1,99,99,0,2,1,0,3,3,0,3,1,0
17 +MYP-C,Late Classic Maya,1100,1000,4,4,2,1,4,2,0,1,2,0,4,3,0,5,3,0,1,3,0,3,2,1,1,3,0,3,2,0,3,1,0,3,3,0,4,2,0,2,3,0,4,1,1,4,2,0,3,3,1,4,2,0,99,99,1,3,1,0,3,1,0,3,1,0,99,99,0,2,3,0,6,1,0,3,1,0,8,1,0,3,2,0,9,2,0,5,3,0,8,2,0,4,2,0,Tikal,2,0,99,99,0,10000,2,0,2,3,0,3,1,0,3,3,0,2,1,0,3,1,1,3,2,0
18 +MYP-D,Postclassic Maya,1000,750,4,4,1,0,4,1,0,1,2,0,4,2,0,5,1,0,2,3,1,3,2,1,1,1,0,2,2,0,2,2,0,3,2,0,5,2,1,3,3,0,99,99,0,2,1,0,99,99,1,99,99,0,3,3,0,3,1,0,99,99,0,3,3,1,99,99,0,2,3,0,6,1,0,3,1,0,8,1,0,99,99,0,99,99,0,5,2,0,8,2,0,4,2,0,Coba,2,0,7000,3,0,21000,3,0,3,1,1,2,3,0,99,99,0,2,1,0,2,1,0,3,1,1
19 +MOP-A,Early Moche,1900,1700,5,2,1,0,4,1,0,3,1,0,5,1,0,5,1,0,3,1,0,7,1,0,1,1,0,4,1,0,4,1,0,3,1,0,2,3,0,2,3,1,4,1,0,3,2,1,3,2,0,2,2,1,2,2,0,4,1,0,3,3,0,3,3,0,2,2,1,2,2,0,6,1,0,88,88,0,8,1,0,3,2,0,9,1,0,5,1,0,8,1,0,4,1,0, ,99,0,99,99,0,10000,3,0,3,1,0,3,1,0,2,1,0,3,2,0,3,1,0,3,1,0
20 +MOP-B,Middle Moche,1700,1450,5,4,3,0,4,1,0,3,1,0,5,1,0,5,1,0,2,1,0,7,2,0,1,1,0,4,1,0,3,1,0,3,2,0,4,2,0,3,3,1,4,1,0,4,1,0,2,2,0,2,2,0,2,2,0,3,2,0,3,2,0,2,1,0,99,99,0,3,1,0,6,1,0,88,88,0,8,1,0,3,1,0,9,1,0,5,1,0,8,1,0,4,1,0,Moche,1,0,300,1,0,10000,1,0,3,1,0,3,1,0,2,1,0,3,1,0,3,2,1,3,1,0
21 +MOP-C,Late Moche,1450,1250,5,4,3,0,5,1,0,3,1,0,5,1,0,5,1,0,2,1,0,7,1,0,1,1,0,4,1,0,3,2,0,3,2,0,4,2,0,3,2,0,3,2,1,3,2,0,2,2,0,3,3,1,2,2,0,3,2,0,3,2,0,2,2,0,2,2,0,2,3,0,6,1,0,88,88,0,8,1,0,3,1,0,9,1,0,6,1,0,8,1,0,5,1,0,Galindo,1,0,600,1,0,99,99,0,3,1,0,3,1,0,2,1,0,3,1,0,3,1,0,3,1,0
22 +MOP-D,Chimu,1250,480,5,4,1,0,5,1,0,2,1,0,5,1,0,1,3,0,1,2,0,7,1,0,4,1,0,4,1,0,4,1,0,4,1,0,2,1,0,4,1,0,3,1,0,5,1,0,3,2,0,2,1,0,3,3,0,4,1,0,3,1,0,2,1,0,4,3,0,3,3,0,6,1,0,88,88,0,8,1,0,3,1,1,9,1,0,5,2,1,8,1,0,4,1,0,Chan-Chan,1,0,2000,1,0,30000,1,0,2,1,0,3,1,1,3,1,0,3,1,0,3,1,0,3,1,1
23 +EGP-1,Lower Egypt Predynastic,7000,5100,6,88,2,0,2,1,0,1,1,0,5,1,0,4,1,0,3,1,0,2,1,0,3,1,0,0,2,0,0,2,0,1,2,0,1,2,0,0,2,0,0,2,0,5,2,0,0,2,0,0,1,0,99,99,0,0,2,1,0,2,0,0,1,0,0,2,0,0,1,0,6,1,0,3,2,1,1,1,0,3,1,0,4,1,0,3,1,0,99,99,0,2,1,0, ,99,0,99,99,0,99,99,0,2,1,0,2,1,0,3,3,0,2,1,0,0,1,0,0,1,0
24 +EGP-2,Early Dynastic Egypt,5100,4200,6,88,2,0,3,1,0,2,1,0,4,1,0,5,1,0,2,2,0,6,1,0,1,1,0,4,1,0,4,1,0,3,1,0,3,1,0,2,1,0,4,1,0,4,1,0,3,1,1,2,1,1,2,1,0,3,1,0,3,1,0,3,1,0,3,1,0,3,1,0,6,1,0,4,1,1,8,1,0,3,3,0,9,1,0,5,1,0,8,1,0,4,3,0,Memphis,1,0,99,99,0,99,99,0,2,1,0,2,1,0,3,3,0,2,1,0,3,1,0,2,1,0
25 +EGP-3,First Intermediate Period,4200,4000,6,4,1,0,3,1,0,3,1,0,4,1,0,5,1,0,3,1,0,2,1,0,1,1,0,4,1,0,4,1,0,4,1,0,3,1,0,2,1,0,3,2,0,4,1,0,2,1,1,2,1,1,3,1,0,4,1,0,3,1,0,3,1,0,4,1,0,3,1,0,6,1,0,4,1,1,8,1,0,4,1,0,9,2,0,5,1,0,8,3,0,5,1,0,Memphis,1,0,99,99,0,99,99,0,2,1,0,3,1,0,3,3,0,3,1,0,3,2,0,3,1,0
26 +NMP-1,Uruk,6000,5200,7,4,1,0,3,1,0,1,1,0,2,2,0,2,1,0,1,2,0,3,2,0,1,1,0,3,2,0,2,1,0,2,1,0,2,1,0,2,1,0,3,1,0,3,1,0,3,2,0,4,2,0,3,1,0,3,2,0,99,99,0,4,1,0,2,1,0,99,99,0,6,1,0,4,1,0,8,1,0,3,1,0,9,1,0,5,2,0,4,1,0,4,1,0,Uruk,1,0,200,1,0,20000,1,0,2,1,0,2,1,0,2,1,0,1,1,0,1,1,0,2,1,0
27 +NMP-2,Sumerian,5200,4300,7,4,1,0,3,1,0,2,1,0,4,1,0,5,1,0,2,2,0,6,1,0,1,1,0,4,1,0,4,1,0,4,1,0,3,1,0,4,1,0,2,2,0,4,1,0,2,2,0,3,1,0,3,1,0,3,1,0,3,2,0,3,1,0,2,2,0,3,2,0,6,1,0,4,1,0,8,1,0,3,1,0,9,1,0,5,1,0,7,1,0,4,1,0,Umma,1,0,400,1,0,26000,1,0,3,1,0,3,1,0,3,3,0,3,1,0,2,1,0,2,1,0
28 +NMP-3,Akkadian,4300,4200,7,99,99,0,2,1,0,3,1,0,2,1,0,88,88,0,1,2,0,6,1,0,1,1,0,99,99,0,99,99,0,3,2,0,4,2,0,2,2,0,3,1,0,4,1,1,2,2,0,3,1,0,3,1,0,3,1,0,4,1,0,3,2,0,3,2,0,4,2,0,6,1,0,4,1,0,8,1,0,3,1,0,8,1,0,5,1,0,8,1,0,5,1,0,Tell Brak,1,0,100,1,0,99,99,0,2,1,0,2,1,0,2,3,0,2,2,0,2,3,0,2,2,0
29 +NEP-1,Early Nordic Bronze Age,3700,3100,8,4,3,0,1,1,0,2,1,0,5,1,0,5,1,0,3,1,0,2,3,0,3,1,0,0,1,0,0,1,0,1,3,0,1,3,0,0,1,0,0,1,0,1,3,0,0,2,0,4,3,0,99,99,0,0,2,0,0,2,0,0,2,0,0,2,0,0,1,0,6,2,0,2,2,0,1,3,0,4,2,0,9,1,0,99,99,0,4,3,1,2,2,0, ,99,0,99,99,0,99,99,0,1,1,1,3,1,0,2,1,0,1,2,1,0,2,0,0,1,0
30 +NEP-2,Late Nordic Bronze Age,3100,2550,8,4,3,0,1,1,0,3,2,0,5,1,0,5,1,0,3,1,0,6,3,0,3,3,0,2,3,0,3,3,0,99,99,0,99,99,0,2,3,0,99,99,0,1,2,0,2,3,0,88,3,0,4,3,0,99,99,0,99,99,0,99,99,1,99,99,0,2,3,0,5,2,0,3,1,0,1,3,1,4,1,0,8,2,0,5,1,0,4,2,0,2,2,0, ,99,0,99,99,0,99,99,0,2,1,0,3,2,0,2,2,0,2,2,0,1,3,0,1,3,0
31 +NEP-3,Pre-Roman Iron Age,2550,1500,8,5,1,1,3,1,0,4,1,0,4,1,0,5,1,0,1,1,0,6,1,0,3,3,0,4,1,0,3,1,0,99,99,0,99,99,1,99,99,0,99,99,0,1,1,0,99,99,0,2,3,0,99,99,0,3,1,1,3,1,0,3,3,0,3,3,0,4,1,0,6,1,0,1,1,0,7,3,0,4,1,0,8,1,0,5,1,0,7,1,0,88,2,0, ,99,0,99,99,0,99,99,0,3,1,0,3,1,0,3,1,0,3,3,0,99,99,0,99,99,0
32 +IRP-1,Middle Harappa,4450,4200,9,5,1,0,2,1,0,2,1,0,4,1,0,4,1,0,3,1,0,2,1,0,1,1,0,2,1,0,1,2,0,3,3,0,3,3,0,99,99,1,2,1,0,3,1,0,3,1,0,3,1,0,3,3,0,2,3,0,2,1,0,1,1,0,1,1,0,3,1,0,6,1,0,4,1,0,8,1,0,3,1,0,9,1,0,3,1,0,7,1,0,3,3,1,Mohenjo Daro,1,0,200,1,0,40000,1,0,2,1,0,2,1,0,2,1,0,2,1,0,3,3,0,3,1,0
33 +IRP-2,Final Harappa,4200,4000,9,5,1,0,2,1,0,2,1,0,4,1,0,4,1,0,2,1,0,2,1,0,1,1,0,2,1,0,1,2,0,3,3,0,3,3,0,99,99,1,2,1,0,3,1,0,3,1,0,3,1,0,3,3,0,2,3,0,2,1,0,1,1,0,1,1,0,3,1,0,6,1,0,4,1,0,8,1,0,3,1,0,9,1,0,3,1,0,7,1,0,3,3,1,Mohenjo Daro,1,0,200,1,0,50000,1,0,3,1,0,3,1,0,2,1,0,2,1,0,3,3,0,3,1,0
34 +
AR-DA-V5-PP.sav
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ARO Codebook_5.pdf
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CDD_CWD_Combined.xlsx
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CDS_Combined_ann.xlsx
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CSDI_Combined.xlsx
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1 +SCCS_ID,language_family,Chronic_Scarcity,Other_Hazards,Famine,ZNatural_Hazards,ZChronic_Scarcity,ZFamine,SCCS_Abundance_imp,ZSCCS_Abundance_imp,Social_Complexity,SocialComplexity_TRUN,LS4_Res_IA_2,S3_Resolved_IA_TR,G1_Associated,G2_Harm,G3_Help,G4_Punitive,SG1_Associated,SG2_Harm,SG3_Help,SG4_Punitive,MS1_Associated,MS2_Harm,MS3_Help,MS4_Punitive
2 +1,Khoe-Kwadi,NA,2,NA,-0.545126265,NA,NA,-1.110426279,-1.110426279,18,0,NA,NA,NA,NA,NA,NA,1,1,1,1,NA,NA,NA,NA
3 +2,Kxa,3,4,NA,1.165442359,1.353222151,NA,-0.423591805,-0.423591805,12,0,0,1,1,NA,1,1,1,NA,NA,1,1,NA,NA,0
4 +3,Atlantic-Congo,NA,NA,NA,NA,NA,NA,1.02242802,1.02242802,30,1,NA,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
5 +4,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.306044252,0.306044252,30,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
6 +5,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.593094996,0.593094996,32,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
7 +6,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.265493544,0.265493544,30,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
8 +7,Atlantic-Congo,NA,NA,NA,NA,NA,NA,1.319502945,1.319502945,28,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
9 +8,Atlantic-Congo,1,2,1,-0.545126265,-0.811933291,-1.117646018,1.359407527,1.359407527,28,1,0,0,0,0,0,0,1,1,1,1,1,1,1,0
10 +9,NA,1,3,1,0.310158047,-0.811933291,-1.117646018,1.038279333,1.038279333,10,0,NA,0,NA,NA,NA,NA,1,NA,NA,1,NA,NA,NA,NA
11 +10,Atlantic-Congo,NA,NA,NA,NA,NA,NA,1.109554289,1.109554289,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
12 +11,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.949046335,0.949046335,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
13 +12,Atlantic-Congo,NA,2,3.5,-0.545126265,NA,1.389893125,1.039498936,1.039498936,37,2,0,1,0,0,0,0,1,1,1,1,NA,NA,NA,NA
14 +13,Atlantic-Congo,1,1,1,-1.400410576,-0.811933291,-1.117646018,1.406768811,1.406768811,10,0,0,0,1,NA,NA,0,1,NA,NA,NA,NA,NA,NA,NA
15 +14,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.735994798,0.735994798,30,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
16 +15,Atlantic-Congo,NA,NA,NA,NA,NA,NA,1.449111137,1.449111137,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
17 +16,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.202387114,0.202387114,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
18 +17,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.551650975,0.551650975,34,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
19 +18,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.220581286,0.220581286,40,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
20 +19,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.763841985,0.763841985,34,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
21 +20,Mande,NA,NA,NA,NA,NA,NA,0.868982493,0.868982493,32,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
22 +21,Atlantic-Congo,3,3,2,0.310158047,1.353222151,-0.114630361,-0.871992271,-0.871992271,39,2,1,1,NA,NA,NA,NA,NA,NA,NA,NA,1,1,1,1
23 +22,Mande,NA,3,NA,0.310158047,NA,NA,-0.292002963,-0.292002963,38,2,1,1,NA,NA,NA,NA,NA,NA,NA,NA,1,1,1,1
24 +23,Atlantic-Congo,2,4,2,1.165442359,0.27064443,-0.114630361,-0.011906629,-0.011906629,32,1,1,1,NA,NA,NA,NA,1,1,NA,1,1,1,1,1
25 +24,Songhay,NA,2,NA,-0.545126265,NA,NA,-1.541326519,-1.541326519,36,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
26 +25,Atlantic-Congo,2,3,3,0.310158047,0.27064443,0.888385296,-1.301598485,-1.301598485,16,0,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,1
27 +26,Afro-Asiatic,2,4,4,1.165442359,0.27064443,1.891400953,0.313676203,0.313676203,43,2,1,NA,1,1,NA,1,1,1,NA,1,NA,NA,NA,NA
28 +27,Afro-Asiatic,1,2,3,-0.545126265,-0.811933291,0.888385296,-0.205671644,-0.205671644,27,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
29 +28,Atlantic-Congo,NA,NA,NA,NA,NA,NA,0.585172296,0.585172296,31,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
30 +29,Furan,1,2,2,-0.545126265,-0.811933291,-0.114630361,-1.242422091,-1.242422091,37,2,1,NA,1,NA,1,1,0,0,0,0,1,0,0,0
31 +30,Heibanic,4,4,4,1.165442359,2.435799873,1.891400953,-0.724205135,-0.724205135,28,1,1,1,1,1,1,0,NA,NA,NA,NA,NA,NA,NA,1
32 +31,Nilotic,NA,NA,NA,NA,NA,NA,-0.30238075,-0.30238075,33,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
33 +32,Blue Nile Mao,1,2,NA,-0.545126265,-0.811933291,NA,-0.001028103,-0.001028103,25,0,NA,1,0,0,0,0,1,NA,1,NA,NA,NA,NA,NA
34 +33,Ta-Ne-Omotic,NA,NA,NA,NA,NA,NA,0.489371626,0.489371626,35,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
35 +34,Nilotic,NA,4,3,1.165442359,NA,0.888385296,1.083773715,1.083773715,19,0,NA,0,1,1,NA,1,1,0,1,0,NA,NA,NA,NA
36 +35,Afro-Asiatic,1,NA,2,NA,-0.811933291,-0.114630361,0.026704249,0.026704249,34,1,NA,1,1,1,1,1,NA,NA,NA,NA,1,NA,0,0
37 +36,Afro-Asiatic,NA,2,2,-0.545126265,NA,-0.114630361,-1.305540471,-1.305540471,28,1,0,1,1,1,1,NA,1,NA,NA,NA,1,NA,NA,0
38 +37,Afro-Asiatic,1,1,2,-1.400410576,-0.811933291,-0.114630361,-0.339668453,-0.339668453,42,2,1,1,1,1,1,1,NA,NA,NA,NA,1,NA,NA,NA
39 +38,Afro-Asiatic,NA,NA,NA,NA,NA,NA,-1.250864241,-1.250864241,27,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
40 +39,Nubian,NA,NA,3.5,NA,NA,1.389893125,-3.159223328,-3.159223328,34,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
41 +40,Saharan,4,4,3,1.165442359,2.435799873,0.888385296,-2.876038126,-2.876038126,21,0,NA,1,1,1,NA,NA,NA,NA,NA,NA,1,1,0,NA
42 +41,Afro-Asiatic,NA,NA,NA,NA,NA,NA,-2.751136511,-2.751136511,26,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
43 +42,Afro-Asiatic,3,2,2,-0.545126265,1.353222151,-0.114630361,-1.36930785,-1.36930785,42,2,1,1,1,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA
44 +43,Afro-Asiatic,2,4,NA,1.165442359,0.27064443,NA,-2.66273082,-2.66273082,47,2,NA,1,1,1,1,1,NA,NA,NA,NA,0,0,0,0
45 +44,Afro-Asiatic,1,2,2,-0.545126265,-0.811933291,-0.114630361,-1.536784803,-1.536784803,46,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
46 +45,Afro-Asiatic,NA,2,NA,-0.545126265,NA,NA,-2.593788647,-2.593788647,49,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
47 +46,Afro-Asiatic,NA,4,3,1.165442359,NA,0.888385296,-2.214468868,-2.214468868,23,0,NA,NA,1,NA,1,0,1,1,1,1,1,NA,1,NA
48 +47,Turkic,3,4,3,1.165442359,1.353222151,0.888385296,-0.411152163,-0.411152163,48,2,NA,NA,1,1,NA,1,NA,NA,NA,NA,1,NA,NA,NA
49 +48,Indo-European,NA,NA,NA,NA,NA,NA,0.222075523,0.222075523,36,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
50 +49,Indo-European,NA,NA,NA,NA,NA,NA,-0.187607934,-0.187607934,49,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
51 +50,Basque,NA,NA,NA,NA,NA,NA,0.01480539,0.01480539,47,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
52 +51,Indo-European,2,NA,NA,-1.400410576,0.27064443,NA,-0.030757432,-0.030757432,47,2,1,1,0,0,0,0,NA,NA,NA,NA,1,NA,1,NA
53 +52,Uralic,NA,1,1,-1.400410576,NA,-1.117646018,-0.766077663,-0.766077663,18,0,1,1,NA,NA,NA,NA,1,1,1,1,1,NA,NA,NA
54 +53,Uralic,2,4,3,1.165442359,0.27064443,0.888385296,-0.976789891,-0.976789891,18,0,1,NA,1,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA
55 +54,Indo-European,1,4,NA,1.165442359,-0.811933291,NA,0.241671524,0.241671524,48,2,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
56 +55,Abkhaz-Adyge,1,3,NA,0.310158047,-0.811933291,NA,0.085190164,0.085190164,36,1,1,NA,1,NA,1,1,1,1,1,1,NA,NA,NA,NA
57 +56,Indo-European,NA,NA,NA,NA,NA,NA,-0.153334246,-0.153334246,43,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
58 +57,Indo-European,NA,1,1,-1.400410576,NA,-1.117646018,-1.252771783,-1.252771783,43,2,NA,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
59 +58,Indo-European,1,2,1,-0.545126265,-0.811933291,-1.117646018,-1.957393684,-1.957393684,25,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
60 +59,Indo-European,2,3,3,0.310158047,0.27064443,0.888385296,-1.213571865,-1.213571865,45,2,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
61 +60,Dravidian,1,1,1,-1.400410576,-0.811933291,-1.117646018,-0.213627236,-0.213627236,27,1,0,1,1,NA,NA,NA,1,0,1,0,NA,NA,NA,NA
62 +61,Dravidian,NA,NA,NA,NA,NA,NA,0.539954324,0.539954324,19,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
63 +62,Austroasiatic,3,2,NA,-0.545126265,1.353222151,NA,-0.441295394,-0.441295394,31,1,NA,0,1,1,1,0,NA,NA,NA,NA,1,NA,1,1
64 +63,Indo-European,NA,2,NA,-0.545126265,NA,NA,-0.804549287,-0.804549287,50,2,NA,NA,0,0,0,0,1,NA,1,NA,1,NA,1,NA
65 +64,NA,2,1,NA,-1.400410576,0.27064443,NA,-0.639041621,-0.639041621,33,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
66 +65,Turkic,1.5,3,3,0.310158047,-0.27064443,0.888385296,-0.296912891,-0.296912891,30,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
67 +66,Mongolic,NA,4,2,1.165442359,NA,-0.114630361,-0.20565455,-0.20565455,32,1,1,1,1,NA,1,NA,1,1,1,0,1,1,1,1
68 +67,Sino-Tibetan,NA,NA,NA,NA,NA,NA,0.996315979,0.996315979,35,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
69 +68,Sino-Tibetan,1,1,1,-1.400410576,-0.811933291,-1.117646018,1.213261184,1.213261184,32,1,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA
70 +69,Sino-Tibetan,NA,NA,NA,NA,NA,NA,0.456514054,0.456514054,31,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
71 +70,Sino-Tibetan,NA,3,3,0.310158047,NA,0.888385296,0.497973312,0.497973312,31,1,NA,1,NA,NA,NA,NA,1,1,1,NA,1,1,1,NA
72 +71,Sino-Tibetan,1,NA,NA,NA,-0.811933291,NA,0.025559785,0.025559785,48,2,1,0,NA,NA,NA,NA,1,NA,1,NA,1,NA,NA,1
73 +72,Austroasiatic,2,2,3,-0.545126265,0.27064443,0.888385296,1.227529072,1.227529072,19,0,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,1,NA
74 +73,Austroasiatic,NA,4,1,1.165442359,NA,-1.117646018,0.391418033,0.391418033,47,2,0,NA,NA,NA,NA,NA,1,NA,1,1,NA,NA,NA,NA
75 +74,Austronesian,NA,NA,NA,NA,NA,NA,1.085165353,1.085165353,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
76 +75,Austroasiatic,NA,NA,NA,NA,NA,NA,0.581909222,0.581909222,46,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
77 +76,Tai-Kadai,1,3,1,0.310158047,-0.811933291,-1.117646018,0.041075496,0.041075496,50,2,1,1,0,0,0,0,1,NA,1,NA,NA,NA,NA,NA
78 +77,Austroasiatic,NA,NA,NA,NA,NA,NA,1.299302125,1.299302125,12,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
79 +78,Austroasiatic,NA,NA,NA,NA,NA,NA,-1.164108422,-1.164108422,27,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
80 +79,Great Andamanese,NA,NA,NA,NA,NA,NA, , ,14,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
81 +80,Indo-European,NA,NA,NA,NA,NA,NA,-0.261352564,-0.261352564,16,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
82 +81,Austronesian,NA,NA,NA,NA,NA,NA,-0.618424945,-0.618424945,27,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
83 +82,Austronesian,NA,NA,NA,NA,NA,NA,0.961160376,0.961160376,45,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
84 +83,Austronesian,NA,3,1,0.310158047,NA,-1.117646018,0.25272541,0.25272541,49,2,1,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
85 +84,Austronesian,1,2,NA,-0.545126265,-0.811933291,NA,-0.430263798,-0.430263798,48,2,0,0,NA,NA,NA,NA,1,1,1,1,NA,NA,NA,0
86 +85,Austronesian,NA,2,NA,-0.545126265,NA,NA,0.931190849,0.931190849,23,0,1,1,NA,NA,NA,NA,1,1,NA,1,1,NA,1,NA
87 +86,Austronesian,1,1,NA,-1.400410576,-0.811933291,NA, , ,15,0,0,0,0,0,0,0,0,0,0,0,1,NA,NA,NA
88 +87,Austronesian,NA,NA,NA,NA,NA,NA,0.29205194,0.29205194,28,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
89 +88,North Halmahera,NA,NA,NA,NA,NA,NA,-0.316134565,-0.316134565,31,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
90 +89,Timor-Alor-Pantar,NA,NA,NA,NA,NA,NA,-1.486727605,-1.486727605,30,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
91 +90,NA,1,1,1,-1.400410576,-0.811933291,-1.117646018, , ,12,0,0,1,0,0,0,0,1,1,1,1,NA,NA,NA,NA
92 +91,Pama-Nyungan,NA,2,2,-0.545126265,NA,-0.114630361,-1.38039561,-1.38039561,13,0,NA,NA,NA,NA,NA,NA,1,1,1,NA,NA,NA,NA,NA
93 +92,Nuclear Trans New Guinea,2,NA,1,NA,0.27064443,-1.117646018,0.695596149,0.695596149,20,0,1,0,NA,NA,NA,NA,1,NA,NA,1,1,NA,NA,NA
94 +93,Kolopom,NA,4,3,1.165442359,NA,0.888385296,-0.76201153,-0.76201153,22,0,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
95 +94,Nuclear Trans New Guinea,1,NA,1,NA,-0.811933291,-1.117646018,0.342954258,0.342954258,29,1,0,NA,0,0,0,0,1,0,0,0,1,1,1,0
96 +95,Sepik,NA,NA,NA,NA,NA,NA,0.711200922,0.711200922,28,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
97 +96,Austronesian,1,1,1,-1.400410576,-0.811933291,-1.117646018,-1.266562874,-1.266562874,26,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,0,1,0
98 +97,Austronesian,NA,NA,NA,NA,NA,NA, , ,26,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
99 +98,Austronesian,2,4,4,1.165442359,0.27064443,1.891400953,-1.737923154,-1.737923154,26,0,1,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,1,0
100 +99,South Bougainville,1,NA,3,NA,-0.811933291,0.888385296,-0.483457234,-0.483457234,27,1,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
101 +100,Austronesian,2,4,3,1.165442359,0.27064443,0.888385296, , ,28,1,0,1,NA,NA,NA,NA,1,1,1,1,1,1,1,1
102 +101,Austronesian,NA,NA,NA,NA,NA,NA, , ,23,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
103 +102,Austronesian,1,1,NA,-1.400410576,-0.811933291,NA, , ,32,1,0,NA,NA,NA,NA,NA,1,1,1,1,1,0,0,0
104 +103,Austronesian,NA,NA,NA,NA,NA,NA, , ,26,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
105 +104,Austronesian,3,4,3,1.165442359,1.353222151,0.888385296, , ,24,0,1,1,0,0,0,0,1,NA,NA,1,1,NA,NA,NA
106 +105,Austronesian,NA,NA,NA,NA,NA,NA, , ,27,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
107 +106,Austronesian,1,4,2,1.165442359,-0.811933291,-0.114630361, , ,28,1,0,NA,NA,NA,NA,NA,1,1,1,1,0,0,0,0
108 +107,Austronesian,NA,NA,NA,NA,NA,NA, , ,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
109 +108,Austronesian,2,3,3,0.310158047,0.27064443,0.888385296, , ,29,1,1,0,NA,NA,NA,NA,1,NA,1,1,1,1,NA,NA
110 +109,Austronesian,NA,2,NA,-0.545126265,NA,NA, , ,28,1,0,1,NA,NA,NA,NA,1,NA,NA,NA,1,1,1,NA
111 +110,Austronesian,NA,4,NA,1.165442359,NA,NA, , ,32,1,0,NA,NA,0,0,0,1,NA,1,0,NA,NA,NA,NA
112 +111,Austronesian,NA,NA,NA,NA,NA,NA, , ,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
113 +112,Austronesian,1,3,1,0.310158047,-0.811933291,-1.117646018,-0.047927208,-0.047927208,31,1,1,1,NA,NA,NA,NA,1,1,NA,1,NA,NA,NA,NA
114 +113,Austronesian,NA,NA,NA,NA,NA,NA,-0.092607264,-0.092607264,27,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
115 +114,Sino-Tibetan,NA,NA,NA,NA,NA,NA,0.123275928,0.123275928,50,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
116 +115,Tungusic,NA,NA,NA,NA,NA,NA,0.066682378,0.066682378,36,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
117 +116,Koreanic,3,2,2,-0.545126265,1.353222151,-0.114630361,-0.010504153,-0.010504153,48,2,0,NA,NA,NA,NA,NA,1,1,1,1,0,NA,NA,0
118 +117,Japonic,NA,2,1,-0.545126265,NA,-1.117646018,-0.028266043,-0.028266043,50,2,0,1,0,0,0,0,0,0,0,0,1,0,1,0
119 +118,Ainu,2,1,2,-1.400410576,0.27064443,-0.114630361,-0.103598293,-0.103598293,17,0,1,1,NA,NA,NA,NA,1,1,1,0,1,NA,NA,NA
120 +119,NA,2,3,4,0.310158047,0.27064443,1.891400953,0.032461396,0.032461396,19,0,1,1,0,0,0,0,1,1,NA,1,NA,NA,NA,NA
121 +120,Yukaghir,NA,NA,NA,NA,NA,NA,-0.960436533,-0.960436533,17,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
122 +121,Chukotko-Kamchatkan,1,3,2,0.310158047,-0.811933291,-0.114630361, , ,18,0,1,1,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA
123 +122,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,-0.675887327,-0.675887327,19,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
124 +123,Eskimo-Aleut,NA,NA,NA,NA,NA,NA,-0.523523495,-0.523523495,21,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
125 +124,Eskimo-Aleut,2,4,4,1.165442359,0.27064443,1.891400953,-1.33027634,-1.33027634,16,0,NA,1,NA,NA,NA,NA,1,1,NA,1,1,NA,NA,1
126 +125,Algic,NA,NA,NA,NA,NA,NA,0.049442145,0.049442145,15,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
127 +126,Algic,NA,NA,NA,NA,NA,NA,0.263084761,0.263084761,17,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
128 +127,Algic,NA,NA,NA,NA,NA,NA,-0.020865687,-0.020865687,20,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
129 +128,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,-0.507859059,-0.507859059,18,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
130 +129,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,-0.371900546,-0.371900546,14,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
131 +130,Athabaskan-Eyak-Tlingit,NA,1,1,-1.400410576,NA,-1.117646018,-0.284366587,-0.284366587,16,0,1,0,NA,NA,NA,NA,1,NA,NA,NA,1,NA,NA,NA
132 +131,Haida,1,1,NA,-1.400410576,-0.811933291,NA,-0.943756356,-0.943756356,23,0,NA,NA,1,NA,NA,NA,1,NA,NA,0,1,NA,NA,NA
133 +132,Salishan,1,1,1,-1.400410576,-0.811933291,-1.117646018,0.162389228,0.162389228,22,0,1,1,0,0,0,0,1,1,1,1,NA,NA,NA,NA
134 +133,Salishan,NA,NA,NA,NA,NA,NA,0.311683442,0.311683442,22,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
135 +134,Algic,NA,NA,NA,NA,NA,NA, , ,18,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
136 +135,Pomoan,NA,NA,NA,NA,NA,NA,-0.281204642,-0.281204642,22,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
137 +136,Yokutsan,NA,NA,NA,NA,NA,NA,-0.849968863,-0.849968863,21,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
138 +137,Uto-Aztecan,NA,NA,NA,NA,NA,NA,-0.122671566,-0.122671566,14,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
139 +138,NA,2,2,2,-0.545126265,0.27064443,-0.114630361,0.329048341,0.329048341,14,0,NA,NA,NA,NA,NA,NA,1,1,1,NA,1,NA,NA,NA
140 +139,NA,NA,NA,NA,NA,NA,NA,0.277500728,0.277500728,18,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
141 +140,Algic,NA,NA,NA,NA,NA,NA,-0.133226989,-0.133226989,18,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
142 +141,Siouan,2,2,2,-0.545126265,0.27064443,-0.114630361,-0.2257957,-0.2257957,24,0,1,1,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA
143 +142,Caddoan,4,4,2,1.165442359,2.435799873,-0.114630361,-0.199172779,-0.199172779,25,0,NA,1,1,0,1,0,1,0,1,0,NA,NA,NA,NA
144 +143,Siouan,NA,NA,NA,NA,NA,NA,-0.112245133,-0.112245133,25,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
145 +144,Iroquoian,NA,4,4,1.165442359,NA,1.891400953,0.421468875,0.421468875,28,1,1,1,0,0,0,0,1,1,1,1,NA,NA,NA,NA
146 +145,Muskogean,NA,NA,NA,NA,NA,NA,0.239435725,0.239435725,29,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
147 +146,NA,NA,NA,NA,NA,NA,NA,0.076957044,0.076957044,32,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
148 +147,Uto-Aztecan,NA,NA,NA,NA,NA,NA,-0.348009156,-0.348009156,17,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
149 +148,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,-0.097100861,-0.097100861,15,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
150 +149,NA,NA,NA,NA,NA,NA,NA,-0.311511294,-0.311511294,35,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
151 +150,Cochimi-Yuman,NA,4,NA,1.165442359,NA,NA,-0.472718402,-0.472718402,20,0,NA,0,NA,NA,NA,NA,1,NA,1,NA,1,NA,NA,NA
152 +151,Uto-Aztecan,2,4,3,1.165442359,0.27064443,0.888385296,-1.177386251,-1.177386251,27,1,1,1,NA,NA,NA,NA,1,NA,1,0,NA,NA,NA,NA
153 +152,Uto-Aztecan,NA,NA,NA,NA,NA,NA,0.256988493,0.256988493,28,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
154 +153,Uto-Aztecan,NA,NA,NA,NA,NA,NA,0.62076598,0.62076598,44,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
155 +154,Mixe-Zoque,1,NA,1,NA,-0.811933291,-1.117646018,0.925953627,0.925953627,29,1,0,NA,0,0,0,0,NA,NA,NA,NA,1,NA,NA,1
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188 +
DT-GodsAndResourceStress_Long.csv
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1 +xwiki:XWiki.Admin
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315 +79,Great Andamanese,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,14,2,NA
316 +79,Great Andamanese,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,14,3,NA
317 +79,Great Andamanese,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,14,4,NA
318 +80,Indo-European,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,16,1,NA
319 +80,Indo-European,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,16,2,NA
320 +80,Indo-European,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,16,3,NA
321 +80,Indo-European,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,16,4,-0.261352564
322 +81,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,1,NA
323 +81,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,2,NA
324 +81,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,3,NA
325 +81,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,4,-0.618424945
326 +82,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,45,1,NA
327 +82,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,45,2,NA
328 +82,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,45,3,NA
329 +82,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,45,4,0.961160376
330 +83,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,49,1,-1.117646018
331 +83,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,49,2,0.310158047
332 +83,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,49,3,NA
333 +83,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,49,4,0.252725410
334 +84,Austronesian,NA,NA,NA,NA,1,1,1,1,NA,NA,NA,0,48,1,NA
335 +84,Austronesian,NA,NA,NA,NA,1,1,1,1,NA,NA,NA,0,48,2,-0.545126265
336 +84,Austronesian,NA,NA,NA,NA,1,1,1,1,NA,NA,NA,0,48,3,-0.811933291
337 +84,Austronesian,NA,NA,NA,NA,1,1,1,1,NA,NA,NA,0,48,4,-0.430263798
338 +85,Austronesian,NA,NA,NA,NA,1,1,NA,1,1,NA,1,NA,23,1,NA
339 +85,Austronesian,NA,NA,NA,NA,1,1,NA,1,1,NA,1,NA,23,2,-0.545126265
340 +85,Austronesian,NA,NA,NA,NA,1,1,NA,1,1,NA,1,NA,23,3,NA
341 +85,Austronesian,NA,NA,NA,NA,1,1,NA,1,1,NA,1,NA,23,4,0.931190849
342 +86,Austronesian,0,0,0,0,0,0,0,0,1,NA,NA,NA,15,1,NA
343 +86,Austronesian,0,0,0,0,0,0,0,0,1,NA,NA,NA,15,2,-1.400410576
344 +86,Austronesian,0,0,0,0,0,0,0,0,1,NA,NA,NA,15,3,-0.811933291
345 +86,Austronesian,0,0,0,0,0,0,0,0,1,NA,NA,NA,15,4,NA
346 +87,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,1,NA
347 +87,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,2,NA
348 +87,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,3,NA
349 +87,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,4,0.292051940
350 +88,North Halmahera,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,31,1,NA
351 +88,North Halmahera,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,31,2,NA
352 +88,North Halmahera,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,31,3,NA
353 +88,North Halmahera,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,31,4,-0.316134565
354 +89,Timor-Alor-Pantar,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,30,1,NA
355 +89,Timor-Alor-Pantar,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,30,2,NA
356 +89,Timor-Alor-Pantar,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,30,3,NA
357 +89,Timor-Alor-Pantar,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,30,4,-1.486727605
358 +90,NA,0,0,0,0,1,1,1,1,NA,NA,NA,NA,12,1,-1.117646018
359 +90,NA,0,0,0,0,1,1,1,1,NA,NA,NA,NA,12,2,-1.400410576
360 +90,NA,0,0,0,0,1,1,1,1,NA,NA,NA,NA,12,3,-0.811933291
361 +90,NA,0,0,0,0,1,1,1,1,NA,NA,NA,NA,12,4,NA
362 +91,Pama-Nyungan,NA,NA,NA,NA,1,1,1,NA,NA,NA,NA,NA,13,1,-0.114630361
363 +91,Pama-Nyungan,NA,NA,NA,NA,1,1,1,NA,NA,NA,NA,NA,13,2,-0.545126265
364 +91,Pama-Nyungan,NA,NA,NA,NA,1,1,1,NA,NA,NA,NA,NA,13,3,NA
365 +91,Pama-Nyungan,NA,NA,NA,NA,1,1,1,NA,NA,NA,NA,NA,13,4,-1.380395610
366 +92,Nuclear Trans New Guinea,NA,NA,NA,NA,1,NA,NA,1,1,NA,NA,NA,20,1,-1.117646018
367 +92,Nuclear Trans New Guinea,NA,NA,NA,NA,1,NA,NA,1,1,NA,NA,NA,20,2,NA
368 +92,Nuclear Trans New Guinea,NA,NA,NA,NA,1,NA,NA,1,1,NA,NA,NA,20,3,0.270644430
369 +92,Nuclear Trans New Guinea,NA,NA,NA,NA,1,NA,NA,1,1,NA,NA,NA,20,4,0.695596149
370 +93,Kolopom,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,22,1,0.888385296
371 +93,Kolopom,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,22,2,1.165442359
372 +93,Kolopom,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,22,3,NA
373 +93,Kolopom,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,22,4,-0.762011530
374 +94,Nuclear Trans New Guinea,0,0,0,0,1,0,0,0,1,1,1,0,29,1,-1.117646018
375 +94,Nuclear Trans New Guinea,0,0,0,0,1,0,0,0,1,1,1,0,29,2,NA
376 +94,Nuclear Trans New Guinea,0,0,0,0,1,0,0,0,1,1,1,0,29,3,-0.811933291
377 +94,Nuclear Trans New Guinea,0,0,0,0,1,0,0,0,1,1,1,0,29,4,0.342954258
378 +95,Sepik,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,1,NA
379 +95,Sepik,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,2,NA
380 +95,Sepik,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,3,NA
381 +95,Sepik,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,28,4,0.711200922
382 +96,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,0,1,0,26,1,-1.117646018
383 +96,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,0,1,0,26,2,-1.400410576
384 +96,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,0,1,0,26,3,-0.811933291
385 +96,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,0,1,0,26,4,-1.266562874
386 +97,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,1,NA
387 +97,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,2,NA
388 +97,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,3,NA
389 +97,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,4,NA
390 +98,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,1,0,26,1,1.891400953
391 +98,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,1,0,26,2,1.165442359
392 +98,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,1,0,26,3,0.270644430
393 +98,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,1,0,26,4,-1.737923154
394 +NA,South Bougainville,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,1,0.888385296
395 +NA,South Bougainville,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,2,NA
396 +NA,South Bougainville,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,3,-0.811933291
397 +NA,South Bougainville,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,4,-0.483457234
398 +100,Austronesian,NA,NA,NA,NA,1,1,1,1,1,1,1,1,28,1,0.888385296
399 +100,Austronesian,NA,NA,NA,NA,1,1,1,1,1,1,1,1,28,2,1.165442359
400 +100,Austronesian,NA,NA,NA,NA,1,1,1,1,1,1,1,1,28,3,0.270644430
401 +100,Austronesian,NA,NA,NA,NA,1,1,1,1,1,1,1,1,28,4,NA
402 +101,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,23,1,NA
403 +101,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,23,2,NA
404 +101,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,23,3,NA
405 +101,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,23,4,NA
406 +102,Austronesian,NA,NA,NA,NA,1,1,1,1,1,0,0,0,32,1,NA
407 +102,Austronesian,NA,NA,NA,NA,1,1,1,1,1,0,0,0,32,2,-1.400410576
408 +102,Austronesian,NA,NA,NA,NA,1,1,1,1,1,0,0,0,32,3,-0.811933291
409 +102,Austronesian,NA,NA,NA,NA,1,1,1,1,1,0,0,0,32,4,NA
410 +103,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,1,NA
411 +103,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,2,NA
412 +103,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,3,NA
413 +103,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,26,4,NA
414 +104,Austronesian,0,0,0,0,1,NA,NA,1,1,NA,NA,NA,24,1,0.888385296
415 +104,Austronesian,0,0,0,0,1,NA,NA,1,1,NA,NA,NA,24,2,1.165442359
416 +104,Austronesian,0,0,0,0,1,NA,NA,1,1,NA,NA,NA,24,3,1.353222151
417 +104,Austronesian,0,0,0,0,1,NA,NA,1,1,NA,NA,NA,24,4,NA
418 +105,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,1,NA
419 +105,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,2,NA
420 +105,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,3,NA
421 +105,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,4,NA
422 +106,Austronesian,NA,NA,NA,NA,1,1,1,1,0,0,0,0,28,1,-0.114630361
423 +106,Austronesian,NA,NA,NA,NA,1,1,1,1,0,0,0,0,28,2,1.165442359
424 +106,Austronesian,NA,NA,NA,NA,1,1,1,1,0,0,0,0,28,3,-0.811933291
425 +106,Austronesian,NA,NA,NA,NA,1,1,1,1,0,0,0,0,28,4,NA
426 +107,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,1,NA
427 +107,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,2,NA
428 +107,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,3,NA
429 +107,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,4,NA
430 +108,Austronesian,NA,NA,NA,NA,1,NA,1,1,1,1,NA,NA,29,1,0.888385296
431 +108,Austronesian,NA,NA,NA,NA,1,NA,1,1,1,1,NA,NA,29,2,0.310158047
432 +108,Austronesian,NA,NA,NA,NA,1,NA,1,1,1,1,NA,NA,29,3,0.270644430
433 +108,Austronesian,NA,NA,NA,NA,1,NA,1,1,1,1,NA,NA,29,4,NA
434 +109,Austronesian,NA,NA,NA,NA,1,NA,NA,NA,1,1,1,NA,28,1,NA
435 +109,Austronesian,NA,NA,NA,NA,1,NA,NA,NA,1,1,1,NA,28,2,-0.545126265
436 +109,Austronesian,NA,NA,NA,NA,1,NA,NA,NA,1,1,1,NA,28,3,NA
437 +109,Austronesian,NA,NA,NA,NA,1,NA,NA,NA,1,1,1,NA,28,4,NA
438 +110,Austronesian,NA,0,0,0,1,NA,1,0,NA,NA,NA,NA,32,1,NA
439 +110,Austronesian,NA,0,0,0,1,NA,1,0,NA,NA,NA,NA,32,2,1.165442359
440 +110,Austronesian,NA,0,0,0,1,NA,1,0,NA,NA,NA,NA,32,3,NA
441 +110,Austronesian,NA,0,0,0,1,NA,1,0,NA,NA,NA,NA,32,4,NA
442 +111,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,1,NA
443 +111,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,2,NA
444 +111,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,3,NA
445 +111,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,29,4,NA
446 +112,Austronesian,NA,NA,NA,NA,1,1,NA,1,NA,NA,NA,NA,31,1,-1.117646018
447 +112,Austronesian,NA,NA,NA,NA,1,1,NA,1,NA,NA,NA,NA,31,2,0.310158047
448 +112,Austronesian,NA,NA,NA,NA,1,1,NA,1,NA,NA,NA,NA,31,3,-0.811933291
449 +112,Austronesian,NA,NA,NA,NA,1,1,NA,1,NA,NA,NA,NA,31,4,-0.047927208
450 +113,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,1,NA
451 +113,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,2,NA
452 +113,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,3,NA
453 +113,Austronesian,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,27,4,-0.092607264
454 +114,Sino-Tibetan,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,50,1,NA
455 +114,Sino-Tibetan,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,50,2,NA
456 +114,Sino-Tibetan,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,50,3,NA
457 +114,Sino-Tibetan,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,50,4,0.123275928
458 +115,Tungusic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,36,1,NA
459 +115,Tungusic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,36,2,NA
460 +115,Tungusic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,36,3,NA
461 +115,Tungusic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,36,4,0.066682378
462 +116,Koreanic,NA,NA,NA,NA,1,1,1,1,0,NA,NA,0,48,1,-0.114630361
463 +116,Koreanic,NA,NA,NA,NA,1,1,1,1,0,NA,NA,0,48,2,-0.545126265
464 +116,Koreanic,NA,NA,NA,NA,1,1,1,1,0,NA,NA,0,48,3,1.353222151
465 +116,Koreanic,NA,NA,NA,NA,1,1,1,1,0,NA,NA,0,48,4,-0.010504153
466 +117,Japonic,0,0,0,0,0,0,0,0,1,0,1,0,50,1,-1.117646018
467 +117,Japonic,0,0,0,0,0,0,0,0,1,0,1,0,50,2,-0.545126265
468 +117,Japonic,0,0,0,0,0,0,0,0,1,0,1,0,50,3,NA
469 +117,Japonic,0,0,0,0,0,0,0,0,1,0,1,0,50,4,-0.028266043
470 +118,Ainu,NA,NA,NA,NA,1,1,1,0,1,NA,NA,NA,17,1,-0.114630361
471 +118,Ainu,NA,NA,NA,NA,1,1,1,0,1,NA,NA,NA,17,2,-1.400410576
472 +118,Ainu,NA,NA,NA,NA,1,1,1,0,1,NA,NA,NA,17,3,0.270644430
473 +118,Ainu,NA,NA,NA,NA,1,1,1,0,1,NA,NA,NA,17,4,-0.103598293
474 +119,NA,0,0,0,0,1,1,NA,1,NA,NA,NA,NA,19,1,1.891400953
475 +119,NA,0,0,0,0,1,1,NA,1,NA,NA,NA,NA,19,2,0.310158047
476 +119,NA,0,0,0,0,1,1,NA,1,NA,NA,NA,NA,19,3,0.270644430
477 +119,NA,0,0,0,0,1,1,NA,1,NA,NA,NA,NA,19,4,0.032461396
478 +120,Yukaghir,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,1,NA
479 +120,Yukaghir,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,2,NA
480 +120,Yukaghir,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,3,NA
481 +120,Yukaghir,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,4,-0.960436533
482 +121,Chukotko-Kamchatkan,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,18,1,-0.114630361
483 +121,Chukotko-Kamchatkan,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,18,2,0.310158047
484 +121,Chukotko-Kamchatkan,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,18,3,-0.811933291
485 +121,Chukotko-Kamchatkan,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,18,4,NA
486 +122,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,19,1,NA
487 +122,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,19,2,NA
488 +122,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,19,3,NA
489 +122,Athabaskan-Eyak-Tlingit,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,19,4,-0.675887327
490 +123,Eskimo-Aleut,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,21,1,NA
491 +123,Eskimo-Aleut,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,21,2,NA
492 +123,Eskimo-Aleut,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,21,3,NA
493 +123,Eskimo-Aleut,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,21,4,-0.523523495
494 +124,Eskimo-Aleut,NA,NA,NA,NA,1,1,NA,1,1,NA,NA,1,16,1,1.891400953
495 +124,Eskimo-Aleut,NA,NA,NA,NA,1,1,NA,1,1,NA,NA,1,16,2,1.165442359
496 +124,Eskimo-Aleut,NA,NA,NA,NA,1,1,NA,1,1,NA,NA,1,16,3,0.270644430
497 +124,Eskimo-Aleut,NA,NA,NA,NA,1,1,NA,1,1,NA,NA,1,16,4,-1.330276340
498 +125,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,15,1,NA
499 +125,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,15,2,NA
500 +125,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,15,3,NA
501 +125,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,15,4,0.049442145
502 +126,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,1,NA
503 +126,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,2,NA
504 +126,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,3,NA
505 +126,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,17,4,0.263084761
506 +127,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,20,1,NA
507 +127,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,20,2,NA
508 +127,Algic,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,20,3,NA
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DT-MoralHighGods_EP(2).csv
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188 +
DT-MoralHighGods_Long_EP(1).csv
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1 +xwiki:XWiki.Admin
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1 +24.6 KB
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... ... @@ -1,0 +1,746 @@
1 +SCCS_ID,language_family,HG_Pres_MoralNoYes,MHG_PresAbs,Social_Complexity,ResourceStress,Stress
2 +1,Khoe-Kwadi,NA,0,18,1,NA
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175 +44,Afro-Asiatic,1,1,46,2,-0.545126265
176 +44,Afro-Asiatic,1,1,46,3,-0.811933291
177 +44,Afro-Asiatic,1,1,46,4,-1.536784803
178 +45,Afro-Asiatic,NA,0,49,1,NA
179 +45,Afro-Asiatic,NA,0,49,2,-0.545126265
180 +45,Afro-Asiatic,NA,0,49,3,NA
181 +45,Afro-Asiatic,NA,0,49,4,-2.593788647
182 +46,Afro-Asiatic,1,1,23,1,0.888385296
183 +46,Afro-Asiatic,1,1,23,2,1.165442359
184 +46,Afro-Asiatic,1,1,23,3,NA
185 +46,Afro-Asiatic,1,1,23,4,-2.214468868
186 +47,Turkic,1,1,48,1,0.888385296
187 +47,Turkic,1,1,48,2,1.165442359
188 +47,Turkic,1,1,48,3,1.353222151
189 +47,Turkic,1,1,48,4,-0.411152163
190 +48,Indo-European,1,1,36,1,NA
191 +48,Indo-European,1,1,36,2,NA
192 +48,Indo-European,1,1,36,3,NA
193 +48,Indo-European,1,1,36,4,0.222075523
194 +49,Indo-European,NA,0,49,1,NA
195 +49,Indo-European,NA,0,49,2,NA
196 +49,Indo-European,NA,0,49,3,NA
197 +49,Indo-European,NA,0,49,4,-0.187607934
198 +50,Basque,1,1,47,1,NA
199 +50,Basque,1,1,47,2,NA
200 +50,Basque,1,1,47,3,NA
201 +50,Basque,1,1,47,4,0.014805390
202 +51,Indo-European,1,1,47,1,NA
203 +51,Indo-European,1,1,47,2,-1.400410576
204 +51,Indo-European,1,1,47,3,0.270644430
205 +51,Indo-European,1,1,47,4,-0.030757432
206 +52,Uralic,1,1,18,1,-1.117646018
207 +52,Uralic,1,1,18,2,-1.400410576
208 +52,Uralic,1,1,18,3,NA
209 +52,Uralic,1,1,18,4,-0.766077663
210 +53,Uralic,0,0,18,1,0.888385296
211 +53,Uralic,0,0,18,2,1.165442359
212 +53,Uralic,0,0,18,3,0.270644430
213 +53,Uralic,0,0,18,4,-0.976789891
214 +54,Indo-European,1,1,48,1,NA
215 +54,Indo-European,1,1,48,2,1.165442359
216 +54,Indo-European,1,1,48,3,-0.811933291
217 +54,Indo-European,1,1,48,4,0.241671524
218 +55,Abkhaz-Adyge,1,1,36,1,NA
219 +55,Abkhaz-Adyge,1,1,36,2,0.310158047
220 +55,Abkhaz-Adyge,1,1,36,3,-0.811933291
221 +55,Abkhaz-Adyge,1,1,36,4,0.085190164
222 +56,Indo-European,1,1,43,1,NA
223 +56,Indo-European,1,1,43,2,NA
224 +56,Indo-European,1,1,43,3,NA
225 +56,Indo-European,1,1,43,4,-0.153334246
226 +57,Indo-European,1,1,43,1,-1.117646018
227 +57,Indo-European,1,1,43,2,-1.400410576
228 +57,Indo-European,1,1,43,3,NA
229 +57,Indo-European,1,1,43,4,-1.252771783
230 +58,Indo-European,1,1,25,1,-1.117646018
231 +58,Indo-European,1,1,25,2,-0.545126265
232 +58,Indo-European,1,1,25,3,-0.811933291
233 +58,Indo-European,1,1,25,4,-1.957393684
234 +59,Indo-European,1,1,45,1,0.888385296
235 +59,Indo-European,1,1,45,2,0.310158047
236 +59,Indo-European,1,1,45,3,0.270644430
237 +59,Indo-European,1,1,45,4,-1.213571865
238 +60,Dravidian,0,0,27,1,-1.117646018
239 +60,Dravidian,0,0,27,2,-1.400410576
240 +60,Dravidian,0,0,27,3,-0.811933291
241 +60,Dravidian,0,0,27,4,-0.213627236
242 +61,Dravidian,NA,0,19,1,NA
243 +61,Dravidian,NA,0,19,2,NA
244 +61,Dravidian,NA,0,19,3,NA
245 +61,Dravidian,NA,0,19,4,0.539954324
246 +62,Austroasiatic,0,0,31,1,NA
247 +62,Austroasiatic,0,0,31,2,-0.545126265
248 +62,Austroasiatic,0,0,31,3,1.353222151
249 +62,Austroasiatic,0,0,31,4,-0.441295394
250 +63,Indo-European,0,0,50,1,NA
251 +63,Indo-European,0,0,50,2,-0.545126265
252 +63,Indo-European,0,0,50,3,NA
253 +63,Indo-European,0,0,50,4,-0.804549287
254 +64,NA,1,1,33,1,NA
255 +64,NA,1,1,33,2,-1.400410576
256 +64,NA,1,1,33,3,0.270644430
257 +64,NA,1,1,33,4,-0.639041621
258 +65,Turkic,1,1,30,1,0.888385296
259 +65,Turkic,1,1,30,2,0.310158047
260 +65,Turkic,1,1,30,3,-0.270644430
261 +65,Turkic,1,1,30,4,-0.296912891
262 +66,Mongolic,NA,NA,32,1,-0.114630361
263 +66,Mongolic,NA,NA,32,2,1.165442359
264 +66,Mongolic,NA,NA,32,3,NA
265 +66,Mongolic,NA,NA,32,4,-0.205654550
266 +67,Sino-Tibetan,NA,0,35,1,NA
267 +67,Sino-Tibetan,NA,0,35,2,NA
268 +67,Sino-Tibetan,NA,0,35,3,NA
269 +67,Sino-Tibetan,NA,0,35,4,0.996315979
270 +68,Sino-Tibetan,0,0,32,1,-1.117646018
271 +68,Sino-Tibetan,0,0,32,2,-1.400410576
272 +68,Sino-Tibetan,0,0,32,3,-0.811933291
273 +68,Sino-Tibetan,0,0,32,4,1.213261184
274 +69,Sino-Tibetan,0,0,31,1,NA
275 +69,Sino-Tibetan,0,0,31,2,NA
276 +69,Sino-Tibetan,0,0,31,3,NA
277 +69,Sino-Tibetan,0,0,31,4,0.456514054
278 +70,Sino-Tibetan,1,1,31,1,0.888385296
279 +70,Sino-Tibetan,1,1,31,2,0.310158047
280 +70,Sino-Tibetan,1,1,31,3,NA
281 +70,Sino-Tibetan,1,1,31,4,0.497973312
282 +71,Sino-Tibetan,NA,0,48,1,NA
283 +71,Sino-Tibetan,NA,0,48,2,NA
284 +71,Sino-Tibetan,NA,0,48,3,-0.811933291
285 +71,Sino-Tibetan,NA,0,48,4,0.025559785
286 +72,Austroasiatic,NA,0,19,1,0.888385296
287 +72,Austroasiatic,NA,0,19,2,-0.545126265
288 +72,Austroasiatic,NA,0,19,3,0.270644430
289 +72,Austroasiatic,NA,0,19,4,1.227529072
290 +73,Austroasiatic,NA,0,47,1,-1.117646018
291 +73,Austroasiatic,NA,0,47,2,1.165442359
292 +73,Austroasiatic,NA,0,47,3,NA
293 +73,Austroasiatic,NA,0,47,4,0.391418033
294 +74,Austronesian,NA,0,29,1,NA
295 +74,Austronesian,NA,0,29,2,NA
296 +74,Austronesian,NA,0,29,3,NA
297 +74,Austronesian,NA,0,29,4,1.085165353
298 +75,Austroasiatic,0,0,46,1,NA
299 +75,Austroasiatic,0,0,46,2,NA
300 +75,Austroasiatic,0,0,46,3,NA
301 +75,Austroasiatic,0,0,46,4,0.581909222
302 +76,Tai-Kadai,0,0,50,1,-1.117646018
303 +76,Tai-Kadai,0,0,50,2,0.310158047
304 +76,Tai-Kadai,0,0,50,3,-0.811933291
305 +76,Tai-Kadai,0,0,50,4,0.041075496
306 +77,Austroasiatic,0,0,12,1,NA
307 +77,Austroasiatic,0,0,12,2,NA
308 +77,Austroasiatic,0,0,12,3,NA
309 +77,Austroasiatic,0,0,12,4,1.299302125
310 +78,Austroasiatic,NA,NA,27,1,NA
311 +78,Austroasiatic,NA,NA,27,2,NA
312 +78,Austroasiatic,NA,NA,27,3,NA
313 +78,Austroasiatic,NA,NA,27,4,-1.164108422
314 +79,Great Andamanese,NA,0,14,1,NA
315 +79,Great Andamanese,NA,0,14,2,NA
316 +79,Great Andamanese,NA,0,14,3,NA
317 +79,Great Andamanese,NA,0,14,4,NA
318 +80,Indo-European,NA,0,16,1,NA
319 +80,Indo-European,NA,0,16,2,NA
320 +80,Indo-European,NA,0,16,3,NA
321 +80,Indo-European,NA,0,16,4,-0.261352564
322 +81,Austronesian,0,0,27,1,NA
323 +81,Austronesian,0,0,27,2,NA
324 +81,Austronesian,0,0,27,3,NA
325 +81,Austronesian,0,0,27,4,-0.618424945
326 +82,Austronesian,1,1,45,1,NA
327 +82,Austronesian,1,1,45,2,NA
328 +82,Austronesian,1,1,45,3,NA
329 +82,Austronesian,1,1,45,4,0.961160376
330 +83,Austronesian,1,1,49,1,-1.117646018
331 +83,Austronesian,1,1,49,2,0.310158047
332 +83,Austronesian,1,1,49,3,NA
333 +83,Austronesian,1,1,49,4,0.252725410
334 +84,Austronesian,NA,0,48,1,NA
335 +84,Austronesian,NA,0,48,2,-0.545126265
336 +84,Austronesian,NA,0,48,3,-0.811933291
337 +84,Austronesian,NA,0,48,4,-0.430263798
338 +85,Austronesian,NA,0,23,1,NA
339 +85,Austronesian,NA,0,23,2,-0.545126265
340 +85,Austronesian,NA,0,23,3,NA
341 +85,Austronesian,NA,0,23,4,0.931190849
342 +86,Austronesian,NA,NA,15,1,NA
343 +86,Austronesian,NA,NA,15,2,-1.400410576
344 +86,Austronesian,NA,NA,15,3,-0.811933291
345 +86,Austronesian,NA,NA,15,4,NA
346 +87,Austronesian,NA,NA,28,1,NA
347 +87,Austronesian,NA,NA,28,2,NA
348 +87,Austronesian,NA,NA,28,3,NA
349 +87,Austronesian,NA,NA,28,4,0.292051940
350 +88,North Halmahera,NA,NA,31,1,NA
351 +88,North Halmahera,NA,NA,31,2,NA
352 +88,North Halmahera,NA,NA,31,3,NA
353 +88,North Halmahera,NA,NA,31,4,-0.316134565
354 +89,Timor-Alor-Pantar,0,0,30,1,NA
355 +89,Timor-Alor-Pantar,0,0,30,2,NA
356 +89,Timor-Alor-Pantar,0,0,30,3,NA
357 +89,Timor-Alor-Pantar,0,0,30,4,-1.486727605
358 +90,NA,0,0,12,1,-1.117646018
359 +90,NA,0,0,12,2,-1.400410576
360 +90,NA,0,0,12,3,-0.811933291
361 +90,NA,0,0,12,4,NA
362 +91,Pama-Nyungan,NA,0,13,1,-0.114630361
363 +91,Pama-Nyungan,NA,0,13,2,-0.545126265
364 +91,Pama-Nyungan,NA,0,13,3,NA
365 +91,Pama-Nyungan,NA,0,13,4,-1.380395610
366 +92,Nuclear Trans New Guinea,NA,0,20,1,-1.117646018
367 +92,Nuclear Trans New Guinea,NA,0,20,2,NA
368 +92,Nuclear Trans New Guinea,NA,0,20,3,0.270644430
369 +92,Nuclear Trans New Guinea,NA,0,20,4,0.695596149
370 +93,Kolopom,NA,NA,22,1,0.888385296
371 +93,Kolopom,NA,NA,22,2,1.165442359
372 +93,Kolopom,NA,NA,22,3,NA
373 +93,Kolopom,NA,NA,22,4,-0.762011530
374 +94,Nuclear Trans New Guinea,0,0,29,1,-1.117646018
375 +94,Nuclear Trans New Guinea,0,0,29,2,NA
376 +94,Nuclear Trans New Guinea,0,0,29,3,-0.811933291
377 +94,Nuclear Trans New Guinea,0,0,29,4,0.342954258
378 +95,Sepik,NA,0,28,1,NA
379 +95,Sepik,NA,0,28,2,NA
380 +95,Sepik,NA,0,28,3,NA
381 +95,Sepik,NA,0,28,4,0.711200922
382 +96,Austronesian,NA,0,26,1,-1.117646018
383 +96,Austronesian,NA,0,26,2,-1.400410576
384 +96,Austronesian,NA,0,26,3,-0.811933291
385 +96,Austronesian,NA,0,26,4,-1.266562874
386 +97,Austronesian,NA,0,26,1,NA
387 +97,Austronesian,NA,0,26,2,NA
388 +97,Austronesian,NA,0,26,3,NA
389 +97,Austronesian,NA,0,26,4,NA
390 +98,Austronesian,NA,0,26,1,1.891400953
391 +98,Austronesian,NA,0,26,2,1.165442359
392 +98,Austronesian,NA,0,26,3,0.270644430
393 +98,Austronesian,NA,0,26,4,-1.737923154
394 +NA,South Bougainville,NA,0,27,1,0.888385296
395 +NA,South Bougainville,NA,0,27,2,NA
396 +NA,South Bougainville,NA,0,27,3,-0.811933291
397 +NA,South Bougainville,NA,0,27,4,-0.483457234
398 +100,Austronesian,NA,0,28,1,0.888385296
399 +100,Austronesian,NA,0,28,2,1.165442359
400 +100,Austronesian,NA,0,28,3,0.270644430
401 +100,Austronesian,NA,0,28,4,NA
402 +101,Austronesian,NA,0,23,1,NA
403 +101,Austronesian,NA,0,23,2,NA
404 +101,Austronesian,NA,0,23,3,NA
405 +101,Austronesian,NA,0,23,4,NA
406 +102,Austronesian,NA,0,32,1,NA
407 +102,Austronesian,NA,0,32,2,-1.400410576
408 +102,Austronesian,NA,0,32,3,-0.811933291
409 +102,Austronesian,NA,0,32,4,NA
410 +103,Austronesian,NA,NA,26,1,NA
411 +103,Austronesian,NA,NA,26,2,NA
412 +103,Austronesian,NA,NA,26,3,NA
413 +103,Austronesian,NA,NA,26,4,NA
414 +104,Austronesian,NA,0,24,1,0.888385296
415 +104,Austronesian,NA,0,24,2,1.165442359
416 +104,Austronesian,NA,0,24,3,1.353222151
417 +104,Austronesian,NA,0,24,4,NA
418 +105,Austronesian,NA,0,27,1,NA
419 +105,Austronesian,NA,0,27,2,NA
420 +105,Austronesian,NA,0,27,3,NA
421 +105,Austronesian,NA,0,27,4,NA
422 +106,Austronesian,NA,0,28,1,-0.114630361
423 +106,Austronesian,NA,0,28,2,1.165442359
424 +106,Austronesian,NA,0,28,3,-0.811933291
425 +106,Austronesian,NA,0,28,4,NA
426 +107,Austronesian,0,0,29,1,NA
427 +107,Austronesian,0,0,29,2,NA
428 +107,Austronesian,0,0,29,3,NA
429 +107,Austronesian,0,0,29,4,NA
430 +108,Austronesian,NA,0,29,1,0.888385296
431 +108,Austronesian,NA,0,29,2,0.310158047
432 +108,Austronesian,NA,0,29,3,0.270644430
433 +108,Austronesian,NA,0,29,4,NA
434 +109,Austronesian,NA,0,28,1,NA
435 +109,Austronesian,NA,0,28,2,-0.545126265
436 +109,Austronesian,NA,0,28,3,NA
437 +109,Austronesian,NA,0,28,4,NA
438 +110,Austronesian,NA,NA,32,1,NA
439 +110,Austronesian,NA,NA,32,2,1.165442359
440 +110,Austronesian,NA,NA,32,3,NA
441 +110,Austronesian,NA,NA,32,4,NA
442 +111,Austronesian,NA,0,29,1,NA
443 +111,Austronesian,NA,0,29,2,NA
444 +111,Austronesian,NA,0,29,3,NA
445 +111,Austronesian,NA,0,29,4,NA
446 +112,Austronesian,NA,0,31,1,-1.117646018
447 +112,Austronesian,NA,0,31,2,0.310158047
448 +112,Austronesian,NA,0,31,3,-0.811933291
449 +112,Austronesian,NA,0,31,4,-0.047927208
450 +113,Austronesian,NA,0,27,1,NA
451 +113,Austronesian,NA,0,27,2,NA
452 +113,Austronesian,NA,0,27,3,NA
453 +113,Austronesian,NA,0,27,4,-0.092607264
454 +114,Sino-Tibetan,NA,0,50,1,NA
455 +114,Sino-Tibetan,NA,0,50,2,NA
456 +114,Sino-Tibetan,NA,0,50,3,NA
457 +114,Sino-Tibetan,NA,0,50,4,0.123275928
458 +115,Tungusic,NA,NA,36,1,NA
459 +115,Tungusic,NA,NA,36,2,NA
460 +115,Tungusic,NA,NA,36,3,NA
461 +115,Tungusic,NA,NA,36,4,0.066682378
462 +116,Koreanic,NA,0,48,1,-0.114630361
463 +116,Koreanic,NA,0,48,2,-0.545126265
464 +116,Koreanic,NA,0,48,3,1.353222151
465 +116,Koreanic,NA,0,48,4,-0.010504153
466 +117,Japonic,0,0,50,1,-1.117646018
467 +117,Japonic,0,0,50,2,-0.545126265
468 +117,Japonic,0,0,50,3,NA
469 +117,Japonic,0,0,50,4,-0.028266043
470 +118,Ainu,NA,0,17,1,-0.114630361
471 +118,Ainu,NA,0,17,2,-1.400410576
472 +118,Ainu,NA,0,17,3,0.270644430
473 +118,Ainu,NA,0,17,4,-0.103598293
474 +119,NA,0,0,19,1,1.891400953
475 +119,NA,0,0,19,2,0.310158047
476 +119,NA,0,0,19,3,0.270644430
477 +119,NA,0,0,19,4,0.032461396
478 +120,Yukaghir,NA,NA,17,1,NA
479 +120,Yukaghir,NA,NA,17,2,NA
480 +120,Yukaghir,NA,NA,17,3,NA
481 +120,Yukaghir,NA,NA,17,4,-0.960436533
482 +121,Chukotko-Kamchatkan,0,0,18,1,-0.114630361
483 +121,Chukotko-Kamchatkan,0,0,18,2,0.310158047
484 +121,Chukotko-Kamchatkan,0,0,18,3,-0.811933291
485 +121,Chukotko-Kamchatkan,0,0,18,4,NA
486 +122,Athabaskan-Eyak-Tlingit,0,0,19,1,NA
487 +122,Athabaskan-Eyak-Tlingit,0,0,19,2,NA
488 +122,Athabaskan-Eyak-Tlingit,0,0,19,3,NA
489 +122,Athabaskan-Eyak-Tlingit,0,0,19,4,-0.675887327
490 +123,Eskimo-Aleut,0,0,21,1,NA
491 +123,Eskimo-Aleut,0,0,21,2,NA
492 +123,Eskimo-Aleut,0,0,21,3,NA
493 +123,Eskimo-Aleut,0,0,21,4,-0.523523495
494 +124,Eskimo-Aleut,NA,0,16,1,1.891400953
495 +124,Eskimo-Aleut,NA,0,16,2,1.165442359
496 +124,Eskimo-Aleut,NA,0,16,3,0.270644430
497 +124,Eskimo-Aleut,NA,0,16,4,-1.330276340
498 +125,Algic,NA,0,15,1,NA
499 +125,Algic,NA,0,15,2,NA
500 +125,Algic,NA,0,15,3,NA
501 +125,Algic,NA,0,15,4,0.049442145
502 +126,Algic,0,0,17,1,NA
503 +126,Algic,0,0,17,2,NA
504 +126,Algic,0,0,17,3,NA
505 +126,Algic,0,0,17,4,0.263084761
506 +127,Algic,NA,0,20,1,NA
507 +127,Algic,NA,0,20,2,NA
508 +127,Algic,NA,0,20,3,NA
509 +127,Algic,NA,0,20,4,-0.020865687
510 +128,Athabaskan-Eyak-Tlingit,0,0,18,1,NA
511 +128,Athabaskan-Eyak-Tlingit,0,0,18,2,NA
512 +128,Athabaskan-Eyak-Tlingit,0,0,18,3,NA
513 +128,Athabaskan-Eyak-Tlingit,0,0,18,4,-0.507859059
514 +129,Athabaskan-Eyak-Tlingit,NA,0,14,1,NA
515 +129,Athabaskan-Eyak-Tlingit,NA,0,14,2,NA
516 +129,Athabaskan-Eyak-Tlingit,NA,0,14,3,NA
517 +129,Athabaskan-Eyak-Tlingit,NA,0,14,4,-0.371900546
518 +130,Athabaskan-Eyak-Tlingit,NA,0,16,1,-1.117646018
519 +130,Athabaskan-Eyak-Tlingit,NA,0,16,2,-1.400410576
520 +130,Athabaskan-Eyak-Tlingit,NA,0,16,3,NA
521 +130,Athabaskan-Eyak-Tlingit,NA,0,16,4,-0.284366587
522 +131,Haida,NA,0,23,1,NA
523 +131,Haida,NA,0,23,2,-1.400410576
524 +131,Haida,NA,0,23,3,-0.811933291
525 +131,Haida,NA,0,23,4,-0.943756356
526 +132,Salishan,0,0,22,1,-1.117646018
527 +132,Salishan,0,0,22,2,-1.400410576
528 +132,Salishan,0,0,22,3,-0.811933291
529 +132,Salishan,0,0,22,4,0.162389228
530 +133,Salishan,NA,0,22,1,NA
531 +133,Salishan,NA,0,22,2,NA
532 +133,Salishan,NA,0,22,3,NA
533 +133,Salishan,NA,0,22,4,0.311683442
534 +134,Algic,NA,0,18,1,NA
535 +134,Algic,NA,0,18,2,NA
536 +134,Algic,NA,0,18,3,NA
537 +134,Algic,NA,0,18,4,NA
538 +135,Pomoan,0,0,22,1,NA
539 +135,Pomoan,0,0,22,2,NA
540 +135,Pomoan,0,0,22,3,NA
541 +135,Pomoan,0,0,22,4,-0.281204642
542 +136,Yokutsan,NA,0,21,1,NA
543 +136,Yokutsan,NA,0,21,2,NA
544 +136,Yokutsan,NA,0,21,3,NA
545 +136,Yokutsan,NA,0,21,4,-0.849968863
546 +137,Uto-Aztecan,NA,0,14,1,NA
547 +137,Uto-Aztecan,NA,0,14,2,NA
548 +137,Uto-Aztecan,NA,0,14,3,NA
549 +137,Uto-Aztecan,NA,0,14,4,-0.122671566
550 +138,NA,NA,0,14,1,-0.114630361
551 +138,NA,NA,0,14,2,-0.545126265
552 +138,NA,NA,0,14,3,0.270644430
553 +138,NA,NA,0,14,4,0.329048341
554 +139,NA,0,0,18,1,NA
555 +139,NA,0,0,18,2,NA
556 +139,NA,0,0,18,3,NA
557 +139,NA,0,0,18,4,0.277500728
558 +140,Algic,1,1,18,1,NA
559 +140,Algic,1,1,18,2,NA
560 +140,Algic,1,1,18,3,NA
561 +140,Algic,1,1,18,4,-0.133226989
562 +141,Siouan,0,0,24,1,-0.114630361
563 +141,Siouan,0,0,24,2,-0.545126265
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568 +142,Caddoan,0,0,25,3,2.435799873
569 +142,Caddoan,0,0,25,4,-0.199172779
570 +143,Siouan,NA,0,25,1,NA
571 +143,Siouan,NA,0,25,2,NA
572 +143,Siouan,NA,0,25,3,NA
573 +143,Siouan,NA,0,25,4,-0.112245133
574 +144,Iroquoian,0,0,28,1,1.891400953
575 +144,Iroquoian,0,0,28,2,1.165442359
576 +144,Iroquoian,0,0,28,3,NA
577 +144,Iroquoian,0,0,28,4,0.421468875
578 +145,Muskogean,0,0,29,1,NA
579 +145,Muskogean,0,0,29,2,NA
580 +145,Muskogean,0,0,29,3,NA
581 +145,Muskogean,0,0,29,4,0.239435725
582 +146,NA,0,0,32,1,NA
583 +146,NA,0,0,32,2,NA
584 +146,NA,0,0,32,3,NA
585 +146,NA,0,0,32,4,0.076957044
586 +147,Uto-Aztecan,NA,NA,17,1,NA
587 +147,Uto-Aztecan,NA,NA,17,2,NA
588 +147,Uto-Aztecan,NA,NA,17,3,NA
589 +147,Uto-Aztecan,NA,NA,17,4,-0.348009156
590 +148,Athabaskan-Eyak-Tlingit,NA,0,15,1,NA
591 +148,Athabaskan-Eyak-Tlingit,NA,0,15,2,NA
592 +148,Athabaskan-Eyak-Tlingit,NA,0,15,3,NA
593 +148,Athabaskan-Eyak-Tlingit,NA,0,15,4,-0.097100861
594 +149,NA,NA,0,35,1,NA
595 +149,NA,NA,0,35,2,NA
596 +149,NA,NA,0,35,3,NA
597 +149,NA,NA,0,35,4,-0.311511294
598 +150,Cochimi-Yuman,NA,0,20,1,NA
599 +150,Cochimi-Yuman,NA,0,20,2,1.165442359
600 +150,Cochimi-Yuman,NA,0,20,3,NA
601 +150,Cochimi-Yuman,NA,0,20,4,-0.472718402
602 +151,Uto-Aztecan,1,1,27,1,0.888385296
603 +151,Uto-Aztecan,1,1,27,2,1.165442359
604 +151,Uto-Aztecan,1,1,27,3,0.270644430
605 +151,Uto-Aztecan,1,1,27,4,-1.177386251
606 +152,Uto-Aztecan,NA,NA,28,1,NA
607 +152,Uto-Aztecan,NA,NA,28,2,NA
608 +152,Uto-Aztecan,NA,NA,28,3,NA
609 +152,Uto-Aztecan,NA,NA,28,4,0.256988493
610 +153,Uto-Aztecan,0,0,44,1,NA
611 +153,Uto-Aztecan,0,0,44,2,NA
612 +153,Uto-Aztecan,0,0,44,3,NA
613 +153,Uto-Aztecan,0,0,44,4,0.620765980
614 +154,Mixe-Zoque,1,1,29,1,-1.117646018
615 +154,Mixe-Zoque,1,1,29,2,NA
616 +154,Mixe-Zoque,1,1,29,3,-0.811933291
617 +154,Mixe-Zoque,1,1,29,4,0.925953627
618 +155,Mayan,1,1,35,1,NA
619 +155,Mayan,1,1,35,2,NA
620 +155,Mayan,1,1,35,3,NA
621 +155,Mayan,1,1,35,4,0.474413155
622 +156,Misumalpan,1,1,27,1,NA
623 +156,Misumalpan,1,1,27,2,-1.400410576
624 +156,Misumalpan,1,1,27,3,-0.811933291
625 +156,Misumalpan,1,1,27,4,-0.260933681
626 +157,Chibchan,0,0,23,1,NA
627 +157,Chibchan,0,0,23,2,NA
628 +157,Chibchan,0,0,23,3,NA
629 +157,Chibchan,0,0,23,4,1.253194889
630 +158,Chibchan,1,1,33,1,NA
631 +158,Chibchan,1,1,33,2,NA
632 +158,Chibchan,1,1,33,3,NA
633 +158,Chibchan,1,1,33,4,1.124995658
634 +159,Arawakan,0,0,20,1,-0.114630361
635 +159,Arawakan,0,0,20,2,1.165442359
636 +159,Arawakan,0,0,20,3,0.270644430
637 +159,Arawakan,0,0,20,4,-0.408503520
638 +160,Indo-European,1,1,45,1,-0.114630361
639 +160,Indo-European,1,1,45,2,1.165442359
640 +160,Indo-European,1,1,45,3,2.435799873
641 +160,Indo-European,1,1,45,4,-1.310751093
642 +161,Arawakan,0,0,26,1,NA
643 +161,Arawakan,0,0,26,2,NA
644 +161,Arawakan,0,0,26,3,NA
645 +161,Arawakan,0,0,26,4,-1.436846177
646 +162,NA,1,1,16,1,NA
647 +162,NA,1,1,16,2,1.165442359
648 +162,NA,1,1,16,3,NA
649 +162,NA,1,1,16,4,0.932068444
650 +163,Yanomamic,NA,0,18,1,NA
651 +163,Yanomamic,NA,0,18,2,NA
652 +163,Yanomamic,NA,0,18,3,NA
653 +163,Yanomamic,NA,0,18,4,1.676702282
654 +164,Cariban,0,0,18,1,-0.114630361
655 +164,Cariban,0,0,18,2,0.310158047
656 +164,Cariban,0,0,18,3,-0.811933291
657 +164,Cariban,0,0,18,4,1.476017453
658 +165,Indo-European,NA,NA,26,1,-0.114630361
659 +165,Indo-European,NA,NA,26,2,-0.545126265
660 +165,Indo-European,NA,NA,26,3,NA
661 +165,Indo-European,NA,NA,26,4,1.688527752
662 +166,Tupian,NA,0,21,1,NA
663 +166,Tupian,NA,0,21,2,NA
664 +166,Tupian,NA,0,21,3,NA
665 +166,Tupian,NA,0,21,4,1.627346381
666 +167,Tucanoan,NA,0,20,1,NA
667 +167,Tucanoan,NA,0,20,2,NA
668 +167,Tucanoan,NA,0,20,3,NA
669 +167,Tucanoan,NA,0,20,4,1.740313941
670 +168,Barbacoan,NA,0,24,1,-1.117646018
671 +168,Barbacoan,NA,0,24,2,-1.400410576
672 +168,Barbacoan,NA,0,24,3,-0.811933291
673 +168,Barbacoan,NA,0,24,4,1.262964904
674 +169,Chicham,NA,0,18,1,NA
675 +169,Chicham,NA,0,18,2,NA
676 +169,Chicham,NA,0,18,3,NA
677 +169,Chicham,NA,0,18,4,1.524907322
678 +170,Pano-Tacanan,NA,0,18,1,NA
679 +170,Pano-Tacanan,NA,0,18,2,NA
680 +170,Pano-Tacanan,NA,0,18,3,NA
681 +170,Pano-Tacanan,NA,0,18,4,1.758676861
682 +171,Quechuan,0,0,36,1,NA
683 +171,Quechuan,0,0,36,2,NA
684 +171,Quechuan,0,0,36,3,NA
685 +171,Quechuan,0,0,36,4,1.148273674
686 +172,Aymaran,1,1,34,1,NA
687 +172,Aymaran,1,1,34,2,1.165442359
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692 +173,Tupian,0,0,14,3,0.270644430
693 +173,Tupian,0,0,14,4,0.891860570
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695 +174,Nambiquaran,NA,0,16,2,NA
696 +174,Nambiquaran,NA,0,16,3,NA
697 +174,Nambiquaran,NA,0,16,4,0.998569826
698 +175,NA,NA,0,20,1,NA
699 +175,NA,NA,0,20,2,NA
700 +175,NA,NA,0,20,3,NA
701 +175,NA,NA,0,20,4,0.958440573
702 +176,Nuclear-Macro-Je,NA,0,23,1,NA
703 +176,Nuclear-Macro-Je,NA,0,23,2,NA
704 +176,Nuclear-Macro-Je,NA,0,23,3,NA
705 +176,Nuclear-Macro-Je,NA,0,23,4,0.884796108
706 +177,Tupian,0,0,24,1,NA
707 +177,Tupian,0,0,24,2,NA
708 +177,Tupian,0,0,24,3,NA
709 +177,Tupian,0,0,24,4,1.739951595
710 +178,Nuclear-Macro-Je,NA,NA,11,1,NA
711 +178,Nuclear-Macro-Je,NA,NA,11,2,NA
712 +178,Nuclear-Macro-Je,NA,NA,11,3,NA
713 +178,Nuclear-Macro-Je,NA,NA,11,4,1.217134340
714 +179,Nuclear-Macro-Je,NA,0,15,1,NA
715 +179,Nuclear-Macro-Je,NA,0,15,2,-1.400410576
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720 +180,Nuclear-Macro-Je,NA,0,11,3,NA
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723 +181,Tupian,NA,NA,16,2,NA
724 +181,Tupian,NA,NA,16,3,NA
725 +181,Tupian,NA,NA,16,4,0.874289016
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727 +182,Lengua-Mascoy,0,0,18,2,1.165442359
728 +182,Lengua-Mascoy,0,0,18,3,NA
729 +182,Lengua-Mascoy,0,0,18,4,0.213463460
730 +183,Guaicuruan,NA,0,19,1,NA
731 +183,Guaicuruan,NA,0,19,2,NA
732 +183,Guaicuruan,NA,0,19,3,NA
733 +183,Guaicuruan,NA,0,19,4,0.318958713
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735 +184,Araucanian,0,0,33,2,0.310158047
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738 +185,Chonan,0,0,16,1,NA
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740 +185,Chonan,0,0,16,3,-0.811933291
741 +185,Chonan,0,0,16,4,-0.900761568
742 +186,NA,1,1,11,1,-1.117646018
743 +186,NA,1,1,11,2,1.165442359
744 +186,NA,1,1,11,3,-0.811933291
745 +186,NA,1,1,11,4,NA
746 +
EmberEtAl-2019-LandTenure-Supplement.docx
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EmberEtAl-2019-LandTenureDataSet.csv
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1 +SCCS_ID,socname,OurSample88,CombinedSample,Com567,Com567_PryorRobust,RobustPriv_Pryor,L2_R,L2_1_234,L2_Pryor_CONAN,L3_R,L4_R,L5_R,L6_R,L7_R,HerdLgAnimORSumHG_5ormore,Irrigation,v150,v150SH14_5,oth_famsh5,PC1_1267_1269cen,v205_Fishing,HuntGath,DepHerdMoveLargeAnimLONG,DepHerdMoveLargeAnimTRUN,DepHerdMoveLargeAnimTRUN_pig0,language_family,Afro_Asiatic,Algic,Arawakan,Athabaskan_Eyak_Tlingit,Atlantic_Congo,Austroasiatic,Austronesian,Chibchan,Dravidian,Eskimo_Aleut,Indo_European,Mande,Nilotic,NuclearTransNewGuinea,Nuclear_Macro_Je,Salishan,Sino_Tibetan,Siouan,Tupian,Turkic,Uralic,Uto_Aztecan,CCR_All3,z_irr_z_CCR,PE_th,PE_pm,PDSI,Interannual_coef_var,agricul1,govt2,govt4,,
2 +1,Nama Hottentot,1,1,3.5,0,NA,2,1,1,3.5,2.5,1.0,1.5,1.0,1,1,1,0,2,NA,1,0,5,1,1,Khoe-Kwadi,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.07,-0.074830107,0.68,0.58,0.1,0.57,0,0,0,,
3 +2,Kung Bushmen,1,1,3,NA,1,4,1,1,3.0,3.0,1.0,1.0,1.0,1,1,1,0,NA,NA,0,1,NA,NA,0,Kxa,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.22,-1.071399286,0.61,0.92,0.27,0.36,0,1,0,,
4 +3,Thonga,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,4,0,NA,0.37505,1,0,3,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
5 +4,Lozi,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,3,0,NA,NA,1,0,2,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
6 +5,Mbundu,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,2,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
7 +6,Suku,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,4,0,NA,NA,1,0,0,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
8 +7,Bemba,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,4,0,NA,NA,1,0,0,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,1,,
9 +8,Nyakyusa,1,1,7,2,NA,4,1,1,2.0,3.0,3.0,2.5,1.5,0,1,4,0,2,-0.40073,1,0,2,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.05,0.058045784,0.52,0.35,0.17,0.55,1,1,0,,
10 +9,Hadza,0,0,NA,NA,0,0,NA,NA,0.0,0.0,0.0,0.0,0.0,1,1,1,0,3,NA,0,1,NA,NA,0,NA,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.1,-0.274143943,0.81,0.92,0.11,0.21,NA,NA,NA,,
11 +10,Luguru,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,1,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
12 +11,Kikuyu,0,1,NA,3,3,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,0.69427,0,0,3,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
13 +12,Ganda,1,1,7,2,NA,4,1,1,5.0,2.5,2.5,2.5,2.0,0,1,5,1,2,NA,1,0,1,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,0.77,0.79,NA,0.18,1,1,1,,
14 +13,Mbuti,1,1,3.5,0,0,4,1,1,3.0,3.0,1.0,1.5,1.0,1,1,1,0,1,-1.80288,0,1,NA,NA,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.08,-0.141268052,0.4,0.2,0.23,0.24,1,1,1,,
15 +14,Nkundo Mongo,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,0,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
16 +15,Banen,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,1,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
17 +16,Tiv,0,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,0.69427,1,0,1,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
18 +17,Ibo,0,0,NA,2,2,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,-0.84523,0,0,1,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
19 +18,Fon,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,2,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
20 +19,Ashanti,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,0,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,1,,
21 +20,Mende,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,1,0,0,Mande,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
22 +21,Wolof,1,1,6.5,2,2.5,4,1,1,2.0,3.0,2.5,2.0,2.0,0,1,5,1,4,NA,1,0,3,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.08,-0.141268052,0.29,0.75,0.16,0.39,1,1,1,,
23 +22,Bambara,1,1,7,2,NA,4,1,1,2.0,1.5,2.0,2.5,2.5,0,1,5,1,NA,NA,1,0,2,0,0,Mande,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0.25,-1.270713122,0.76,0.91,0.27,0.14,1,1,1,,
24 +23,Tallensi,1,0,7,2,2,2,1,NA,2.5,2.0,2.0,2.5,2.5,0,1,5,1,4,0.69427,0,0,2,0,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.05,0.058045784,0.35,0.32,0.13,0.16,0,1,1,,
25 +24,Songhai,1,1,9,3,NA,2,1,1,2.0,2.5,3.0,3.0,3.0,0,1,5,1,2,NA,2,0,3,0,0,Songhay,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.04,0.124483729,0.44,0.41,0.12,0.19,NA,NA,NA,,
26 +25,Pastoral Fulani,1,1,5,NA,0,2,1,1,3.0,3.0,3.0,1.0,1.0,1,1,1,0,5,0.69427,0,0,9,1,1,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.82,0.82,0,0.46,NA,NA,NA,,
27 +26,Hausa,1,0,9.5,3,3,1,0,NA,1.0,3.0,3.5,3.0,3.0,0,2,5,1,5,0.37505,0,0,3,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.08,0.764796006,0.26,0.3,0.17,0.18,1,1,1,,
28 +27,Massa (Masa),0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,2,5,1,NA,0.69427,3,0,1,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.03,-1.033610444,0.24,0.3,0.04,0.28,NA,NA,NA,,
29 +28,Azande,0,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,NA,NA,0,Atlantic-Congo,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
30 +29,Fur (Darfur),0,0,NA,2,2,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,3,0,0,Furan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.1,-0.274143943,0.26,0.33,0.19,0.83,NA,NA,NA,,
31 +30,Otoro Nuba,1,1,9,3,NA,2,1,1,3.0,3.0,3.0,3.0,3.0,0,1,5,1,5,0.37505,0,0,2,0,0,Heibanic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.04,0.16,0.04,0.2,NA,NA,NA,,
32 +31,Shilluk,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,0.69427,1,0,2,0,0,Nilotic,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
33 +32,Mao,1,1,7.5,2,NA,2,1,1,3.0,3.0,3.0,3.0,1.5,0,1,5,1,2,NA,1,0,1,0,0,Blue Nile Mao,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,-0.008392162,0.62,0.67,0.07,0.21,NA,NA,NA,,
34 +33,Kaffa (Kafa),0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,2,0,0,Ta-Ne-Omotic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
35 +34,Masai,1,1,3,0,0,2,1,1,3.5,3.0,1.0,1.0,1.0,1,1,1,0,5,NA,0,0,9,1,1,Nilotic,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0.1,-0.274143943,0.75,0.94,0.11,0.27,1,0,0,,
36 +35,Konso,1,1,12,3,3,1,0,0,1.0,4.0,4.0,4.0,4.0,0,1,5,1,NA,0.69427,0,0,2,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.07,-0.074830107,0.48,0.46,0.34,0.21,NA,NA,NA,,
37 +36,Somali,1,1,4,0,0,2,1,1,4.0,2.5,1.5,1.5,1.0,1,1,1,0,2,0.37505,0,0,9,1,1,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.11,-0.340581888,0.82,0.6,0.27,0.74,0,1,1,,
38 +37,Amhara,1,0,8,NA,2,1,0,NA,1.0,3.0,3.0,3.0,2.0,0,1,5,1,1,1.32064,1,0,3,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.07,-0.074830107,0.57,0.6,0.14,0.25,1,1,0,,
39 +38,Bogo,0,1,NA,3,3,NA,NA,0,NA,NA,NA,NA,NA,1,1,3,0,NA,0.37505,0,0,9,1,1,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
40 +39,Kenuzi Nubians,0,1,NA,3,2.5,NA,NA,0,NA,NA,NA,NA,NA,0,2,5,1,NA,NA,1,0,3,0,0,Nubian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-2.112654314,0.88,0.58,0,1.73,NA,NA,NA,,
41 +40,Teda,1,1,6,2,NA,2,1,1,3.0,3.0,2.5,2.0,1.5,0,2,1,0,5,0.69427,0,0,3,0,0,Saharan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-2.112654314,0.81,0.51,0,0.85,1,1,1,,
42 +41,Tuareg,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,2,1,0,NA,0.69427,0,0,5,1,1,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,0,0,,
43 +42,Riffians,1,1,11,3,NA,1,0,0,1.0,4.0,3.5,4.0,3.5,0,1,5,1,2,NA,1,0,3,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.01,0.323797565,0.04,0.04,0.07,0.32,0,1,1,,
44 +43,Egyptians,1,1,10,3,3,1,0,0,1.0,4.0,3.5,4.0,2.5,0,2,5,1,NA,NA,1,0,3,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.05,-0.314247864,0.77,0.8,0.04,0.83,1,1,1,,
45 +44,Hebrews,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,3,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.07,0.14,0,0.45,NA,NA,NA,,
46 +45,Babylonians,1,1,11,3,NA,2,1,1,1.0,4.0,4.0,4.0,3.0,0,2,5,1,2,NA,2,0,2,0,0,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-2.112654314,0.08,0.07,0.07,0.51,NA,NA,NA,,
47 +46,Rwala Bedouin,1,1,3.5,0,NA,1,0,0,1.0,3.0,1.0,1.5,1.0,1,1,1,0,5,0.37505,0,0,8,1,1,Afro-Asiatic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.15,-0.606333669,0.61,0.75,0.2,0.34,NA,NA,NA,,
48 +47,Turks,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,1.32064,0,0,4,0,0,Turkic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0.39023551,0.04,0.06,0,0.32,0,1,0,,
49 +48,Gheg Albanians,0,0,NA,3,2.5,NA,NA,NA,NA,NA,NA,NA,NA,0,1,3,0,NA,NA,0,0,4,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,0,,
50 +49,Romans,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,1.32064,2,0,2,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,1,,
51 +50,Basques,0,1,NA,2,2,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,4,0,0,Basque,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
52 +51,Irish,1,1,12,3,NA,1,0,0,1.0,4.0,4.0,4.0,4.0,0,1,5,1,NA,-0.84523,0,0,4,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.78,0.94,0,0.3,0,0,0,,
53 +52,Lapps,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,1,1,0,NA,NA,2,0,6,1,1,Uralic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0.15,-0.606333669,0.49,0.48,0.24,0.21,1,0,0,,
54 +53,Yurak Samoyed,1,1,7,NA,1,2,1,1,3.0,2.0,2.0,3.0,2.0,0,1,1,0,5,NA,3,0,4,0,0,Uralic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0.06,-0.008392162,0.55,0.53,0.11,0.3,0,1,0,,
55 +54,Russians,1,1,4,0,NA,4,1,1,2.0,1.0,1.5,1.5,1.0,0,2,5,1,NA,1.32064,0,0,3,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0.06,0.045433426,0.85,0.96,0.06,0.2,0,1,0,,
56 +55,Abkhaz,1,1,6.5,2,2,2,1,1,2.5,2.5,2.5,2.5,1.5,1,1,5,1,NA,NA,0,0,6,1,1,Abkhaz-Adyge,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.25,0.42,0,0.16,0,0,0,,
57 +56,Armenians,0,0,NA,3,3,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,3,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
58 +57,Kurd,1,1,6,NA,3,1,0,0,1.0,1.5,2.0,2.5,1.5,0,2,5,1,1,NA,1,0,4,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,-2.112654314,0,0.01,0.14,0.57,1,1,0,,
59 +58,Basseri,1,1,4,0,0,2,1,1,3.0,3.0,1.0,1.5,1.5,1,1,1,0,2,NA,0,0,8,1,1,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0.13,-0.473457779,0.66,0.96,0.17,0.66,NA,NA,NA,,
60 +59,Punjabi (West),1,1,12,3,3,1,0,0,2.0,4.0,4.0,4.0,4.0,0,1,5,1,5,NA,0,0,2,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0.01,0.323797565,0.11,0.06,0.17,0.3,NA,NA,NA,,
61 +60,Gond,1,1,4.5,1,NA,2,1,1,2.0,2.0,1.5,2.0,1.0,0,1,4,0,1,-1.80288,0,0,2,0,0,Dravidian,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,-0.008392162,0.5,0.51,0.22,0.24,1,1,0,,
62 +61,Toda,0,1,NA,0,0,NA,NA,1,NA,NA,NA,NA,NA,1,1,3,0,NA,NA,0,0,9,1,1,Dravidian,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,1,,
63 +62,Santal,1,1,6.5,2,NA,1,0,0,1.0,2.0,2.0,2.5,2.0,0,2,5,1,2,0.23771,1,0,1,0,0,Austroasiatic,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-2.112654314,0,0,0.13,0.19,1,1,0,,
64 +63,Uttar Pradesh,1,1,6.5,2,2,1,0,0,1.0,2.0,2.0,2.5,2.0,0,2,5,1,2,NA,0,0,2,0,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0.01,-1.752973024,0.13,0.06,0.14,0.24,0,0,0,,
65 +64,Burusho,1,1,9.5,NA,2,1,0,0,1.0,2.0,3.0,3.0,3.5,0,2,5,1,1,NA,0,0,4,0,0,NA,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.14,2.922883746,0.25,0.52,0.26,0.34,1,0,1,,
66 +65,Kazak,1,1,6,NA,0,2,1,1,3.0,3.0,2.5,2.0,1.5,1,1,2,0,5,0.86408,0,0,8,1,1,Turkic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0.25,-1.270713122,0.89,0.98,0.28,0.54,0,1,0,,
67 +66,Khalka Mongols,1,1,5,NA,0,4,1,1,3.5,2.5,2.0,1.5,1.5,1,1,2,0,4,NA,0,0,8,1,1,Mongolic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.09,-0.207705997,0.83,0.94,0.1,0.34,1,1,1,,
68 +67,Lolo,0,1,NA,3,3,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,3,0,0,Sino-Tibetan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,0,0,,
69 +68,Lepcha,1,1,6,2,2,1,0,0,1.0,2.0,2.0,2.0,2.0,0,1,5,1,1,0.37505,0,0,3,0,0,Sino-Tibetan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0.18,-0.805647505,0.83,0.94,0.1,0.22,1,0,1,,
70 +69,Garo,0,1,NA,2,2,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,-1.48366,1,0,1,0,0,Sino-Tibetan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
71 +70,Lakher,1,1,8,3,NA,4,1,1,2.0,2.0,3.0,2.0,3.0,0,1,5,1,5,0.86408,1,0,1,0,0,Sino-Tibetan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0.04,0.124483729,0.49,0.52,0.07,0.15,NA,NA,NA,,
72 +71,Burmese,1,1,12,3,2.5,1,0,0,1.0,3.5,4.0,4.0,4.0,0,2,5,1,NA,-1.80288,0,0,2,0,0,Sino-Tibetan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0.02,-1.393291734,0.83,0.91,0.02,0.3,1,1,1,,
73 +72,Lamet,1,1,8.5,3,NA,4,1,1,2.5,3.5,3.0,3.0,2.5,0,1,3,0,2,NA,0,0,2,0,0,Austroasiatic,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.13,-0.473457779,0.84,0.89,0.13,0.14,NA,NA,NA,,
74 +73,Vietnamese,1,1,10,3,NA,1,0,0,1.0,3.0,4.0,3.0,3.0,0,2,5,1,3,-0.08151,2,0,2,0,0,Austroasiatic,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.03,-1.033610444,0.52,0.3,0.1,0.18,1,1,1,,
75 +74,Rhade,0,1,NA,3,3,NA,NA,1,NA,NA,NA,NA,NA,0,1,4,0,NA,0.37505,0,0,1,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
76 +75,Khmer,0,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,3,0,0,Austroasiatic,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
77 +76,Siamese,1,1,10,3,3,1,0,0,1.0,3.0,3.5,3.5,3.0,0,2,5,1,3,-1.80288,1,0,1,0,0,Tai-Kadai,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.13,2.563202456,0.82,0.92,0.16,0.28,0,0,0,,
78 +77,Semang,0,1,NA,1,0.5,NA,NA,1,NA,NA,NA,NA,NA,1,1,1,0,NA,NA,3,1,NA,NA,0,Austroasiatic,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,0,,
79 +78,Nicobarese,0,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,-1.80288,2,0,NA,NA,0,Austroasiatic,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
80 +79,Andamanese,0,1,NA,0,0,NA,NA,1,NA,NA,NA,NA,NA,1,1,2,0,NA,-1.80288,4,1,NA,NA,0,Great Andamanese,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
81 +80,Vedda,0,1,NA,1,1,NA,NA,1,NA,NA,NA,NA,NA,1,1,2,0,NA,NA,3,1,NA,NA,0,Indo-European,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,0,,
82 +81,Tanala,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,2,3,0,NA,NA,2,0,2,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
83 +82,Negri Sembilan,0,1,NA,2,2,NA,NA,0,NA,NA,NA,NA,NA,0,2,5,1,NA,NA,1,0,1,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
84 +83,Javanese,1,1,10,3,2.5,1,0,0,1.0,2.0,3.5,3.5,3.0,0,2,5,1,3,NA,0,0,2,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,0.045433426,0.53,0.34,0.13,0.32,1,1,0,,
85 +84,Balinese,1,0,6.5,2,2,4,1,NA,2.0,2.0,2.0,2.5,2.0,0,2,5,1,2,NA,0,0,3,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-2.112654314,0.44,0,0,0.39,0,1,1,,
86 +85,Iban,1,0,6,2,NA,3,1,NA,2.5,2.5,2.5,2.0,1.5,0,1,4,0,2,NA,2,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,-0.008392162,0.32,0.23,0.17,0.42,1,1,1,,
87 +86,Badjau,0,1,NA,0,0,NA,NA,1,NA,NA,NA,NA,NA,0,1,1,0,NA,NA,8,0,0,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.42,0,0,0.42,NA,NA,NA,,
88 +87,Toradja,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,2,0,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
89 +88,Tobelorese,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,NA,NA,0,North Halmahera,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
90 +89,Alorese,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,NA,NA,0,Timor-Alor-Pantar,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,1,,
91 +90,Tiwi,1,1,3.5,0,0,4,1,1,3.0,2.5,1.0,1.5,1.0,1,1,1,0,1,NA,2,1,NA,NA,0,NA,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.94,0,0,0.42,0,1,0,,
92 +91,Aranda,1,1,3,0,0,2,1,1,3.0,3.0,1.0,1.0,1.0,1,1,1,0,2,NA,0,1,NA,NA,0,Pama-Nyungan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.22,-1.071399286,0.79,0.62,0.29,0.67,0,1,0,,
93 +92,Orokaiva,1,1,6,2,NA,2,1,1,2.5,3.0,2.5,2.5,1.0,0,1,5,1,NA,NA,2,0,NA,NA,0,Nuclear Trans New Guinea,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0.13,-0.473457779,0.46,0.34,0.12,0.27,1,0,0,,
94 +93,Kimam,1,1,4.5,1,NA,4,1,1,3.0,3.0,2.0,1.5,1.0,0,1,5,1,5,-0.08151,1,0,NA,NA,0,Kolopom,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,-0.008392162,0.83,0.82,0.05,0.34,NA,NA,NA,,
95 +94,Kapauku,1,0,9,3,NA,2,1,NA,2.0,3.0,3.5,3.0,2.5,0,1,5,1,NA,NA,1,0,NA,NA,0,Nuclear Trans New Guinea,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0.09,-0.207705997,0.39,0.32,0.11,0.48,1,0,0,,
96 +95,Kwoma,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,1,5,1,NA,NA,0,1,NA,NA,0,Sepik,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,0,0,,
97 +96,Manus,1,1,5,1,1,4,1,1,2.0,3.0,1.5,2.0,1.5,0,1,5,1,1,0.69427,9,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.42,0,0,0.18,0,1,1,,
98 +97,New Ireland,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,0.23771,4,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,0,1,,
99 +98,Trobrianders,1,1,6.5,2,NA,2,1,1,2.0,3.0,2.0,2.5,2.0,0,1,5,1,5,0.69427,3,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.45,0,0,0.18,1,1,1,,
100 +99,Siuai,1,1,7,2,NA,4,1,1,2.0,4.0,3.0,2.5,1.5,0,1,5,1,NA,-0.08151,0,0,NA,NA,0,South Bougainville,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.5,0.34,0,0.18,NA,NA,NA,,
101 +100,Tikopia,1,1,6.5,2,NA,2,1,1,2.0,3.0,2.5,2.5,1.5,0,1,5,1,5,0.23771,5,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0,0,0,0.49,1,1,0,,
102 +101,Pentecost,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
103 +102,Mbau Fijians,1,1,9,NA,1,2,1,1,2.0,3.0,3.0,3.0,3.0,0,1,5,1,1,-1.80288,5,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.45,0,0,0.49,NA,NA,NA,,
104 +103,Ajie,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,2,5,1,NA,NA,3,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
105 +104,Maori,1,1,5,1,1,3,1,1,2.5,3.0,2.0,1.5,1.5,0,1,5,1,5,NA,2,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.07,-0.074830107,0.8,0.97,0.07,0.18,1,1,0,,
106 +105,Marquesans,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,0.69427,4,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,0,0,,
107 +106,Western Samoans,1,1,8,3,NA,2,1,1,2.0,2.5,3.0,3.0,2.0,0,1,5,1,4,NA,3,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.45,0,0,0.15,0,1,0,,
108 +107,Gilbertese,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,4,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
109 +108,Marshallese,1,0,7,NA,3,2,1,NA,2.0,2.0,2.5,2.5,2.0,0,1,5,1,5,1.32064,5,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0,0,0,0.23,1,1,0,,
110 +109,Trukese,1,1,7.5,2,NA,2,1,1,2.0,3.0,3.0,2.5,2.0,0,1,5,1,2,0.23771,5,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.45,0,0,0.14,1,1,0,,
111 +110,Yapese,1,1,6.5,2,NA,4,1,1,2.0,3.0,2.5,2.0,2.0,0,1,5,1,NA,NA,4,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.49,0,0,0.21,0,1,0,,
112 +111,Palauans,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,4,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,,NA,NA,NA,,
113 +112,Ifugao,1,1,9.5,3,NA,1,0,0,1.0,3.0,3.5,3.5,2.5,0,2,5,1,3,-0.40073,1,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.18,4.361608907,0.5,0.51,0.25,0.23,1,1,1,,
114 +113,Atayal,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,4,0,NA,NA,1,0,NA,NA,0,Austronesian,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
115 +114,Chinese,0,1,NA,3,3,NA,NA,0,NA,NA,NA,NA,NA,0,2,5,1,NA,NA,1,0,1,0,0,Sino-Tibetan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
116 +115,Manchu,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,2,0,0,Tungusic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
117 +116,Koreans,1,1,8.5,3,NA,1,0,0,1.0,2.5,3.0,3.0,2.5,0,2,5,1,2,0.86408,2,0,2,0,0,Koreanic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,0.59,0.65,NA,0.27,0,1,0,,
118 +117,Japanese,1,1,10,3,NA,1,0,0,1.0,2.5,2.5,4.0,3.5,0,2,5,1,2,NA,0,0,1,0,0,Japonic,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.06,0.045433426,0.82,0.95,0.06,0.22,0,1,1,,
119 +118,Ainu,1,1,5,1,1,3,1,1,3.0,3.0,1.5,2.5,1.0,1,1,3,0,1,-0.38866,4,1,NA,NA,0,Ainu,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.8,0.91,0,0.2,0,1,0,,
120 +119,Gilyak,1,1,5.5,1,1,2,1,1,3.0,2.5,1.5,2.0,2.0,1,1,2,0,5,NA,5,1,NA,NA,0,NA,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.91,0,0,0.24,1,1,1,,
121 +120,Yukaghir,0,0,NA,2,1.5,NA,NA,NA,NA,NA,NA,NA,NA,1,1,1,0,NA,0.37505,4,1,NA,NA,0,Yukaghir,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
122 +121,Chukchee,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,1,2,0,NA,0.69427,3,0,5,1,1,Chukotko-Kamchatkan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,1,0.99,1,0.22,0,1,0,,
123 +122,Ingalik,0,0,NA,2,1.5,NA,NA,NA,NA,NA,NA,NA,NA,1,1,3,0,NA,0.69427,5,1,NA,NA,0,Athabaskan-Eyak-Tlingit,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
124 +123,Aleut,0,0,NA,0,0,NA,NA,NA,NA,NA,NA,NA,NA,0,1,3,0,NA,0.69427,6,0,NA,NA,0,Eskimo-Aleut,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,1,,
125 +124,Copper Eskimo,1,1,3.5,0,0,4,1,1,3.0,3.0,1.5,1.0,1.0,0,1,2,0,5,0.69427,6,0,NA,NA,0,Eskimo-Aleut,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0.06,-0.008392162,0.44,0.51,0.13,0.34,0,1,0,,
126 +125,Montagnais,0,0,NA,2,2,NA,NA,NA,NA,NA,NA,NA,NA,1,1,2,0,NA,1.32064,2,1,NA,NA,0,Algic,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
127 +126,Micmac,0,1,NA,2,2,NA,NA,1,NA,NA,NA,NA,NA,1,1,2,0,NA,-0.08151,4,1,NA,NA,0,Algic,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,0,,
128 +127,Saulteaux,0,1,NA,2,1.5,NA,NA,1,NA,NA,NA,NA,NA,1,1,2,0,NA,1.32064,4,1,NA,NA,0,Algic,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,1,,
129 +128,Slave,0,1,NA,2,2,NA,NA,1,NA,NA,NA,NA,NA,1,1,3,0,NA,0.23771,4,1,NA,NA,0,Athabaskan-Eyak-Tlingit,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
130 +129,Kaska,0,1,NA,1,1,NA,NA,1,NA,NA,NA,NA,NA,1,1,2,0,NA,0.69427,5,1,NA,NA,0,Athabaskan-Eyak-Tlingit,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
131 +130,Eyak,1,1,3,0,0,4,1,1,4.0,3.0,1.0,1.0,1.0,1,1,3,0,1,NA,5,1,NA,NA,0,Athabaskan-Eyak-Tlingit,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.49,0.54,0,0.2,NA,NA,NA,,
132 +131,Haida,1,1,7,NA,3,4,1,1,3.0,3.0,1.0,3.0,3.0,0,1,3,0,1,0.05583,6,0,NA,NA,0,Haida,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.39023551,0.78,0,0,0.15,NA,NA,NA,,
133 +132,Bellacoola,1,1,6,2,2,2,1,1,2.5,2.5,3.0,2.0,1.0,0,1,5,1,1,-0.08151,6,0,NA,NA,0,Salishan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0.06,-0.008392162,0.84,0.94,0.06,0.18,1,1,1,,
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146 +145,Creek,0,1,NA,1,0.5,NA,NA,1,NA,NA,NA,NA,NA,0,1,3,0,NA,NA,2,0,NA,NA,0,Muskogean,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,0,1,0,,
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148 +147,Comanche,0,1,NA,0,0,NA,NA,1,NA,NA,NA,NA,NA,1,1,1,0,NA,0.37505,0,1,0,0,0,Uto-Aztecan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,NA,NA,NA,NA,NA,NA,0,1,0,,
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153 +152,Huichol,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,1,0,1,0,0,Uto-Aztecan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
154 +153,Aztec,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,2,5,1,NA,0.69427,1,0,NA,NA,0,Uto-Aztecan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,NA,NA,NA,NA,NA,NA,0,0,0,,
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156 +155,Quiche,0,1,NA,3,3,NA,NA,0,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,0,0,1,0,0,Mayan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
157 +156,Miskito,1,0,8,NA,1,1,0,NA,1.0,3.0,3.0,2.5,2.5,1,1,5,1,1,NA,2,1,1,0,0,Misumalpan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.1,-0.274143943,0.55,0.55,0.18,0.19,1,1,0,,
158 +157,Bribri,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,NA,NA,0,Chibchan,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,,1,0,0,,
159 +158,Cuna (Tule),0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,3,0,NA,NA,0,Chibchan,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,1,,
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162 +161,Callinago,0,1,NA,1,1,NA,NA,1,NA,NA,NA,NA,NA,0,1,4,0,NA,NA,5,0,NA,NA,0,Arawakan,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,0,0,,
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167 +166,Mundurucu,0,1,NA,1,1,NA,NA,1,NA,NA,NA,NA,NA,0,1,5,1,NA,NA,2,0,NA,NA,0,Tupian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,NA,NA,NA,NA,NA,NA,1,0,0,,
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170 +169,Jivaro,0,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,4,0,NA,-1.80288,1,0,NA,NA,0,Chicham,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
171 +170,Amahuaca,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,4,0,NA,-1.80288,1,0,NA,NA,0,Pano-Tacanan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,,
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175 +174,Nambicuara,0,1,NA,0,0,NA,NA,1,NA,NA,NA,NA,NA,1,1,2,0,NA,NA,1,1,NA,NA,0,Nambiquaran,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,NA,NA,NA,NA,NA,NA,1,1,0,,
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188 +,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
189 +
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1 +ID_Culture,Culture_Name,OWC,EA_ID,Place,Time,Country,Independence,R_Pacification,IntFreqSum,ReliabIntFreq,R_IntBNC1,R_IntBNC2,R_IntBNCC3,R_IntBNC4,R_IntBNC5,R_IntBNC1_Pop,R_IntBNC2_Pop,R_IntBNCC3_Pop,R_IntBNC4_Pop,R_IntBNC5_Pop,IntBNC1xPop,IntBNC2xPop,IntBNcC3xPop,IntBNc4xPop,IntBNc5xPop,BNC1to5xPopSumDivByViable,Resolved_Local_Var6,Resolved_Local_Var7,Resolved_Local_Var8,Resolved_Local_Var10,Resolved_Local_Var11,Reversed_Local_Var11,Resolved_Local_Var30,LittleFormalizedLeadership,Factor_LocalPart_Vars67811,Resolved_Multi10M_Range_of_Decision_Making_2coders,rvmult,StateShort,PopulationLog10,PopulationSoc,R_Disasters,DisastersShort
2 +29,Mongo,FO32,Ae24,"Nkundo Mongo, Ilanga group",1930,DRC,1960,3,2,1,8,8,3,8,8,8,8,4,8,8, , ,12, , , , , , , , , , ,0, ,8,0,0, , ,1,1
3 +17,Gwembe Tonga,FQ12,Ac30,Ronga subtribe,1950,Zimbabwe,1980,4,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , , , , , , , , ,0, , , , , , ,4,4
4 +22,Lakeshore Tonga,FR07,Ac13,General,1950,Malawi,1964,4,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , , , , , , , , ,0, , , , , , ,1,1
5 +25,Luo,FL11,Aj6, ,1940,Kenya,1963,4,2.5,2,1,8,1,1,1,1,8,1,1,1,1, ,1,1,1,1, , , , , , , ,0, , , , , , ,3,3
6 +46,Yao,FT07,Ac7,entire society,1920,Mozambique,1975,4,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , , , , , , , , ,0, , , , , , , ,
7 +11,Dorobo,FL06,Aa2,North Tindiret forest area,1920,Kenya,1963,9,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , , , , , , , , , , , , , , , , ,
8 +12,Ganda,FK07,Ad7,"Kyaddondo district, around Kampala",1875,Uganda,1962,1,3,3,7,7,7,7,7,7,7,7,7,7, , , , , , ,1,2,1,1,4,1,9,0,-1.64337993591686,9,1,1,5.8750612633917,750000,1,1
9 +20,Kaffa,MP14,Ca30,Entire kingdom,1905,Ethiopia,n/a,1,2,1,3,4,4,4,4,3,3,3,3,3,9,12,12,12,12,11.4,1,1,1,1.25,4,1,1,0,-1.96691076322795,1,1,1,5.69897000433602,500000,1,1
10 +40,Shilluk,FY23,Ai6,Entire Kingdom,1910,Sudan,1956,1,10,1,2,1,8,2,8,4,4,8,4,8,8,4, ,8, ,6.66666666666667,1,2,1,3,3,2,9,0,-1.32121318270477,9,1,0,4.77815125038364,60000,3,3
11 +13,Gisu,FK13,Ad9,General,1900,Uganda,1962,2,6,1,2,8,1,3,8,1,8,1,2,8,2, ,1,6, ,3,1,9,1,1.25,9, ,2,0, ,8,0, ,5.38693037036905,243742,3,3
12 +52,Hehe,FN09,Ad8,Iringa group,1890,Tanzania,1964,1,7,3,8,8,8,8,8,8,8,8,8,8, , , , , , ,1.25,1.75,1,1.75,4,1,3,0,-1.64298020116005,2.25,1,0,4.54406804435028,35000,2,2
13 +37,Nyoro,FK11,Ad2,General,1897,Uganda,1962,1,5,3,4,2.5,3,3.5,4,3,2,4,4,3,12,5,12,14,12,11,1.75,2,1.5,2.5,3,2,1.25,0,-.893552285280621,1.75,1,1,5.04139268515823,110000,3,3
14 +38,Rwandans,FO42,Ae10,General,1986,Rwanda,1962,2,8,4,4,4,4,4,4,4,4,4,4,4,16,16,16,16,16,16,1.75,1.75,1.5,2,3.25,1.75,1,0,-1.05497668041142,2,1,1,6.81224469680037,6490000,3,3
15 +2,Azande,FO07,Ai3,Yambio Chiefdom,1905,DRC,1960,1,4,1,4,4,8,4,4,3,3,8,4,3,12,12, ,16,12,13,2,3,3,1,4,1,2,0,-.259465051585853,9,1,0,4.8750612633917,75000,1,1
16 +5,Bemba,FQ05,Ac3,Zambia branch,1897,Zambia,1964,1,4.5,2,8,8,8,8,8,8,8,8,8,8, , , , , , ,2,3,2.5,2.5,3,2,1.5,0,-.121111871044158,2.25,1,0,5.14612803567824,140000,2,2
17 +23,Lozi,FQ09,Ab3,Ruling Luyana,1900,Zambia,1964,1,5,3,9,4,3,8,8,8,3,3,8,8, ,12,9, , ,10.5,2,2,1,3,3,2,1,0,-.996083416366429,9,4,1,4.82607480270083,67000,4,4
18 +54,Pare,FN04,Ad36,South Pare,1890,Tanzania,1964,1,10,1,8,8,8,8,8,8,8,8,8,8, , , , , , ,2,3,1,2,2,3,1,0,-.350385835843252,2,5,0,4.30102999566398,20000,3,3
19 +1,Amhara,MP05,Ca7,Gondar Province,1953,Ethiopia,n/a,2,7,4,2,8,2,3,2,3,8,3,3,2,6, ,6,9,4,6.25,2,2,1,1,4,1,9,0,-1.31825016957852,9,1,1,6.30102999566398,2000000,1,1
20 +3,Barundians,FQ42,Ae8,Burundi (Kingdom/Republic),1986,Burundi,1962+,2,5,3,4,4,4,4,4, , , , , , , , , , , ,2,1.5,2,2.75,3,2,1.5,0,-.790221684681184,3,1,1,6.30102999566398,2000000,2.5,2
21 +6,Bena,FN31,Ad11,"Njonge, Ulanga & Kilombero districts",1897,Tanzania,1964,2,8,4,7,7,7,7,7,7,7,7,7,7, , , , , , ,2,2,1.5,3,3.25,1.75,9,0,-.892811531999057,2,1,0,4.20411998265593,16000,2.5,2
22 +53,Lugbara,FK14,Ai32,entire society,1920,Uganda,1962,2,8,1,8,8,8,8,8,8,8,8,8,8, , , , , , ,2,2.5,2,2.75,3,2,1.75,0,-.466690857370097,8,0,1,5.38381536598043, ,4,4
23 +33,Ngoni,FR05,Ac9,General,1898,Malawi,1964,1,2.5,2,4,2,8,4,8,2,2,8,2,8,8,4, ,8, ,6.66666666666667,2.25,2.5,2,2.25,2,3,2,0,-.0632416625734208,2,4,1,4.92941892571429,85000,3,3
24 +55,Shambala,FN24,Ad10,entire society,1890,Tanzania,1964,1,9.5,2,8,8,8,8,8,8,8,8,8,8, , , , , , ,2.25,2.25,2,2,2,3,2.5,0,-.144124369401193,2.5,4,0,4.90308998699194,80000,4,4
25 +27,Mbundu,FP13,Ab5,Bailundu subtribe,1880,Angola,1975,1,6,4,8,8,8,2,8,8,8,8,3,8, , , ,6, , ,2.5,9,1.75,2,2.5,2.5,2,0, ,9,4,0,5.65321251377534,450000,3,3
26 +31,Ngonde,FN17,Ad16,General,1895,Tanzania,1964,1,9,3,1,1,8,8,8,4,4,8,8,8,4,4, , , , ,2.5,2,3,2,2.25,2.75,1.25,0,.143360822393388,3,4,0,4.60205999132796,40000,3,3
27 +10,Darfur,MQ08,Cb17,Jebel Merra,1999,Sudan,1956,2, ,5,4,4,4,4,4,4,4,4,4,4,16,16,16,16,16,16,2.75,2.5,2.25,2.25,2.5,2.5,2,0,.0301466303249044,2.25,1,1,5.69897000433602,500000,4,4
28 +8,Chagga,FN04,Ad3,"General, Chagga society",1875,Tanzania,1964,1,10,1,1,1,2,4,1,1,1,1,3,1,1,1,2,12,1,3.4,3,1.5,2,2,2.5,2.5,1.5,0,-.304008541736794,1.75,4,0,4.97772360528885,95000,1,1
29 +15,Gikuyu,FL10,Ad4,Motume district (Ft Hall),1885,Kenya,1963,1,4,1,2,2,8,2,8,1,1,8,2,8,2,2, ,4, ,2.66666666666667,3,3.25,2.25,2,2,3,2,0,.515160568998851,2,4,0,5.69897000433602,500000,3.5,3
30 +19,Ila,FQ06,Ac1,General,1880,Zambia,1964,1,3,3,4,2,4,8,4,2,2,2,8,2,8,4,8, ,8,7,3,3,2,2.25,2,3,2,0,.342371075835882,8,0,0,4.21582255515437,16437,2.5,2
31 +24,Luguru,FN27,Ad14,Morogoro district,1895,Tanzania,1964,1,5,3,8,8,8,8,8,8,8,8,8,8, , , , , , ,3,2.25,2,2.25,2,3,2,0,.0997229553525664,8,0,0,5.19033169817029,155000,8,
32 +26,Maasai,FL12,Aj2,"Kisonko or SE Maasai, Tanzania",1900,General,1963,1,9,3,2,2,1,8,8,1,1,8,8,8,2,2, , , ,2,3,3,3,2,2,3,2,0,.709998221176671,8,0,0,5,100000,3.5,3
33 +34,Nuba,FJ21,Ai10,General,1938,Sudan,1956,1,5,3,2,8,8,8,8,1,8,8,8,8,2, , , , , ,3,2.5,2,1.5,2,3,2.5,0,.180605662180338,8,0,0,4.94448267215017,88000,8,
34 +42,Suku,FO46,Ac17,Feshi territory lineage center,1920,DRC,1960,1,6.5,2,1,1,1,4,4,1,1,1,1,1,1,1,1,4,4,2.2,3,3,2,3,3,2,2,0,.0202043226237926,3,1,1,4.90308998699194,80000,1,1
35 +43,Teda,MS22,Cc2,Nomads of Tibesti,1920,Chad,1960,1,6,4,1,1,1,8,8,1,1,8,8,8,1,1, , , ,1,3,3,3,3,9, ,1,0, ,8,0,0,5.29003461136252,195000,4,4
36 +50,Giriama,FL14,Ad32,entire society,1900,Kenya,1963,1,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , ,3,2.5,3,3,2,3,1.75,0,.548232807521127,8,0,1,4.78532983501077,61000,4,4
37 +56,Acoli,FK04,Aj10,entire society,1920,Uganda,1962,2,4.5,2,2,8,3,8,8,1,8,2,8,8,2, ,6, , ,4,3,3,2,2.5,1.75,3.25,1.75,0,.422912764138904,3,4,0,5.33375953179445,2500,2,2
38 +21,Konso,MP17,Ca1,Town of Buso,1935,Ethiopia,n/a,2,6.5,2,1,2,3,2,1,8,1,2,3,8, ,2,6,6, ,4.66666666666667,3.25,2.25,2.25,1.25,2,3,2,0,.27291218327235,4,3,0,4.75966784468963,1100,4,4
39 +47,Jie,FK08,Aj21,entire society,1950,Uganda,1962,2,2,1,8,8,8,8,8,8,8,8,8,8, , , , , , ,3.25,4,3,3,2,3,2,0,1.11481149007234,2.75,4,0,4.26007138798508,18200,3,3
40 +48,Oromo,FL09,Ca39,Oromo of Arsi & Jima,1890,Kenya,1963,1,5,4,2,8,3,2,2,2,8,2,2,2,4, ,6,4,4,4.5,3.75,2,3,3,2,3,1.25,0,.630314718619342,1.5,1,0,6.90308998699194,8000000,1,1
41 +16,Gusii,FL08,Ad12,Kisii District,1915,Kenya,1963,1,8,1,1,2,2,8,2,1,1,1,8,1,1,2,2, ,2,1.75,4,4,3,2,1,4,2,1,1.68082556803819,8,0,0,5.37657695705651,238000,1,1
42 +35,Nuer,FJ22,Aj3,General,1930,Sudan,1956,1,10,1,2,1,2,2,8,1,1,1,2,8,2,1,2,4, ,2.25,4,4,3,2.75,2,3,1.75,1,1.3586588148261,8,0,0,5.63346845557959,430000,4,4
43 +41,Somali,MO04,Ca2,Dolbahanta subtribe,1900,Somali,1960,1,10,1,8,8,8,8,8,8,8,8,8,8, , , , , , ,4,4,3,1,2,3,2,1,1.3586588148261,8,0,0,4.69897000433602,50000,4,4
44 +44,Turkana,FL18,Aj5,entire society,1918,Kenya,1963,1,9,3,2,2,2,2,2,3,2,2,3,2,6,4,4,6,4,4.8,4,3.75,3,3,1.5,3.5,1,1,1.43885948460438,8,0,0,4.47712125471966,30000,4,4
45 +51,Hadza,FN11,Aa9,entire society,1930,Tanzania,1964,1,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , ,4,4,3,4,1,4,1,1,1.68082556803819,8,0,0,2.74036268949424,550,1,1
46 +28,Mbuti,FO04,Aa5,"Epulu net hunters, Ituri Forest",1950,DRC,1960,4,2,1,7,7,7,7,7,7,7,7,7,7, , , , , , ,4,4,3,3,1,4,1,1,1.68082556803819,8,0, , , ,1,1
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Ember_et_al_EAFrica_PolPart_Codes_JACPR2017.sav
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Ember_et_al_Worldwide_PolPart_Codes_JACPR2017_SHort.csv
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1 +id,name$,date$,paccode,intfreq,reliable_intfreq$,revvar6,revvar7,revvar8,revvar10,revvar11,revvar11Reversed,revvar30,LittleFormalCommLeader,rvmult,stateshort,isl,pop,popdate,poplog10
2 +187,Nyakyusa,+1890,1,5,3,3,1,2,2.5,1.75,3.25,1,0,4,1,0,49248,1921,4.69238859815138
3 +188,Bambara,<1900,1,4,2,3,9,2,1.5,3,2,1,9,1,0,0,538450,1900,5.73114538129738
4 +189,Tallensi,+1890,1,3.75,3,3.25,9,3,2.5,1.75,3.25,1.5,9,0,0,0,35000,1931,4.54406804435028
5 +190,Iban,+1820,1,4.75,2,2.5,9,1,9,4,1,1,9,0,0,0,190326,1947,5.27949812031661
6 +192,Manus,+1910,1,3.25,3,4,3.5,3,4,1.25,3.75,1.5,0,0,0,0,2000,1928,3.30102999566398
7 +193,Trobriands,+1890,1,4.25,3,3,1,3,1.5,1.75,3.25,3,0,1,0,1,9000,1920,3.95424250943932
8 +194,Marshallese,+1875,1,4.75,3,1,1,1,1,4,1,3,0,1,0,1,10250,1874,4.01072386539177
9 +195,Truk,+1900,1,5,3,2.75,1,2,1.75,2.75,2.25,2.75,0,0,0,1,11000,1900,4.04139268515823
10 +196,Havasupai,+1880,2,1.25,3,3.25,9,3,2.25,1.75,3.25,9,9,0,0,0,225,1881,2.35218251811136
11 +197,Mapuche,+1873,1,5,3,4,2.25,3,3.5,2,3,2,0,0,0,0,110000,1870,5.04139268515823
12 +201,Camaracoto,+1930,1,1,3,3,3,2.75,4,1,4,2,0,0,0,0,250,1939,2.39794000867204
13 +202,Ontong-Java,+1920,1,2.5,2,3,2.25,1.5,2.5,2.75,2.25,1,0,0,0,1,700,1928,2.84509804001426
14 +203,Macha,+1950,1,4,3,3,9,2.25,1.5,1.5,3.5,2.25,9,0,9,0,2350000,1930,6.37106786227174
15 +204,Mangaians,+1820,2,5,3,3,9,2,9,2.25,2.75,9,9,4,0,1,2500,1823,3.39794000867204
16 +205,Slave,+1860,2,5,3,3.5,4,2.5,3,1.5,3.5,9,0,0,0,0,397,1858,2.59879050676312
17 +206,Uveans,+1830,1,1.5,3,1.5,9,1.25,2,2,3,9,9, ,0,1,3000,1837,3.47712125471966
18 +207,Gisu,+1900,2,4.5,3,1,9,1,1.25,9, ,2,9,0,0,0,2000,1920,3.30102999566398
19 +208,Sarsi,+1880,2,1,3,3,4,2.75,2,9, ,1,0,4,0,0,500,1885,2.69897000433602
20 +209,Topotha,+1930,1.5,8,2,2,9,1.25,2,3,2,2,9,0,0,0,34000,1948,4.53147891704226
21 +210,Mataco,+1860,2,5,3,4,4,3,3.75,3,2,9,1,0,0,0,20000,1886,4.30102999566398
22 +211,Caraja,+1950,2,3,3,3,9,2.75,3.5,2,3,1,9,0,0,0,1510,1939,3.17897694729317
23 +212,Wichita,+1860,1,1,3,2.75,9,2,2,1.5,3.5,9,9, ,0,0,500,1950,2.69897000433602
24 +213,Eastern Mono,+1860,2,1.25,3,2.75,9,2,2.25,1.5,3.5,9,9,0,0,0,1000,1885,3
25 +214,Choiseulese,+1900,1,5,3,3.25,3,3,2.25,2,3,1,0,0,0,0,4051,1931,3.60756224318359
26 +215,Seniang,+1930,2,3.25,3,3.75,4,3,2,2,3,9,1,0,0,0,166,1934,2.22010808804006
27 +216,Stalo,+1880,2,1.25,3,4,4,3,3,2,3,1,1,0,0,0,1896,1879,3.27783833300205
28 +217,Katikitegon,+1800,1,1,2,2.5,2,2.25,3,1.25,3.75,1.5,0,0,0,0,40000,1834,4.60205999132796
29 +218,Kasena,+1910,1.5,2.5,3,3.25,1,2,2,2.25,2.75,2.75,0,0,0,0,43930,1921,4.64276120326532
30 +219,Chinook,+1850,2,2.5,3,1,1,1.25,1.5,3.25,1.75,9,0,0,0,0,509,1849,2.70671778233676
31 +220,Kpelle,+1920,2,4.5,3,3.75,2,3,2.5,2,3,3,0, ,0,0,175000,1950,5.24303804868629
32 +221,Keweyipaya,+1870,2,8,2,4,4,9,4,2,3,1,1,0,0,0, , ,
33 +222,Alur,+1890,1,5,3,3,2.5,2.5,9,2.5,2.5,1,0,0,0,0,200000,1890,5.30102999566398
34 +223,Enga,+1950,8,5,3,3.25,4,2.75,2.5,1.75,3.25,2.25,0,0,0,0,100000,1950,5
35 +224,Dilling,+1930,9,1,3, , , , , , , , , ,0,0,8000,1930,3.90308998699194
36 +225,Gosiute,+1860,1,1,2, , , , , , , , , ,0,0,460,1867,2.66275783168157
37 +226,Kamuku,+1920,9, ,2, , , , , , , , , ,0,0,22000,1949,4.34242268082221
38 +227,Ket,+1900,4,1,3, , , , , , , , , ,0,0,1300,1900,3.11394335230684
39 +228,Luapula,+1940,4,1,2, , , , , , , , , ,0,0,100000,1940,5
40 +229,Mesakin,+1940,3,8,3,0,0,0,0,0, ,0,9, ,0,0,6000,1947,3.77815125038364
41 +230,Ngombe,+1900,1,2.75,3,2.5,9,1.75,2.25,2.5,2.5,2.5,9,0,0,0,150000,1940,5.17609125905568
42 +231,Plateau Tong,+1940,4,1,3, , , , , , , , , ,0,0,90000,1948,4.95424250943933
43 +232,Sukuma,+1950,4,1,3, , , , , , , , , ,0,0,1000000,1948,6
44 +233,Tagbanua,+1950,4,1,3, , , , , , , , , ,0,0,7000,1948,3.84509804001426
45 +237,Tarasco,+1500, , , , , , , , , , , , ,0, , , ,
46 +240,Wintu,+1860,2,3.75,3,1.75,1,1.75,2,2.5,2.5,9,0,0,0,0, , ,
47 +241,Vugusu,+1930,3.5,8,3, , , , , , , , , ,0,0,39500,1939,4.59659709562646
48 +242,Chagga,+1890,2,4.75,3,2.5,1.5,1.75,2.25,3,2,1,0,1,0,0,60000,1890,4.77815125038364
49 +243,Tarasco,+1500,1,8,2,1,1,1,1.5,3.75,1.25,9,0,1,0,0,40000,1525,4.60205999132796
50 +244,Chichimec,+1570,1,5,3,0,0,0,0,0, ,0,9,0,0,0,12000,1540,4.07918124604763
51 +245,Dobuans,+1890,4,1,3, , , , , , , , , ,0,0, , ,
52 +246,Lhota Nagas,+1860,1,1,3,2.25,9,2.25,3.5,2,3,3,9,0,0,0,20000,1920,4.30102999566398
53 +247,Lotuko,+1920,1, ,2,2.5,9,3,2.25,1.75,3.25,9,9,1,0,0,3105,1932,3.4920616045126
54 +248,Alkatcho Car,+1865,2,1.25,3,3.5,3.25,2.75,3,2,3,2,0,0,0,0,135,1800,2.13033376849501
55 +249,Lifu Islande,+1910,2,3.25,2,1,1,2,1,4,1,9,0,9,0,1, , ,
56 +250,Miami,+1720,2,4,3,0,0,0,0,0, ,0,9, ,0,0,6000,1718,3.77815125038364
57 +253,Sivokakmiet,+1920,9,8,2, , , , , , , , , ,0,0,550,1917,2.74036268949424
58 +254,Goldi,+1920,9,8,3,0,0,0,0,0, ,0,9, ,0,0,100,1930,2
59 +255,Suri,+1940,2,8,3,2.75,9,1.5,3,2.5,2.5,9,9,0,0,0,3900,1947,3.5910646070265
60 +256,Herero,+1900,1, ,2,3,2.5,2,3,2,3,2,0,0,0,0,25000,1928,4.39794000867204
61 +257,Cahuilla,+1870,1,2.25,3,3,4,9,3.25,1.75,3.25,9,0,0,0,0,750,1920,2.8750612633917
62 +258,Shivwits,+1860,2,1,3,4,4,3,4,1.75,3.25,9,1,0,0,0,300,1873,2.47712125471966
63 +259,Gbari,+1885,1,3.5,3,1.5,9,1.5,2.25,2.75,2.25,9,9,1,0,0,140000,1921,5.14612803567824
64 +261,Lango,+1890,1,4.75,3,3.5,1,2.5,2.75,2.25,2.75,1,0,0,0,0,275000,1947,5.43933269383026
65 +263,Naskapi,+1890,2,1,3,4,4,3,4,1,4,9,1,0,0,0,3910,1857,3.59217675739587
66 +264,Choctaw,+1766,1,2,3,2.75,3.25,2.5,2.5,1.75,3.25,9,0,4,0,0,21500,1764,4.3324384599156
67 +265,Gurage,+1800,3.5,8,3,0,0,0,0,0, ,0,9, ,0,0,350000,1960,5.54406804435028
68 +266,Nyankole,+1850,1,1,3,1.5,1.25,1,2.5,3.75,1.25,9,0,1,1,0,520000,1959,5.7160033436348
69 +267,Shona,+1920,4,1,3,0,0,0,0,0, ,0,9, ,0,0,700000,1931,5.84509804001426
70 +268,Yukaghir,+1900,2,1.25,3,3.25,3.75,3,1.75,1.25,3.75,2,0,0,0,0,1000,1900,3
71 +269,Tahltan,+1870,9, , ,3,9,3,2.75,1.25,3.75,9,9,0,0,0,50,1885,1.69897000433602
72 +270,Tibet,+1920,9, , ,0,0,0,0,0, ,0,9, ,0,0,4000000,1915,6.60205999132796
73 +271,Uncompahgre,+1860,2,1,3,2.5,9,1.5,2.25,1.5,3.5,9,9,1,0,0, , ,
74 +272,Yaruro,+1950,1.5,1,3,4,1,2.5,3,1.25,3.75,9,0,0,0,0,150,1930,2.17609125905568
75 +9,Hadza,1930,4,1,3, , , , , , , , ,0,0,0,750,1960,2.8750612633917
76 +13,Mbuti,1950,9, ,2,4,4,3,3,1,4,1,1,0,0,0, , ,
77 +30,Otoro Nuba,1930,2,4,3,3,3,9,3,4,1,2,0,0,0,0,300000,1930,5.47712125471966
78 +80,Vedda,1860,4,1,3, , , , , , , , ,0,0,0,364,1856,2.56110138364906
79 +90,Tiwi,1929,2,3.5,2,3,4,3,4,3,2,9,0,0,0,0,1062,1928,3.02612451674545
80 +112,Ifugao,1910,1,5,3,4,3,3,4,1,4,9,0,0,0,0,120000,1910,5.07918124604763
81 +124,Copper Esk.,1915,9,1,3,4,4,3,4,1,4,1,1,0,0,0,750,1915,2.8750612633917
82 +134,Yurok,1850,1,3,3,4,9,3,4,9, ,1,9,0,0,0,1052,1852,3.02201573981772
83 +169,Jivaro,1920,1, ,2,4,4,3,4,4,1,1,1,0,0,0,10059,1930,4.00255480814848
84 +170,Amahuaca,1960,1,4.75,2, , , , , , , , ,0,0,0,500,1968,2.69897000433602
85 +180,Aweikoma,1932,9, ,2,4,4,3,4,1,4,1,1,0,0,0,106,1934,2.02530586526477
86 +2,Kung,1950,9,1,3,4,4,3,3,1,4,1,1,0,0,0,433,1964,2.63648789635337
87 +10,Luguru,1925,9,1,3, , , , , , , , ,0,0,0, , ,
88 +11,Kikuyu,1920,3,1,3,3,3,2,3,2,3,2,0,0,0,0,795934,1929,5.90087705690327
89 +23,Tallensi,1934,4,1,3,2,1,2,2,2,3,3,0,1,0,0,29972,1921,4.47671572392606
90 +27,Masa,1910,2,8,3, , , , , , , , ,0,0,0, , ,
91 +32,Mao,1939,9, ,1, , , , , , , , ,0,0,0, , ,
92 +34,Masai,1900,1,4,3,3,3,3,2,2,3,2,0,1,0,0, , ,
93 +39,Kenuzi Nub.,1900,2, ,2, , , , , , , , ,0,0,0,25542,1897,4.40725490056078
94 +40,Teda,1950,4, ,1,3,3,3,3,9, ,1,0,0,0,0,195000,1957,5.29003461136252
95 +52,Lapps,1950,1,1,3,3,4,2,3,3,2,2,0,0,0,0,34000,1945,4.53147891704226
96 +53,Yurak,1894,9,2.5,3, , , , , , , , ,3,0,0,9245,1897,3.96590691549519
97 +67,Lolo,1910,1,4.5,2,4,1,1,1.75,2,3,9,0,0,0,0,1800000,1943,6.25527250510331
98 +72,Lamet,1940,9, ,3,2,9,1,3,3,2,2,9,0,0,0,3806,1940,3.580468783951
99 +74,Rhade,1962,1,2.25,3, , , , , , , , ,0,0,0,115000,1962,5.06069784035361
100 +77,Semang,1925,1,1,3,3,3,3,3,1,4,9,0,0,0,0,1980,1925,3.29666519026153
101 +78,Nicobarese,1870,1,1,3, , , , , , , , ,0,0,1,6310,1901,3.80002935924413
102 +79,Andamanese,1860,1,4,3,4,4,3,3,2,3,9,1,0,0,1,5500,1859,3.74036268949424
103 +85,Iban,1950,4,1,3,3,2,3,3,1,4,1,0,0,0,0,190326,1947,5.27949812031661
104 +86,Badjau,1963,1,1,3, , , , , , , , ,0,0,0,3766,1963,3.57588031568065
105 +91,Aranda,1896,1,8,2,3,3.5,2.5,1.5,2.25,2.75,0,0,0,0,0,2000,1896,3.30102999566398
106 +92,Orokaiva,1925,2,5,3,4,3,3,4,9, ,2,0,0,0,0,9000,1925,3.95424250943932
107 +93,Kimam,1960,9,1,3, , , , , , , , ,0,0,0,7000,1960,3.84509804001426
108 +95,Kwoma,1937,3,1.75,3, , , , , , , , ,0,0,0,898,1936,2.9532763366673
109 +96,Manus,1929,4,1,3,4,3,3,4,9, ,1,0,0,0,0,30000,1928,4.47712125471966
110 +97,New Ireland,1930,4,1,3, , , , , , , , ,0,0,0,7096,1928,3.85101360682367
111 +99,Siuai,1939,3,2.5,3, , , , , , , , ,0,0,0,35000,1938,4.54406804435028
112 +101,Pentecost,1953,4,1,2, , , , , , , , ,0,0,0,400,1953,2.60205999132796
113 +109,Trukese,1947,4,1,3, , , , , , , , ,0,0,1,9185,1946,3.96307916064183
114 +118,Ainu,1880,3,2,3,2,2,2,1,2,3,3,0,0,0,0,17198,1882,4.23547794461295
115 +119,Gilyak,1890,2,3.75,2,4,4,3,4,2,3,1,1,0,0,0,4500,1890,3.65321251377534
116 +120,Yukaghir,1850,1,1.25,3, , , , , , , , ,0,0,0,707,1850,2.8494194137969
117 +121,Chukchee,1900,9,4.5,2, , , , , , , , ,0,0,0,12000,1900,4.07918124604763
118 +122,Ingalik,1885,1,1.75,3,4,4,3,4,1,4,3,1,0,0,0,451,1880,2.65417654187796
119 +125,Montagnais,1910,9,1,3, , , , , , , , ,0,0,0,75,1921,1.8750612633917
120 +126,Micmac,1650,1,1,3,3.5,3,2,2.75,2,3,9,0,0,0,0,3000,1615,3.47712125471966
121 +127,Saulteaux,1930,4,1,3,4,4,3,4,2,3,1,1,0,0,0,20000,1930,4.30102999566398
122 +128,Slave,1940,4,1,3,4,4,3,4,1,4,9,1,0,0,0,1386,1941,3.14176323027579
123 +129,Kaska,1900,9,1,3, , , , , , , , ,0,0,0,350,1900,2.54406804435028
124 +131,Haida,1875,9, ,1, , , , , , , , ,0,0,0,800,1885,2.90308998699194
125 +132,Bellacoola,1880,1,2.25,3,3,3,3,3,2,3,1,0,0,0,0,300,1922,2.47712125471966
126 +133,Twana,1860,2,1.5,3, , , , , , , , ,0,0,0,290,1858,2.46239799789896
127 +135,E. Pomo,1850,1,2.25,3,3,1,3,2.5,1.25,3.75,3,0,0,0,0,8000,1850,3.90308998699194
128 +136,Yokuts,1850,1, ,2,2,3,1,2,3,2,9,0,1,0,0,2436,1859,3.38667728396084
129 +137,Paiute,1870,1,1,3,4,4,3,3.5,1.5,3.5,1,1,0,0,0,200,1872,2.30102999566398
130 +138,Klamath,1860,1,4,3,9,1,9,4,9, ,9,9,0,0,0,676,1881,2.82994669594164
131 +139,Kutenai,1890,1,1,3,1,1.5,1,1.5,4,1,2.25,0,0,0,0,1000,1892,3
132 +141,Hidatsa,1836,2,1,3,3,3,2.5,1.75,1.75,3.25,1.5,0,0,0,0,400,1837,2.60205999132796
133 +147,Comanche,1870,1,2,2,3,3,3,2,2,3,1,0,0,0,0,15000,1870,4.17609125905568
134 +149,Zuni,1880,9,1,3, , , , , , , , ,0,0,0,1650,1884,3.21748394421391
135 +150,Havasupai,1918,4,1,3,4,4,3,4,2,3,9,1,0,0,0,177,1919,2.24797326636181
136 +151,Papago,1910,9,1,3,3,4,3,1,2,3,3,0,0,0,0,9942,1890,3.99747375880298
137 +152,Huichol,1890,4, ,2, , , , , , , , ,0,0,0,4000,1895,3.60205999132796
138 +157,Bribri,1917,9,1,3, , , , , , , , ,0,0,0, , ,
139 +161,Callinago,1650,1,8,3, , , , , , , , ,0,0,0,4500,1647,3.65321251377534
140 +162,Warrau,1935,1,1,3,9,9,1,3,4,1,9,9,1,0,0,8000,1941,3.90308998699194
141 +163,Yanomamo,1965,1,5,3,4,3.5,3,2.75,2,3,1,0,0,0,0,10000,1964,4
142 +164,Carib,1932,4,1,3,3,3,3,4,2,3,1,0,0,0,0,600,1932,2.77815125038364
143 +166,Mundurucu,1850,1, ,1,3,3,3,2,2,3,1,0,0,0,0,1250,1952,3.09691001300806
144 +167,Cubeo,1939,2,3.5,3, , , , , , , , ,0,0,0,2500,1939,3.39794000867204
145 +168,Cayapa,1908,1,1,3,2,3,1,4,4,1,2,0,0,0,0,2500,1900,3.39794000867204
146 +173,Siriono,1942,1,1,3,4,3,3,4,9, ,2.75,0,0,0,0,2000,1950,3.30102999566398
147 +174,Nambicuara,1940,2,5,3,2,3,2,1,3,2,1,0,0,0,0,2500,1948,3.39794000867204
148 +175,Trumai,1938,2, ,3, , , , , , , , ,0,0,0,43,1938,1.63346845557959
149 +176,Timbira,1915,3,1,2,4,3,2,3,2,3,9,0,0,0,0, , ,
150 +178,Botocudo,1884,9,4.25,3, , , , , , , , ,0,0,0,13000,1883,4.11394335230684
151 +179,Shavante,1958,2,4,3,3,4,3,1,2,3,1,0,0,0,0,2000,1958,3.30102999566398
152 +181,Cayua,1890,4, ,1, , , , , , , , ,0,0,0,3000,1945,3.47712125471966
153 +182,Lengua,1889,1,1,2, , , , , , , , ,0,0,0, , ,
154 +183,Abipon,1750,1,4,3,4,3,3,4,9, ,1,0,0,0,0, , ,
155 +185,Tehuelche,1870,2,3,3,4,3.5,3,4,9, ,1,0,0,0,0,1400,1870,3.14612803567824
156 +186,Yahgan,1865,1,2.75,2,4,4,3,4,1,4,9,1,0,0,0,3000,1867,3.47712125471966
157 +1,Nama,1860,1,5,3,3,1.5,2.5,1.75,2.5,2.5,9,0,4,0,0,2500,1876,3.39794000867204
158 +14,Nkundo Mongo,1930,2,3.5,3, , , , , , , , ,0,0,0,1000000,1930,6
159 +15,Banen,1935,9, ,1, , , , , , , , ,1,0,0, , ,
160 +16,Tiv,1920,1,5,3,3,3,2,1,2,3,1,0,0,0,0,350000,1922,5.54406804435028
161 +17,Ibo,1935,2,3.75,3,3.5,3,2.5,1.5,1,4,9,0,0,0,0,3000000,1934,6.47712125471966
162 +20,Mende,1945,9,1.5,3,3,9,2,1,1,4,9,9,4,0,0,750000,1945,5.8750612633917
163 +22,Bambara,1902,4,8,3,2,1,1,1,2,3,2,0,1,0,0, , ,
164 +24,Songhai,1940,9,1,3, , , , , , , , ,0,0,0,3500,1940,3.54406804435028
165 +25,Past. Fulani,1951,9,2.5,2, , , , , , , , ,1,0,0, , ,
166 +31,Shilluk,1910,2,3.5,3,1,9,1,3,3,2,9,9,1,0,0,60000,1910,4.77815125038364
167 +35,Konso,1935,4, ,2, , , , , , , , ,3,0,0,1100,1948,3.04139268515822
168 +36,Somali,1900,1,5,2,4,4,3,1,2,3,2,1,0,0,0,50000,1880,4.69897000433602
169 +38,Bogo,1855,9, ,1, , , , , , , , ,0,0,0, , ,
170 +46,Rwala,1913,2,5,3,2,1,1,2,3,2,1,0,1,0,0,35000,1913,4.54406804435028
171 +55,Abkhaz,1880,2,5,3, , , , , , , , ,0,0,0,72103,1897,4.85795333484898
172 +60,Gond,1930,4,1,3,3,2,2,2,2,3,3,0,4,0,0,3063753,1931,6.48625374951768
173 +61,Toda,1900,1,1,3, , , , , , , , ,4,0,0,805,1901,2.90579588036787
174 +64,Burusho,1934,4,1,3,1,1,1,3,4,1,3,0,1,0,0,20813,1931,4.31833468422614
175 +68,Lepcha,1937,1,1,3,3,2,2,3,3,2,3,0,1,0,0,25780,1931,4.41128291301738
176 +70,Lakher,1930,3,1.75,3,2,9,1,1,4,1,3,9,0,0,0,10000,1921,4
177 +81,Tanala,1925,3,3,3, , , , , , , , ,1,0,0, , ,
178 +87,Toradja,1910,1,4,3,3,3,3,1,2,3,2,0,0,0,0,30000,1930,4.47712125471966
179 +94,Kapauku,1955,1,4.5,3,2,3,1,3,4,1,9,0,1,0,0,52500,1954,4.72015930340596
180 +98,Trobrianders,1914,4,1,3,2,3,2,2,2,3,9,0,0,0,1,8780,1921,3.9434945159061
181 +100,Tikopia,1930,4,1,3,3,1,1,1,3,2,3,0,1,0,1,1278,1929,3.10653085382238
182 +103,Ajie,1845,9, ,1, , , , , , , , ,4,0,0, , ,
183 +104,Maori,1820,1,4.5,3,2,3,2,2,2,3,9,0,0,0,1,37520,1871,4.57426282970703
184 +105,Marquesans,1800,1,5,2, , , , , , , , ,0,0,1,50000,1804,4.69897000433602
185 +107,Gilbertese,1890,1,8,2, , , , , , , , ,1,0,1,1945,1905,3.28891960566173
186 +108,Marshallese,1900,4,1,2,1,1,1,2,4,1,3,0,1,0,1,11300,1886,4.05307844348342
187 +110,Yapese,1910,9,1.25,2,3,1,2,2,2,3,9,0,1,0,1,5790,1915,3.76267856372744
188 +113,Atayal,1930,2,5,3, , , , , , , , ,0,0,0,32925,1930,4.51752578363382
189 +115,Manchu,1915,2,5,3,1,0,1,1.5,3.5,1.5,9,0,0,0,0,19639671,1916,7.29313420829404
190 +123,Aleut,1778,1,5,3,3,2,2,2,2.5,2.5,2.5,0,1,0,1,13500,1750,4.13033376849501
191 +130,Eyak,1890,1,1,3,3,3,2,9,3,2,3,0,1,0,0,154,1890,2.18752072083646
192 +140,Gros Ventre,1880,1,1,3,3,3,2,2,3,2,9,0,0,0,0,1400,1875,3.14612803567824
193 +142,Pawnee,1867,1,1,3,3,9,3,3,3,2,3,9,0,0,0,3414,1861,3.53326351677871
194 +143,Omaha,1860,1,3.5,2,1,1,1,1.25,3.75,1.25,3,0,0,0,0,1076,1876,3.03181227133037
195 +148,Chiricahua,1870,1,1,2,3,3,3,3,1,4,2,0,1,0,0, , ,
196 +154,Popoluca,1940,9, ,1, , , , , , , , ,5,0,0,6779,1930,3.83116563390944
197 +155,Quiche,1930,9,1,3, , , , , , , , ,5,0,0,24408,1952,4.38753219463435
198 +156,Miskito,1921,9, ,2,9,9,9,9,2,3,9,9,0,0,0,15000,1932,4.17609125905568
199 +158,Cuna,1927,1,1.25,3,3,2,2,2,1,4,2,0,3,0,0,22155,1927,4.34547175436763
200 +159,Goajiro,1947,1,3.25,3,9,3,3,3,4,1,1,9,1,0,0,18000,1948,4.25527250510331
201 +172,Aymara,1940,6,1.5,3,2,9,1,1,3,2,9,9,0,0,0,600000,1935,5.77815125038364
202 +177,Tupinamba,1550,1,5,3,9,3.5,3,4,9, ,9,9,0,0,0,27000,1600,4.43136376415899
203 +184,Mapuche,1950,4,1,3,3,2,3,3,2,3,1,0,5,0,0,200000,1950,5.30102999566398
204 +3,Thonga,1895,9, ,2, , , , , , , , ,1,1,0, , ,
205 +5,Mbundu,1890,1,2,3,2.5,0,1.75,2,2.5,2.5,2,0,1,1,0, , ,
206 +8,Nyakyusa,1934,4,1,3,3,2,2,2,3,2,1,0,1,1,0,84000,1931,4.92427928606188
207 +21,Wolof,1950,4,1,3, , , , , , , , ,1,1,0,30000,1949,4.47712125471966
208 +28,Azande,1905,2,5,3,2,3,3,1,4,1,2,0,1,1,0,75000,1907,4.8750612633917
209 +41,Tuareg,1900,2,5,2, , , , , , , , ,1,1,0, , ,
210 +42,Riffians,1926,2,5,3,3,3,2,1,3,2,1,0, ,1,0, , ,
211 +44,Hebrews,-621,2,2.5,2, , , , , , , , ,1,1,0,12500,-621,4.09691001300806
212 +48,Gheg Alban.,1910,1,4.5,3,3,1,2,1,2,3,2,0,4,1,0,814485,1927,5.91088309051412
213 +50,Basques,1940,6,1,3, , , , , , , , , ,1,0, , ,
214 +51,Irish,1955,1,1,2,3,4,3,4,4,1,1,0,4,1,0, , ,
215 +57,Kurd,1951,3,2.5,3,1,1,2,2,2,3,1,0,4,1,0,3000000,1950,6.47712125471966
216 +58,Basseri,1958,9,8,3,3,2,3,3,2,3,1,0,1,1,0, , ,
217 +62,Santal,1940,4,1,3,3,9,2,1,3,2,2,9,4,1,0,2902266,1941,6.4627372141107
218 +65,Kazak,1885,2,4,3,2,3,2,2,3,2,2,0,0,1,0,4000000,1897,6.60205999132796
219 +69,Garo,1955,4,1,3, , , , , , , , ,5,1,0,300000,1955,5.47712125471966
220 +82,NegriSembil.,1958,2,3.25,2,3,9,2,3,3,2,1,9,5,1,0,72154,1947,4.85826041207227
221 +84,Balinese,1958,2,5,3,3,2,2,1,2,3,9,0,0,1,0,1500000,1954,6.17609125905568
222 +88,Tobelorese,1900,9, ,1, , , , , , , , ,0,1,0, , ,
223 +89,Alorese,1938,4,1,3, , , , , , , , ,1,1,0,70000,1938,4.84509804001426
224 +102,Mbau Fijians,1840,1,5,3,2,9,1,1,3,2,1,9,1,1,0,150000,1840,5.17609125905568
225 +106,W. Samoans,1829,1,4.5,3,2,2,2,1,2,3,2,0,4,1,1,44502,1922,4.64837952939544
226 +111,Palauans,1873,1,5,3,3,2,1.5,1.25,3,2,9,0,4,1,1,6578,1951,3.81809386914664
227 +144,Huron,1634,2,1.75,3,3,2,3,1,2,3,2,0,4,1,0,21000,1633,4.32221929473392
228 +145,Creek,1800,2,2,2,3,2,1.75,1.5,2.75,2.25,2,0,0,1,0, , ,
229 +146,Natchez,1718,1,1.25,3, , , , , , , , ,1,1,0,3500,1700,3.54406804435028
230 +153,Aztec,1520,1,4.5,3,2,2,1,1,4,1,9,0,1,1,0,300000,1520,5.47712125471966
231 +165,Saramacca,1928,3,2,3, , , , , , , , ,1,1,0,14000,1930,4.14612803567824
232 +4,Lozi,1900,1,3.5,2,2,2,1,3,3,2,1,0,4,1,0, , ,
233 +6,Suku,1920,1,2.75,2,3,3,2,3,3,2,2,0,1,1,0, , ,
234 +7,Bemba,1897,1,5,1, , , , , , , , ,1,1,0, , ,
235 +12,Ganda,1875,1,4.5,2,1,2,1,1,4,1,9,0,1,1,0,750000,1878,5.8750612633917
236 +18,Fon,1890,1,1.5,3,3,2,1,1,4,1,9,0,1,1,0, , ,
237 +19,Ashanti,1895,1,1,3, , , , , , , , ,4,1,0,406193,1921,5.60873243485518
238 +26,Hausa,1900,2,4.5,3,2,2,1,1,4,1,2,0,1,1,0, , ,
239 +29,Fur,1880,1,8,2, , , , , , , , ,1,1,0, , ,
240 +33,Kaffa,1905,2,8,3, , , , , , , , ,1,1,0, , ,
241 +37,Amhara,1953,2,8,3,2,2,1,1,4,1,9,0,1,1,0, , ,
242 +43,Egyptians,1950,2,2,3,2,2,1,2,3,2,3,0,4,1,0,15932694,1937,7.2022892152496
243 +45,Babylonians,-1750,2,8,2, , , , , , , , ,1,1,0, , ,
244 +47,Turks,1950,1,1,3,4,2,2,3,1.25,3.75,9,0,5,1,0,20934670,1950,7.32086611935629
245 +49,Romans,110,2,1,2, , , , , , , , ,1,1,0,1200000,117,6.07918124604763
246 +54,Russians,1955,1,5,3, , , , , , , , ,3,1,0,111000000,1950,8.04532297878666
247 +56,Armenians,1843,9,8,3, , , , , , , , ,1,1,0,300000,1854,5.47712125471966
248 +59,Punjabi,1950,2,3.25,3,1.5,1,1,2.5,3.25,1.75,2.25,0,4.5,1,0,76450000,1951,7.88337748974834
249 +63,Uttar Prad.,1945,6,1.5,3, , , , , , , , ,4,1,0,1400,1941,3.14612803567824
250 +66,Khalka Mong.,1920,2,3,2, , , , , , , , ,4,1,0,492000,1918,5.69196510276736
251 +71,Burmese,1960,2,5,2, , , , , , , , ,4.5,1,0, , ,
252 +73,Vietnamese,1930,2,5,3,2,9,1,1,3,2,9,9,4,1,0,8096000,1931,6.90827049949572
253 +75,Khmer,1292,1,2,2, , , , , , , , ,1,1,0,5000000, ,6.69897000433602
254 +76,Siamese,1955,1, ,1, , , , , , , , , ,1,0,17442689,1947,7.24161343746814
255 +83,Javanese,1955,2,5,2, , , , , , , , ,0,1,0,248625,1953,5.39554479613249
256 +114,Chinese,1936,2,4.5,3,2.75,3,2,1.5,2,3,1.5,0,1,1,0,430000000,1933,8.63346845557959
257 +116,Koreans,1947,1,5,3,2,1,1,2,3,2,3,0,1,1,0,24326327,1940,7.38607654033025
258 +117,Japanese,1950,1,1,3,3,2,2,1.75,1.5,3.5,2,0,5,1,0,83199637,1950,7.92012143146812
259 +160,Haitians,1935,9, ,2, , , , , , , , ,1,1,0, , ,
260 +171,Inca,1530,1,5,2, , , , , , , , ,1,1,0,1500000,1571,6.17609125905568
261 +
Ember_et_al_Worldwide_PolPart_Codes_JACPR2017_SHort.sav
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Factors_revised_2020.xlsx
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Factors_revised_Oct20.xlsx
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IBSS_indices_final.sps
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1 +* Encoding: UTF-8.
2 +FILTER OFF.
3 +USE ALL.
4 +EXECUTE.
5 +
6 +DESCRIPTIVES VARIABLES=PE_15 PE_16 PE_17 PE_18 PE_19 TL_5 TL_6 TL_15 TL_19 TL_20 TL_21
7 + /SAVE
8 + /STATISTICS=MEAN STDDEV MIN MAX.
9 +
10 +COMPUTE IN_1=MEAN(ZPE_15, ZPE_16,ZPE_17,ZPE_18,ZPE_19).
11 +VARIABLE LABELS IN_1 'Corporate-Exclusionary Index'.
12 +EXECUTE.
13 +RELIABILITY
14 + /VARIABLES=ZPE_15 ZPE_16 ZPE_17 ZPE_18 ZPE_19
15 + /SCALE('Corporate-Exclusionary Index') ALL
16 + /MODEL=ALPHA
17 + /SUMMARY=TOTAL.
18 +EXECUTE.
19 +
20 +COMPUTE IN_2b=MEAN(ZTL_5,ZTL_6,ZTL_15,ZTL_19,ZTL_20,ZTL_21).
21 +VARIABLE LABELS IN_2b 'Looseness-Tightness Index'.
22 +EXECUTE.
23 +RELIABILITY
24 + /VARIABLES=ZTL_5 ZTL_6 ZTL_15 ZTL_19 ZTL_20 ZTL_21
25 + /SCALE('Looseness-Tightness Index') ALL
26 + /MODEL=ALPHA
27 + /SUMMARY=TOTAL.
28 +EXECUTE.
29 +
30 +FACTOR
31 + /VARIABLES PE_15 PE_16 PE_17 PE_18 PE_19 TL_5 TL_6 TL_15 TL_19 TL_20 TL_21
32 + /MISSING LISTWISE
33 + /ANALYSIS PE_15 PE_16 PE_17 PE_18 PE_19 TL_5 TL_6 TL_15 TL_19 TL_20 TL_21
34 + /PRINT UNIVARIATE INITIAL EXTRACTION ROTATION
35 + /CRITERIA MINEIGEN(1) ITERATE(25)
36 + /EXTRACTION PC
37 + /CRITERIA ITERATE(25)
38 + /ROTATION VARIMAX
39 + /METHOD=CORRELATION.
40 +EXECUTE.
41 +
42 +FACTOR
43 + /VARIABLES PE_15 PE_16 PE_17 PE_18 PE_19
44 + /MISSING LISTWISE
45 + /ANALYSIS PE_15 PE_16 PE_17 PE_18 PE_19
46 + /PRINT UNIVARIATE INITIAL EXTRACTION ROTATION
47 + /CRITERIA MINEIGEN(1) ITERATE(25)
48 + /EXTRACTION PC
49 + /CRITERIA ITERATE(25)
50 + /ROTATION VARIMAX
51 + /METHOD=CORRELATION.
52 +EXECUTE.
53 +
54 +FACTOR
55 + /VARIABLES TL_5 TL_6 TL_15 TL_19 TL_20 TL_21
56 + /MISSING LISTWISE
57 + /ANALYSIS TL_5 TL_6 TL_15 TL_19 TL_20 TL_21
58 + /PRINT UNIVARIATE INITIAL EXTRACTION ROTATION
59 + /CRITERIA MINEIGEN(1) ITERATE(25)
60 + /EXTRACTION PC
61 + /CRITERIA ITERATE(25)
62 + /ROTATION VARIMAX
63 + /METHOD=CORRELATION.
64 +EXECUTE.
65 +
OurBetterNature_ReadmeForDataFile.pdf
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Ranalysis_StressReligionSharing2020-1.R
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1 +#############################################################
2 +####Religion and Resource Stress -- Analysis Script 01-2020####
3 +#############################################################
4 +
5 +library(Hmisc)
6 +library(lme4)
7 +library(lmerTest)
8 +library(ggplot2)
9 +library(ggthemes)
10 +library(phia) #also loads car package
11 +library(plyr)
12 +library(lm.beta)
13 +lm.beta.lmer <- function(mod) { b <- fixef(mod)[-1]; sd.x <- apply(matrix(getME(mod,"X")[,-1]),2,sd); sd.y <- sd(getME(mod,"y")); b*sd.x/sd.y; }
14 +
15 +#G = High gods
16 +#SG = Superior gods
17 +#MS = minor spirits
18 +#Gor_SG = broader supernatural agents
19 +
20 +#re-naming data files to shorter names (arbitrary-just for easier typing in R)
21 +mor<-read.csv("DT-MoralHighGods_Long_EP.csv")
22 +ang<-read.csv("DT-GodsAndResourceStress_Long.csv")
23 +
24 +
25 +#####################################
26 +##Analyses on Newly Coded Variables##
27 +#####################################
28 +
29 +##How many overlapping language families are there?
30 +table(ang$language_family)
31 +
32 +##Dummy-coding language families
33 +ang$Afroasiatic<-ifelse(as.character(ang$language_family)=="Afro-Asiatic",1,0)
34 +ang$Afroasiatic<-ifelse(is.na(ang$Afroasiatic)==T,0,ang$Afroasiatic)
35 +
36 +ang$Austronesian<-ifelse(as.character(ang$language_family)=="Austronesian",1,0)
37 +ang$Austronesian<-ifelse(is.na(ang$Austronesian)==T,0,ang$Austronesian)
38 +
39 +ang$AtlanticCongo<-ifelse(as.character(ang$language_family)=="Atlantic-Congo",1,0)
40 +ang$AtlanticCongo<-ifelse(is.na(ang$AtlanticCongo)==T,0,ang$AtlanticCongo)
41 +
42 +ang$Indoeuropean<-ifelse(as.character(ang$language_family)=="Indo-European",1,0)
43 +ang$Indoeuropean<-ifelse(is.na(ang$Indoeuropean)==T,0,ang$Indoeuropean)
44 +
45 +ang$Austroasiatic<-ifelse(as.character(ang$language_family)=="Austroasiatic",1,0)
46 +ang$Austroasiatic<-ifelse(is.na(ang$Austroasiatic)==T,0,ang$Austroasiatic)
47 +
48 +ang$NuclearTransNewGuinea<-ifelse(as.character(ang$language_family)=="Nuclear Trans New Guinea",1,0)
49 +ang$NuclearTransNewGuinea<-ifelse(is.na(ang$NuclearTransNewGuinea)==T,0,ang$NuclearTransNewGuinea)
50 +
51 +ang$SinoTibetan<-ifelse(as.character(ang$language_family)=="Sino-Tibetan",1,0)
52 +ang$SinoTibetan<-ifelse(is.na(ang$SinoTibetan)==T,0,ang$SinoTibetan)
53 +
54 +ang$Turkic<-ifelse(as.character(ang$language_family)=="Turkic",1,0)
55 +ang$Turkic<-ifelse(is.na(ang$Turkic)==T,0,ang$Turkic)
56 +
57 +ang$Uralic<-ifelse(as.character(ang$language_family)=="Uralic",1,0)
58 +ang$Uralic<-ifelse(is.na(ang$Uralic)==T,0,ang$Uralic)
59 +
60 +
61 +##Dummy variables for separate stressors
62 +#Famine (re-coded during restructuring as 1 in variable "ResourceStress")
63 +ang$famine<-ifelse(as.character(ang$ResourceStress)=="1",1,0)
64 +#Natural Hazards (re-coded during restructuring as 2 in variable "ResourceStress")
65 +ang$naturalhazards<-ifelse(as.character(ang$ResourceStress)=="2",1,0)
66 +#Chronic Scarcity (re-coded during restructuring as 3 in variable "ResourceStress")
67 +ang$chron_scarcity<-ifelse(as.character(ang$ResourceStress)=="3",1,0)
68 +#Abundance (re-coded during restructuring as 4 in variable "ResourceStress")
69 +ang$abundance<-ifelse(as.character(ang$ResourceStress)=="4",1,0)
70 +
71 +#Recoding resource stress
72 +ang$stress2<-ifelse(ang$abundance==1,(0-ang$Stress),
73 + ifelse(ang$abundance==0,ang$Stress,
74 + NA))
75 +
76 +#Dichotomized stress variable (primary analyses do not use this variable)
77 +ang$stress3<-ifelse(ang$chron_scarcity==1&ang$stress2<(-.11),(-1),
78 + ifelse(ang$chron_scarcity==1&ang$stress2>(-.11),1,
79 + ifelse(ang$famine==1&ang$stress2<(-.11),(-1),
80 + ifelse(ang$famine==1&ang$stress2>(-.11),1,
81 + ang$stress2))))
82 +
83 +
84 +ang_fam<-ang[ang$famine==1,]
85 +ang_naturalhazards<-ang[ang$naturalhazards==1,]
86 +ang_abundance<-ang[ang$abundance==1,]
87 +ang_chron_scarcity<-ang[ang$chron_scarcity==1,]
88 +ang_hurthelp<-ang[is.na(ang$stress2)==F&is.na(ang$G3_Help)==F&is.na(ang$G2_Harm)==F,]
89 +
90 +##Creating datasets for each of the god variables (this will allow us to calculate R2 later)
91 +ang2<-ang[is.na(ang$G1_Associated)==F,]
92 +ang3<-ang[is.na(ang$G2_Harm)==F,]
93 +ang4<-ang[is.na(ang$G3_Help)==F,]
94 +ang5<-ang[is.na(ang$G4_Punitive)==F,]
95 +ang6<-ang[is.na(ang$SG1_Associated)==F,]
96 +ang7<-ang[is.na(ang$SG2_Harm)==F,]
97 +ang8<-ang[is.na(ang$SG3_Help)==F,]
98 +ang9<-ang[is.na(ang$SG4_Punitive)==F,]
99 +ang10<-ang[is.na(ang$MS1_Associated)==F,]
100 +ang11<-ang[is.na(ang$MS2_Harm)==F,]
101 +ang12<-ang[is.na(ang$MS3_Help)==F,]
102 +ang13<-ang[is.na(ang$MS4_Punitive)==F,]
103 +
104 +#Empty model controlling for language family (anova) (this will allow us to calculate R2 later)
105 +summary(lmer(stress2~(1|SCCS_ID),data=ang))
106 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
107 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang2))
108 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang3))
109 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang4))
110 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang5))
111 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang_hurthelp))
112 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+SinoTibetan+Uralic+(1|SCCS_ID),data=ang6))
113 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang7))
114 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+SinoTibetan+(1|SCCS_ID),data=ang8))
115 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang9))
116 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Turkic+NuclearTransNewGuinea+Austroasiatic+SinoTibetan+(1|SCCS_ID),data=ang10))
117 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang11))
118 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang12))
119 +summary(lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang13))
120 +
121 +#################################################################
122 +###PART A: Central Analyses on Stressors and Religious Beliefs###
123 +#################################################################
124 +
125 +##For the analyses below, you can get the R squared by comparing...
126 +#...the variance explained at the society level with the variance explained by language family alone
127 +
128 +#Resource Stress and Gods Associated with Weather# Table 2, Model 1
129 +summary(model1<-lmer(stress2~G1_Associated+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
130 +lm.beta.lmer(model1)
131 +
132 +##Secondary analyses looking at specific types of resource stress# Table S4, Model S1
133 +#looking at chronic scarcity
134 +summary(model1b<-lmer(stress2~G1_Associated*famine+G1_Associated*naturalhazards+G1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
135 +#looking at natural hazards
136 +summary(model1c<-lmer(stress2~G1_Associated*famine+G1_Associated*chron_scarcity+G1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
137 +#Looking at abundance
138 +summary(model1d<-lmer(stress2~G1_Associated*famine+G1_Associated*naturalhazards+G1_Associated*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
139 +#Looking at famine
140 +summary(model1e<-lmer(stress2~G1_Associated*chron_scarcity+G1_Associated*naturalhazards+G1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
141 +
142 +#Resource Stress and Gods that Harm with Weather#
143 +summary(model2<-lmer(stress2~G2_Harm+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
144 +lm.beta.lmer(model2)
145 +
146 +##Secondary analyses looking at specific types of resource stress # Table S4, Model S2
147 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
148 +summary(model2b<-lmer(stress2~G2_Harm*famine+G2_Harm*naturalhazards+G2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
149 +summary(model2c<-lmer(stress2~G2_Harm*famine+G2_Harm*chron_scarcity+G2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
150 +summary(model2d<-lmer(stress2~G2_Harm*famine+G2_Harm*naturalhazards+G2_Harm*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
151 +summary(model2e<-lmer(stress2~G2_Harm*chron_scarcity+G2_Harm*naturalhazards+G2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
152 +
153 +#Resource Stress and Gods that Help with Weather# Table 2, Model 3
154 +summary(model3<-lmer(stress2~G3_Help+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
155 +lm.beta.lmer(model3)
156 +
157 +##Secondary analyses looking at specific types of resource stress# Table S4, Model S3
158 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
159 +summary(model3b<-lmer(stress2~G3_Help*famine+G3_Help*naturalhazards+G3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
160 +summary(model3c<-lmer(stress2~G3_Help*famine+G3_Help*chron_scarcity+G3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
161 +summary(model3d<-lmer(stress2~G3_Help*famine+G3_Help*naturalhazards+G3_Help*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
162 +summary(model3e<-lmer(stress2~G3_Help*chron_scarcity+G3_Help*naturalhazards+G3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
163 +
164 +#Resource Stress and Gods that Punish with Weather# Table 2, Model 4
165 +summary(model4<-lmer(stress2~G4_Punitive+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
166 +lm.beta.lmer(model4)
167 +
168 +##Secondary analyses looking at specific types of resource stress# Table S4, Model S4
169 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
170 +summary(model4b<-lmer(stress2~G4_Punitive*famine+G4_Punitive*naturalhazards+G4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
171 +summary(model4c<-lmer(stress2~G4_Punitive*famine+G4_Punitive*chron_scarcity+G4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
172 +summary(model4d<-lmer(stress2~G4_Punitive*famine+G4_Punitive*naturalhazards+G4_Punitive*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
173 +summary(model4e<-lmer(stress2~G4_Punitive*chron_scarcity+G4_Punitive*naturalhazards+G4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
174 +
175 +#Modeling Helping and Harming Together# Table 2, Model 5
176 +summary(model5<-lmer(stress2~G3_Help+G2_Harm+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang_hurthelp))
177 +vif(model5) ##Look at Multicollinearity, since the predictors are highly correlated
178 +
179 +#Resource Stress and Superior Gods Associated With Weather# Table 3, Model 6
180 +summary(model6<-lmer(stress2~SG1_Associated+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+SinoTibetan+Uralic+(1|SCCS_ID),data=ang))
181 +
182 +##Secondary analyses looking at specific types of resource stress# Table S5, Model S5
183 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
184 +summary(model6b<-lmer(stress2~SG1_Associated*famine+SG1_Associated*naturalhazards+SG1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Indoeuropean+NuclearTransNewGuinea+SinoTibetan+Uralic+(1|SCCS_ID),data=ang))
185 +summary(model6c<-lmer(stress2~SG1_Associated*famine+SG1_Associated*chron_scarcity+SG1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Indoeuropean+NuclearTransNewGuinea+SinoTibetan+Uralic+(1|SCCS_ID),data=ang))
186 +summary(model6d<-lmer(stress2~SG1_Associated*famine+SG1_Associated*naturalhazards+SG1_Associated*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Indoeuropean+NuclearTransNewGuinea+SinoTibetan+Uralic+(1|SCCS_ID),data=ang))
187 +summary(model6e<-lmer(stress2~SG1_Associated*chron_scarcity+SG1_Associated*naturalhazards+SG1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Indoeuropean+NuclearTransNewGuinea+SinoTibetan+Uralic+(1|SCCS_ID),data=ang))
188 +
189 +#Resource Stress and Superior Gods that Harm With Weather# Table 3, Model 7
190 +summary(model7<-lmer(stress2~SG2_Harm+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
191 +
192 +##Secondary analyses looking at specific types of resource stress# Table S5, Model S6
193 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
194 +summary(model7b<-lmer(stress2~SG2_Harm*famine+SG2_Harm*naturalhazards+SG2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
195 +summary(model7c<-lmer(stress2~SG2_Harm*famine+SG2_Harm*chron_scarcity+SG2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
196 +summary(model7d<-lmer(stress2~SG2_Harm*famine+SG2_Harm*naturalhazards+SG2_Harm*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
197 +summary(model7e<-lmer(stress2~SG2_Harm*chron_scarcity+SG2_Harm*naturalhazards+SG2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=ang))
198 +
199 +#Resource Stress and Superior Gods that Help With Weather# Table 3, Model 8
200 +summary(model8<-lmer(stress2~SG3_Help+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+SinoTibetan+(1|SCCS_ID),data=ang))
201 +
202 +##Secondary analyses looking at specific types of resource stress# Table S5, Model S7
203 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
204 +summary(model8b<-lmer(stress2~SG3_Help*famine+SG3_Help*naturalhazards+SG3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+SinoTibetan+(1|SCCS_ID),data=ang))
205 +summary(model8c<-lmer(stress2~SG3_Help*famine+SG3_Help*chron_scarcity+SG3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+SinoTibetan+(1|SCCS_ID),data=ang))
206 +summary(model8d<-lmer(stress2~SG3_Help*famine+SG3_Help*naturalhazards+SG3_Help*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+SinoTibetan+(1|SCCS_ID),data=ang))
207 +summary(model8e<-lmer(stress2~SG3_Help*chron_scarcity+SG3_Help*naturalhazards+SG3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+SinoTibetan+(1|SCCS_ID),data=ang))
208 +
209 +#Resource Stress and Superior Gods that Punish With Weather# Table 3, Model 9
210 +summary(model9<-lmer(stress2~SG4_Punitive+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
211 +
212 +##Secondary analyses looking at specific types of resource stress# Table S5, Model S8
213 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
214 +summary(model9b<-lmer(stress2~SG4_Punitive*famine+SG4_Punitive*naturalhazards+SG4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
215 +summary(model9c<-lmer(stress2~SG4_Punitive*famine+SG4_Punitive*chron_scarcity+SG4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
216 +summary(model9d<-lmer(stress2~SG4_Punitive*famine+SG4_Punitive*naturalhazards+SG4_Punitive*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
217 +summary(model9e<-lmer(stress2~SG4_Punitive*chron_scarcity+SG4_Punitive*naturalhazards+SG4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
218 +
219 +#Resource Stress and Minor Spirits Associated With Weather# Table 4, Model 10
220 +summary(model10<-lmer(stress2~MS1_Associated+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Turkic+NuclearTransNewGuinea+Austroasiatic+SinoTibetan+(1|SCCS_ID),data=ang))
221 +
222 +##Secondary analyses looking at specific types of resource stress# Table S6, Model S9
223 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
224 +summary(model0b<-lmer(stress2~MS1_Associated*famine+MS1_Associated*naturalhazards+MS1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Turkic+NuclearTransNewGuinea+Austroasiatic+SinoTibetan+(1|SCCS_ID),data=ang))
225 +summary(model0c<-lmer(stress2~MS1_Associated*famine+MS1_Associated*chron_scarcity+MS1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Turkic+NuclearTransNewGuinea+Austroasiatic+SinoTibetan+(1|SCCS_ID),data=ang))
226 +summary(model0d<-lmer(stress2~MS1_Associated*famine+MS1_Associated*naturalhazards+MS1_Associated*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Turkic+NuclearTransNewGuinea+Austroasiatic+SinoTibetan+(1|SCCS_ID),data=ang))
227 +summary(model0e<-lmer(stress2~MS1_Associated*chron_scarcity+MS1_Associated*naturalhazards+MS1_Associated*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Turkic+NuclearTransNewGuinea+Austroasiatic+SinoTibetan+(1|SCCS_ID),data=ang))
228 +
229 +#Resource Stress and Minor Spirits That Harm With Weather# Table 4, Model 11
230 +summary(model11<-lmer(stress2~MS2_Harm+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
231 +
232 +##Secondary analyses looking at specific types of resource stress# Table S6, Model S10
233 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
234 +summary(model11b<-lmer(stress2~MS2_Harm*famine+MS2_Harm*naturalhazards+MS2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
235 +summary(model11c<-lmer(stress2~MS2_Harm*famine+MS2_Harm*chron_scarcity+MS2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
236 +summary(model11d<-lmer(stress2~MS2_Harm*famine+MS2_Harm*naturalhazards+MS2_Harm*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
237 +summary(model11e<-lmer(stress2~MS2_Harm*chron_scarcity+MS2_Harm*naturalhazards+MS2_Harm*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
238 +
239 +
240 +#Resource Stress and Minor Spirits That Help With Weather# Table 4, Model 12
241 +summary(model12<-lmer(stress2~MS3_Help+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
242 +
243 +##Secondary analyses looking at specific types of resource stress# Table S6, Model S11
244 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
245 +summary(model12b<-lmer(stress2~MS3_Help*famine+MS3_Help*naturalhazards+MS3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
246 +summary(model12c<-lmer(stress2~MS3_Help*famine+MS3_Help*chron_scarcity+MS3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
247 +summary(model12d<-lmer(stress2~MS3_Help*famine+MS3_Help*naturalhazards+MS3_Help*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
248 +summary(model12e<-lmer(stress2~MS3_Help*chron_scarcity+MS3_Help*naturalhazards+MS3_Help*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
249 +
250 +#Resource Stress and Minor Spirits That Punish With Weather# Table 4, Model 13
251 +summary(model13<-lmer(stress2~MS4_Punitive+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
252 +
253 +##Secondary analyses looking at specific types of resource stress# Table S6, Model S12
254 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
255 +summary(model13b<-lmer(stress2~MS4_Punitive*famine+MS4_Punitive*naturalhazards+MS4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
256 +summary(model13c<-lmer(stress2~MS4_Punitive*famine+MS4_Punitive*chron_scarcity+MS4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
257 +summary(model13d<-lmer(stress2~MS4_Punitive*famine+MS4_Punitive*naturalhazards+MS4_Punitive*chron_scarcity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
258 +summary(model13e<-lmer(stress2~MS4_Punitive*chron_scarcity+MS4_Punitive*naturalhazards+MS4_Punitive*abundance+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+NuclearTransNewGuinea+(1|SCCS_ID),data=ang))
259 +
260 +#################################################
261 +##For the Existing SCCS Moralizing God Variable##
262 +#################################################
263 +
264 +##Dummy-coding language family (there are more language families represented in these data)
265 +mor$Afroasiatic<-ifelse(as.character(mor$language_family)=="Afro-Asiatic",1,0)
266 +mor$Afroasiatic<-ifelse(is.na(mor$Afroasiatic)==T,0,mor$Afroasiatic)
267 +
268 +mor$Austronesian<-ifelse(as.character(mor$language_family)=="Austronesian",1,0)
269 +mor$Austronesian<-ifelse(is.na(mor$Austronesian)==T,0,mor$Austronesian)
270 +
271 +mor$AtlanticCongo<-ifelse(as.character(mor$language_family)=="Atlantic-Congo",1,0)
272 +mor$AtlanticCongo<-ifelse(is.na(mor$AtlanticCongo)==T,0,mor$AtlanticCongo)
273 +
274 +mor$Indoeuropean<-ifelse(as.character(mor$language_family)=="Indo-European",1,0)
275 +mor$Indoeuropean<-ifelse(is.na(mor$Indoeuropean)==T,0,mor$Indoeuropean)
276 +
277 +mor$Algic<-ifelse(as.character(mor$language_family)=="Algic",1,0)
278 +mor$Algic<-ifelse(is.na(mor$Algic)==T,0,mor$Algic)
279 +
280 +mor$Arawakan<-ifelse(as.character(mor$language_family)=="Arawakan",1,0)
281 +mor$Arawakan<-ifelse(is.na(mor$Arawakan)==T,0,mor$Arawakan)
282 +
283 +mor$AthabaskanEyakTlingit<-ifelse(as.character(mor$language_family)=="Athabaskan-Eyak-Tlingit",1,0)
284 +mor$AthabaskanEyakTlingit<-ifelse(is.na(mor$AthabaskanEyakTlingit)==T,0,mor$AthabaskanEyakTlingit)
285 +
286 +mor$Chibchan<-ifelse(as.character(mor$language_family)=="Chibchan",1,0)
287 +mor$Chibchan<-ifelse(is.na(mor$Chibchan)==T,0,mor$Chibchan)
288 +
289 +mor$SinoTibetan<-ifelse(as.character(mor$language_family)=="Sino-Tibetan",1,0)
290 +mor$SinoTibetan<-ifelse(is.na(mor$SinoTibetan)==T,0,mor$SinoTibetan)
291 +
292 +mor$Tupian<-ifelse(as.character(mor$language_family)=="Tupian",1,0)
293 +mor$Tupian<-ifelse(is.na(mor$Tupian)==T,0,mor$Tupian)
294 +
295 +mor$Turkic<-ifelse(as.character(mor$language_family)=="Turkic",1,0)
296 +mor$Turkic<-ifelse(is.na(mor$Turkic)==T,0,mor$Turkic)
297 +
298 +mor$Uralic<-ifelse(as.character(mor$language_family)=="Uralic",1,0)
299 +mor$Uralic<-ifelse(is.na(mor$Uralic)==T,0,mor$Uralic)
300 +
301 +mor$UtoAztecan<-ifelse(as.character(mor$language_family)=="Uto-Aztecan",1,0)
302 +mor$UtoAztecan<-ifelse(is.na(mor$UtoAztecan)==T,0,mor$UtoAztecan)
303 +
304 +mor$Dravidian<-ifelse(as.character(mor$language_family)=="Dravidian",1,0)
305 +mor$Dravidian<-ifelse(is.na(mor$Dravidian)==T,0,mor$Dravidian)
306 +
307 +mor$EskimoAleut<-ifelse(as.character(mor$language_family)=="Eskimo-Aleut",1,0)
308 +mor$EskimoAleut<-ifelse(is.na(mor$EskimoAleut)==T,0,mor$EskimoAleut)
309 +
310 +mor$Mande<-ifelse(as.character(mor$language_family)=="Mande",1,0)
311 +mor$Mande<-ifelse(is.na(mor$Mande)==T,0,mor$Mande)
312 +
313 +mor$Salishan<-ifelse(as.character(mor$language_family)=="Salishan",1,0)
314 +mor$Salishan<-ifelse(is.na(mor$Salishan)==T,0,mor$Salishan)
315 +
316 +table(mor$language_family)
317 +
318 +##Dummy coding stressors
319 +#Famine=1 under ResourceStress Variable
320 +mor$famine<-ifelse(as.character(mor$ResourceStress)=="1",1,0)
321 +#Natural Hazards=2 under ResourceStress Variable
322 +mor$naturalhazards<-ifelse(as.character(mor$ResourceStress)=="2",1,0)
323 +#Chronic Scarcity=3 under ResourceStress Variable
324 +mor$chron_scarcity<-ifelse(as.character(mor$ResourceStress)=="3",1,0)
325 +#Abundance=4 under ResourceStress Variable
326 +mor$abundance<-ifelse(as.character(mor$ResourceStress)=="4",1,0)
327 +
328 +#Reverse-coding abundance to be able to merge it with other stressors
329 +mor$stress2<-ifelse(mor$abundance==1,(0-mor$Stress),
330 + ifelse(mor$abundance==0,mor$Stress,
331 + NA))
332 +
333 +#Dichotomized stress variable (not necessary for this analysis)
334 +mor$stress3<-ifelse(mor$chron_scarcity==1&mor$stress2<(-.11),(-1),
335 + ifelse(mor$chron_scarcity==1&mor$stress2>(-.11),1,
336 + ifelse(mor$famine==1&mor$stress2<(-.11),(-1),
337 + ifelse(mor$famine==1&mor$stress2>(-.11),1,
338 + mor$stress2))))
339 +
340 +##Creating datasets for each of the god variables (this can be used to compute R2 later)
341 +mor2<-mor[is.na(mor$MHG_PresAbs)==F,]
342 +mor3<-mor[is.na(mor$HG_Pres_MoralNoYes)==F,]
343 +
344 +#Empty model (anova) (this can be used to compute R2 later)
345 +summary(fit1<-lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=mor))
346 +summary(fit1<-lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=mor2))
347 +summary(fit1<-lmer(stress2~Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+(1|SCCS_ID),data=mor3))
348 +
349 +
350 +##For the analyses below, you can get the R squared by comparing...
351 +#...the variance explained at the society level with the variance explained by language family alone
352 +
353 +#Association between presence of moralizing high gods and resource stress# Table 5, Model 14
354 +summary(model14<-lmer(stress2~MHG_PresAbs+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+Dravidian+EskimoAleut+Mande+Salishan+(1|SCCS_ID),data=mor))
355 +summary(model14<-lmer(scale(stress2)~scale(MHG_PresAbs)+scale(Social_Complexity)+scale(Afroasiatic)+scale(Austronesian)+scale(AtlanticCongo)+scale(Indoeuropean)+scale(Algic)+scale(Arawakan)+scale(AthabaskanEyakTlingit)+scale(Chibchan)+scale(SinoTibetan)+scale(Tupian)+scale(Turkic)+scale(Uralic)+scale(UtoAztecan)+scale(Dravidian)+scale(EskimoAleut)+scale(Mande)+scale(Salishan)+(1|SCCS_ID),data=mor))
356 +##Extract effect size from model on line 355, since beta.lmer is having trouble with this model
357 +
358 +##Secondary analyses looking at specific types of resource stress# Table S7, Model S13
359 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
360 +summary(model14b<-lmer(stress2~MHG_PresAbs*famine+MHG_PresAbs*naturalhazards+MHG_PresAbs*abundance+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+Dravidian+EskimoAleut+Mande+Salishan+(1|SCCS_ID),data=mor))
361 +summary(model14c<-lmer(stress2~MHG_PresAbs*famine+MHG_PresAbs*chron_scarcity+MHG_PresAbs*abundance+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+Dravidian+EskimoAleut+Mande+Salishan+(1|SCCS_ID),data=mor))
362 +summary(model14d<-lmer(stress2~MHG_PresAbs*famine+MHG_PresAbs*naturalhazards+MHG_PresAbs*chron_scarcity+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+Dravidian+EskimoAleut+Mande+Salishan+(1|SCCS_ID),data=mor))
363 +summary(model14e<-lmer(stress2~MHG_PresAbs*chron_scarcity+MHG_PresAbs*naturalhazards+MHG_PresAbs*abundance+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+Dravidian+EskimoAleut+Mande+Salishan+(1|SCCS_ID),data=mor))
364 +
365 +
366 +#Association between presence of moralizing high gods amongst societies that have high gods and resource stress# Table 5, Model 15
367 +summary(model15<-lmer(stress2~HG_Pres_MoralNoYes+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+(1|SCCS_ID),data=mor))
368 +summary(model15<-lmer(scale(stress2)~scale(HG_Pres_MoralNoYes)+scale(Social_Complexity)+scale(Afroasiatic)+scale(Austronesian)+
369 + scale(AtlanticCongo)+scale(Indoeuropean)+scale(Algic)+scale(Arawakan)+scale(AthabaskanEyakTlingit)+
370 + scale(Chibchan)+scale(SinoTibetan)+scale(Tupian)+scale(Turkic)+scale(Uralic)+scale(UtoAztecan)+(1|SCCS_ID),data=mor))
371 +##Extract effect size from model on line 368, since beta.lmer is having trouble with this model
372 +
373 +##Secondary analyses looking at specific types of resource stress# Table S7, Model S14
374 +#Looking at Chronic scarcity, then natural hazards, then abundance, then famine
375 +summary(model15b<-lmer(stress2~HG_Pres_MoralNoYes*famine+HG_Pres_MoralNoYes*naturalhazards+HG_Pres_MoralNoYes*abundance+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+(1|SCCS_ID),data=mor))
376 +summary(model15c<-lmer(stress2~HG_Pres_MoralNoYes*famine+HG_Pres_MoralNoYes*chron_scarcity+HG_Pres_MoralNoYes*abundance+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+(1|SCCS_ID),data=mor))
377 +summary(model15d<-lmer(stress2~HG_Pres_MoralNoYes*famine+HG_Pres_MoralNoYes*naturalhazards+HG_Pres_MoralNoYes*chron_scarcity+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+(1|SCCS_ID),data=mor))
378 +summary(model15e<-lmer(stress2~HG_Pres_MoralNoYes*chron_scarcity+HG_Pres_MoralNoYes*naturalhazards+HG_Pres_MoralNoYes*abundance+Social_Complexity+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan+(1|SCCS_ID),data=mor))
379 +
380 +###########################################################################
381 +###PART B: Central Analyses on Stressors, Religious Beliefs, and Sharing###
382 +###########################################################################
383 +
384 +
385 +mor<-read.csv("DT-MoralHighGods_EP.csv")
386 +ang<-read.csv("DT-GodsAndResourceStress.csv")
387 +
388 +library(Kendall)
389 +
390 +##Dummy-coding language family information
391 +mor$Afroasiatic<-ifelse(as.character(mor$language_family)=="Afro-Asiatic",1,0)
392 +mor$Afroasiatic<-ifelse(is.na(mor$Afroasiatic)==T,0,mor$Afroasiatic)
393 +mor$Austronesian<-ifelse(as.character(mor$language_family)=="Austronesian",1,0)
394 +mor$Austronesian<-ifelse(is.na(mor$Austronesian)==T,0,mor$Austronesian)
395 +mor$AtlanticCongo<-ifelse(as.character(mor$language_family)=="Atlantic-Congo",1,0)
396 +mor$AtlanticCongo<-ifelse(is.na(mor$AtlanticCongo)==T,0,mor$AtlanticCongo)
397 +mor$Indoeuropean<-ifelse(as.character(mor$language_family)=="Indo-European",1,0)
398 +mor$Indoeuropean<-ifelse(is.na(mor$Indoeuropean)==T,0,mor$Indoeuropean)
399 +mor$Afroasiatic<-ifelse(as.character(mor$language_family)=="Afro-Asiatic",1,0)
400 +mor$Afroasiatic<-ifelse(is.na(mor$Afroasiatic)==T,0,mor$Afroasiatic)
401 +mor$Austronesian<-ifelse(as.character(mor$language_family)=="Austronesian",1,0)
402 +mor$Austronesian<-ifelse(is.na(mor$Austronesian)==T,0,mor$Austronesian)
403 +mor$AtlanticCongo<-ifelse(as.character(mor$language_family)=="Atlantic-Congo",1,0)
404 +mor$AtlanticCongo<-ifelse(is.na(mor$AtlanticCongo)==T,0,mor$AtlanticCongo)
405 +mor$Indoeuropean<-ifelse(as.character(mor$language_family)=="Indo-European",1,0)
406 +mor$Indoeuropean<-ifelse(is.na(mor$Indoeuropean)==T,0,mor$Indoeuropean)
407 +mor$Algic<-ifelse(as.character(mor$language_family)=="Algic",1,0)
408 +mor$Algic<-ifelse(is.na(mor$Algic)==T,0,mor$Algic)
409 +mor$Arawakan<-ifelse(as.character(mor$language_family)=="Arawakan",1,0)
410 +mor$Arawakan<-ifelse(is.na(mor$Arawakan)==T,0,mor$Arawakan)
411 +mor$AthabaskanEyakTlingit<-ifelse(as.character(mor$language_family)=="Athabaskan-Eyak-Tlingit",1,0)
412 +mor$AthabaskanEyakTlingit<-ifelse(is.na(mor$AthabaskanEyakTlingit)==T,0,mor$AthabaskanEyakTlingit)
413 +mor$Chibchan<-ifelse(as.character(mor$language_family)=="Chibchan",1,0)
414 +mor$Chibchan<-ifelse(is.na(mor$Chibchan)==T,0,mor$Chibchan)
415 +mor$SinoTibetan<-ifelse(as.character(mor$language_family)=="Sino-Tibetan",1,0)
416 +mor$SinoTibetan<-ifelse(is.na(mor$SinoTibetan)==T,0,mor$SinoTibetan)
417 +mor$Tupian<-ifelse(as.character(mor$language_family)=="Tupian",1,0)
418 +mor$Tupian<-ifelse(is.na(mor$Tupian)==T,0,mor$Tupian)
419 +mor$Turkic<-ifelse(as.character(mor$language_family)=="Turkic",1,0)
420 +mor$Turkic<-ifelse(is.na(mor$Turkic)==T,0,mor$Turkic)
421 +mor$Uralic<-ifelse(as.character(mor$language_family)=="Uralic",1,0)
422 +mor$Uralic<-ifelse(is.na(mor$Uralic)==T,0,mor$Uralic)
423 +mor$UtoAztecan<-ifelse(as.character(mor$language_family)=="Uto-Aztecan",1,0)
424 +mor$UtoAztecan<-ifelse(is.na(mor$UtoAztecan)==T,0,mor$UtoAztecan)
425 +mor$Dravidian<-ifelse(as.character(mor$language_family)=="Dravidian",1,0)
426 +mor$Dravidian<-ifelse(is.na(mor$Dravidian)==T,0,mor$Dravidian)
427 +mor$EskimoAleut<-ifelse(as.character(mor$language_family)=="Eskimo-Aleut",1,0)
428 +mor$EskimoAleut<-ifelse(is.na(mor$EskimoAleut)==T,0,mor$EskimoAleut)
429 +mor$Mande<-ifelse(as.character(mor$language_family)=="Mande",1,0)
430 +mor$Mande<-ifelse(is.na(mor$Mande)==T,0,mor$Mande)
431 +mor$Salishan<-ifelse(as.character(mor$language_family)=="Salishan",1,0)
432 +mor$Salishan<-ifelse(is.na(mor$Salishan)==T,0,mor$Salishan)
433 +
434 +ang$Afroasiatic<-ifelse(as.character(ang$language_family)=="Afro-Asiatic",1,0)
435 +ang$Afroasiatic<-ifelse(is.na(ang$Afroasiatic)==T,0,ang$Afroasiatic)
436 +ang$Austronesian<-ifelse(as.character(ang$language_family)=="Austronesian",1,0)
437 +ang$Austronesian<-ifelse(is.na(ang$Austronesian)==T,0,ang$Austronesian)
438 +ang$AtlanticCongo<-ifelse(as.character(ang$language_family)=="Atlantic-Congo",1,0)
439 +ang$AtlanticCongo<-ifelse(is.na(ang$AtlanticCongo)==T,0,ang$AtlanticCongo)
440 +ang$Indoeuropean<-ifelse(as.character(ang$language_family)=="Indo-European",1,0)
441 +ang$Indoeuropean<-ifelse(is.na(ang$Indoeuropean)==T,0,ang$Indoeuropean)
442 +ang$NuclearTransNewGuinea<-ifelse(as.character(ang$language_family)=="Nuclear Trans New Guinea",1,0)
443 +ang$NuclearTransNewGuinea<-ifelse(is.na(ang$NuclearTransNewGuinea)==T,0,ang$NuclearTransNewGuinea)
444 +ang$SinoTibetan<-ifelse(as.character(ang$language_family)=="Sino-Tibetan",1,0)
445 +ang$SinoTibetan<-ifelse(is.na(ang$SinoTibetan)==T,0,ang$SinoTibetan)
446 +ang$Uralic<-ifelse(as.character(ang$language_family)=="Uralic",1,0)
447 +ang$Uralic<-ifelse(is.na(ang$Uralic)==T,0,ang$Uralic)
448 +ang$Turkic<-ifelse(as.character(ang$language_family)=="Turkic",1,0)
449 +ang$Turkic<-ifelse(is.na(ang$Turkic)==T,0,ang$Turkic)
450 +ang$Austroasiatic<-ifelse(as.character(ang$language_family)=="Austroasiatic",1,0)
451 +ang$Austroasiatic<-ifelse(is.na(ang$Austroasiatic)==T,0,ang$Austroasiatic)
452 +
453 +
454 +##Creating single stressor variable
455 +ang$ZSCCS_Abundance_imp_rev<-(0-ang$ZSCCS_Abundance_imp)
456 +mor$ZSCCS_Abundance_imp_rev<-(0-mor$ZSCCS_Abundance_imp)
457 +ang_stress<-data.frame(ang$ZFamine,ang$ZNatural_Hazards,ang$ZChronic_Scarcity,ang$ZSCCS_Abundance_imp_rev)
458 +ang$stress<-rowMeans(ang_stress,na.rm=T)
459 +mor_stress<-data.frame(mor$ZFamine,mor$ZNatural_Hazards,mor$ZChronic_Scarcity,mor$ZSCCS_Abundance_imp_rev)
460 +mor$stress<-rowMeans(mor_stress,na.rm=T)
461 +
462 +##Regressions on Food Sharing
463 +summary(model16<-lm(S3_Resolved_IA_TR~stress+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
464 +lm.beta(model16)
465 +confint(lm.beta(model16),level = .95)
466 +summary(model17<-lm(S3_Resolved_IA_TR~stress+G3_Help+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
467 +lm.beta(model17)
468 +confint(lm.beta(model17),level = .95)
469 +summary(model18<-lm(S3_Resolved_IA_TR~stress+G2_Harm+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
470 +lm.beta(model18)
471 +confint(lm.beta(model18),level = .95)
472 +summary(model19<-lm(S3_Resolved_IA_TR~stress+G4_Punitive+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
473 +lm.beta(model19)
474 +confint(lm.beta(model19),level = .95)
475 +summary(model20<-lm(S3_Resolved_IA_TR~HG_Pres_MoralNoYes+Social_Complexity+stress+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Arawakan+SinoTibetan+Uralic+UtoAztecan,data=mor))
476 +lm.beta(model20)
477 +confint(lm.beta(model20),level = .95)
478 +
479 +##Just regressions for labor sharing
480 +summary(model21<-lm(LS4_Res_IA_2~stress+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
481 +lm.beta(model21)
482 +confint(lm.beta(model21),level = .95)
483 +summary(model22<-lm(LS4_Res_IA_2~stress+G3_Help+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
484 +lm.beta(model22)
485 +confint(lm.beta(model22),level = .95)
486 +summary(model23<-lm(LS4_Res_IA_2~stress+G2_Harm+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
487 +lm.beta(model23)
488 +confint(lm.beta(model23),level = .95)
489 +summary(model24<-lm(LS4_Res_IA_2~stress+G4_Punitive+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean,data=ang))
490 +lm.beta(model24)
491 +confint(lm.beta(model24),level = .95)
492 +summary(model25<-lm(LS4_Res_IA_2~HG_Pres_MoralNoYes+Social_Complexity+stress+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Arawakan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan,data=mor))
493 +lm.beta(model25)
494 +confint(lm.beta(model25),level = .95)
495 +
496 +#making social complexity and moral high god interaction term
497 +mor$HGPres_x_Complex=mor$HG_Pres_MoralNoYes * mor$Social_Complexity
498 +
499 +summary(model20a<-lm(S3_Resolved_IA_TR~HG_Pres_MoralNoYes+Social_Complexity+stress+ HGPres_x_Complex+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan,data=mor))
500 +summary(model20a)
501 +summary(lm.beta(model20a))
502 +summary.lm.beta(model20a)
503 +confint(lm.beta(model20a),level = .95)
504 +
505 +summary(model25a<-lm(LS4_Res_IA_2~HG_Pres_MoralNoYes+Social_Complexity+stress+ HGPres_x_Complex+Afroasiatic+Austronesian+AtlanticCongo+Indoeuropean+Algic+Arawakan+AthabaskanEyakTlingit+Chibchan+SinoTibetan+Tupian+Turkic+Uralic+UtoAztecan,data=mor))
506 +summary(model25a)
507 +lm.beta(model25a)
508 +summary.lm.beta(model25a)
509 +confint(lm.beta(model25a),level = .95)
510 +
511 +###########################
512 +##Monte Carlo Simulations##
513 +##########################
514 +##Model involving Resource Stress, Helping Gods, and Food Sharing
515 +require(MASS)
516 +a=0.9401
517 +b=-0.2995
518 +rep=20000
519 +conf=95
520 +pest=c(a,b)
521 +acov <- matrix(c(
522 + 0.07160976, 0,
523 + 0, 0.04109729
524 +),2,2)
525 +acov
526 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
527 +ab <- mcmc[,1]*mcmc[,2]
528 +low=(1-conf/100)/2
529 +upp=((1-conf/100)/2)+(conf/100)
530 +LL=quantile(ab,low)
531 +UL=quantile(ab,upp)
532 +LL4=format(LL,digits=4)
533 +UL4=format(UL,digits=4)
534 +################################################
535 +# The number of columns in the histogram can #
536 +# be changed by replacing 'FD' below with #
537 +# an integer value. #
538 +################################################
539 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
540 + main='Distribution of Indirect Effect')
541 +
542 +##Model involving Resource Stress, Harming Gods, and Food Sharing
543 +require(MASS)
544 +a=1.194
545 +b=-0.69148
546 +rep=20000
547 +conf=95
548 +pest=c(a,b)
549 +acov <- matrix(c(
550 + 0.11048976, 0,
551 + 0, 0.0482022
552 +),2,2)
553 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
554 +ab <- mcmc[,1]*mcmc[,2]
555 +low=(1-conf/100)/2
556 +upp=((1-conf/100)/2)+(conf/100)
557 +LL=quantile(ab,low)
558 +UL=quantile(ab,upp)
559 +LL4=format(LL,digits=4)
560 +UL4=format(UL,digits=4)
561 +################################################
562 +# The number of columns in the histogram can #
563 +# be changed by replacing 'FD' below with #
564 +# an integer value. #
565 +################################################
566 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
567 + main='Distribution of Indirect Effect')
568 +
569 +##Model involving Resource Stress, Punitive Gods, and Food Sharing
570 +require(MASS)
571 +a=0.2929
572 +b=-0.3853
573 +rep=20000
574 +conf=95
575 +pest=c(a,b)
576 +acov <- matrix(c(
577 + 0.08988004, 0,
578 + 0, 0.05175625
579 +),2,2)
580 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
581 +ab <- mcmc[,1]*mcmc[,2]
582 +low=(1-conf/100)/2
583 +upp=((1-conf/100)/2)+(conf/100)
584 +LL=quantile(ab,low)
585 +UL=quantile(ab,upp)
586 +LL4=format(LL,digits=4)
587 +UL4=format(UL,digits=4)
588 +################################################
589 +# The number of columns in the histogram can #
590 +# be changed by replacing 'FD' below with #
591 +# an integer value. #
592 +################################################
593 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
594 + main='Distribution of Indirect Effect')
595 +
596 +##Model involving Resource Stress, Moralizing Gods, and Food Sharing
597 +require(MASS)
598 +a=0.468225
599 +b=-0.286069
600 +rep=20000
601 +conf=95
602 +pest=c(a,b)
603 +acov <- matrix(c(
604 + 0.03375671, 0,
605 + 0, 0.03394769
606 +),2,2)
607 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
608 +ab <- mcmc[,1]*mcmc[,2]
609 +low=(1-conf/100)/2
610 +upp=((1-conf/100)/2)+(conf/100)
611 +LL=quantile(ab,low)
612 +UL=quantile(ab,upp)
613 +LL4=format(LL,digits=4)
614 +UL4=format(UL,digits=4)
615 +################################################
616 +# The number of columns in the histogram can #
617 +# be changed by replacing 'FD' below with #
618 +# an integer value. #
619 +################################################
620 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
621 + main='Distribution of Indirect Effect')
622 +
623 +##Model involving Resource Stress, Helping Gods, and Labor Sharing
624 +require(MASS)
625 +a=0.9401
626 +b=0.08712
627 +rep=20000
628 +conf=95
629 +pest=c(a,b)
630 +acov <- matrix(c(
631 + 0.07160976, 0,
632 + 0, 0.076016
633 +),2,2)
634 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
635 +ab <- mcmc[,1]*mcmc[,2]
636 +low=(1-conf/100)/2
637 +upp=((1-conf/100)/2)+(conf/100)
638 +LL=quantile(ab,low)
639 +UL=quantile(ab,upp)
640 +LL4=format(LL,digits=4)
641 +UL4=format(UL,digits=4)
642 +################################################
643 +# The number of columns in the histogram can #
644 +# be changed by replacing 'FD' below with #
645 +# an integer value. #
646 +################################################
647 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
648 + main='Distribution of Indirect Effect')
649 +
650 +##Model involving Resource Stress, Harming Gods, and Labor Sharing
651 +require(MASS)
652 +a=1.194
653 +b=0.1561
654 +rep=20000
655 +conf=95
656 +pest=c(a,b)
657 +acov <- matrix(c(
658 + 0.11048976, 0,
659 + 0, 0.18198756
660 +),2,2)
661 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
662 +ab <- mcmc[,1]*mcmc[,2]
663 +low=(1-conf/100)/2
664 +upp=((1-conf/100)/2)+(conf/100)
665 +LL=quantile(ab,low)
666 +UL=quantile(ab,upp)
667 +LL4=format(LL,digits=4)
668 +UL4=format(UL,digits=4)
669 +################################################
670 +# The number of columns in the histogram can #
671 +# be changed by replacing 'FD' below with #
672 +# an integer value. #
673 +################################################
674 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
675 + main='Distribution of Indirect Effect')
676 +
677 +##Model involving Resource Stress, Punitive Gods, and Labor Sharing
678 +require(MASS)
679 +a=0.2929
680 +b=0.09117
681 +rep=20000
682 +conf=95
683 +pest=c(a,b)
684 +acov <- matrix(c(
685 + 0.08988004, 0,
686 + 0, 0.05847208
687 +),2,2)
688 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
689 +ab <- mcmc[,1]*mcmc[,2]
690 +low=(1-conf/100)/2
691 +upp=((1-conf/100)/2)+(conf/100)
692 +LL=quantile(ab,low)
693 +UL=quantile(ab,upp)
694 +LL4=format(LL,digits=4)
695 +UL4=format(UL,digits=4)
696 +################################################
697 +# The number of columns in the histogram can #
698 +# be changed by replacing 'FD' below with #
699 +# an integer value. #
700 +################################################
701 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
702 + main='Distribution of Indirect Effect')
703 +
704 +##Model involving Resource Stress, Moralizing Gods, and Labor Sharing
705 +require(MASS)
706 +a=0.468225
707 +b=0.188035
708 +rep=20000
709 +conf=95
710 +pest=c(a,b)
711 +acov <- matrix(c(
712 + 0.03375671, 0,
713 + 0, 0.02658661
714 +),2,2)
715 +mcmc <- mvrnorm(rep,pest,acov,empirical=FALSE)
716 +ab <- mcmc[,1]*mcmc[,2]
717 +low=(1-conf/100)/2
718 +upp=((1-conf/100)/2)+(conf/100)
719 +LL=quantile(ab,low)
720 +UL=quantile(ab,upp)
721 +LL4=format(LL,digits=4)
722 +UL4=format(UL,digits=4)
723 +################################################
724 +# The number of columns in the histogram can #
725 +# be changed by replacing 'FD' below with #
726 +# an integer value. #
727 +################################################
728 +hist(ab,breaks='FD',col='skyblue',xlab=paste(conf,'% Confidence Interval ','LL',LL4,' UL',UL4),
729 + main='Distribution of Indirect Effect')
730 +
731 +
SDIIS_Combined_ann.xlsx
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Content
SPSS_PCM.xlsx
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SPSS_indices.xlsx
Author
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Content
Skoggard et al._Data.csv
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1 +SCCS_ID,Complexity,G1_Resolved,G2_Resolved,G3_Resolved,G4_Resolved,SG1_Resolved,SG2_Resolved,SG3_Resolved,SG4_Resolved,MS1_Resolved,MS2_Resolved,MS3_Resolved,MS4_Resolved,Natural_Hazards,Chronic_Scarcity,Famine,Resource_Abundance,Climate_Stability,LS4_Res_IA_2,S3_Resolved_IA_TR,EA_34MHG
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4 +8,1,0,0,0,0,1,1,1,1,1,1,1,0,2,1,1,1.359407527,-0.40857176,0,0,0
5 +9,0,NA,NA,NA,NA,1,NA,NA,1,NA,NA,NA,NA,3,1,1,1.038279333,-0.167191931,NA,0,NA
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Skoggard et al._Data.xlsx
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Social Resilience ARO-DA.sav
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Social Resilience.csv
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1 +Case_Number,Case_Name,NGA,SigTempChng,Data_Source,CV_1,DV_1,DV_2,DV_3,DV_4_1,DV_4_2,DV_4_3,DV_1rec,DV_2rec,DV_3rec,DV_4_1rec,DV_4_2rec,DV_4_3rec,M486,M536,TempDiff,ZIV_2_1,ZIV_2_2,ZIV_2_3,ZIV_2_4,ZIV_2_5,ZIV_2_6,ZIV_3_1,ZIV_3_2,ZIV_3_3,ZIV_3_4,ZIV_3_5,ZDV_1rec,ZDV_2rec,ZDV_3rec,ZDV_4_1rec,ZDV_4_2rec,ZDV_4_3rec,ZCE_Index,ZTL_Full_Index,ZDV_Index,SC_Index
2 +ARO-1,Point Peninsula,Ontario,2,1,1,3,3,3,3,3,3,1,1,1,1,1,1,-.016927127,-.760167645,.743240518,-.840819091235472,-.0979589689408756,-.974679434480896,-.374384741177081,-1.40046075367382,.255474412755014,-1.85691899342652,-1.90418387514612,-1.62894084480133,-1.57974550321319,-1.46864503505568,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,-1.68768685032857,-.572138096125522,-.911788253507778,6
3 +ARO-2,Mund,Cahokia,2,1,1,3,3,3,3,2,2,1,1,1,1,2,2,-.035090798,-.737780036,.702689238,-1.89184295527981,-1.07754865834964,-.974679434480896,-.374384741177081,-1.40046075367382,.255474412755014,-1.85691899342652,-1.90418387514612,-1.62894084480133,-1.57974550321319,-1.46864503505568,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,.0658627325836015,.239949489634293,-1.68768685032857,-.910573688367706,-.492287903533862,8
4 +ARO-3,Pioneer/Formative,Gila River,1,1,1,4,3,3,4,4,3,2,1,1,2,2,1,-.020913683,-.765680713,.74476703,.210204772808869,-1.07754865834964,-.974679434480896,-.374384741177081,-.525172782627683,-1.44768833894508,-1.85691899342652,-1.90418387514612,-1.62894084480133,-1.57974550321319,-1.46864503505568,.171410161014361,-.521749194749951,-.724490058419616,.260494036125864,.0658627325836015,-.959797958537171,-1.68768685032857,-.698211530461918,-.284711713663819,9
5 +ARO-4,Monte Alban IIIB and IV,Oaxaca,1,2,2,1,4,3,1,1,1,3,2,1,3,3,3,-.139726824,-.290147404,.15042058,1.26122863685321,.881630720467889,1.94935886896179,.873564396079853,1.22540315946459,1.10705578860506,.795822425754221,.211575986127346,1.08596056320089,.850632194037869,1.62323924927207,1.31414456777677,.968962790249909,-.724490058419616,1.56296421675518,1.38311738425563,1.43969693780576,.913446083678479,1.21637359507207,.990732639737272,15
6 +ARO-5,Early Classic,Tikal,1,1,2,4,3,3,4,5,5,2,1,1,2,3,3,-.138150449,-.290298822,.152148373,-.840819091235472,-.0979589689408756,.974679434480897,-.374384741177081,1.22540315946459,1.10705578860506,.132637070959037,.211575986127346,1.08596056320089,.0405062949541843,.0772971071081939,.171410161014361,-.521749194749951,-.724490058419616,.260494036125864,1.38311738425563,1.43969693780576,.30959540446993,.332329263532853,.334746544338674,12
7 +ARO-6,Early Medieval,Paris Basin,2,2,3,3,3,3,3,3,3,1,1,1,1,1,1,.049944951,-.743630537,.793575488,.210204772808869,-.0979589689408756,2.16422309957864E-016,-.374384741177081,.350115188418455,.255474412755014,.132637070959037,.211575986127346,.180993427200148,.0405062949541843,.0772971071081939,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,.128601977269782,.0572417773107302,-.911788253507778,6
8 +ARO-7,Ostrogoths,Latium,2,1,3,1,5,5,2,2,3,3,3,3,2,2,1,-.015152511,-.705394836,.690242324,1.26122863685321,.881630720467889,.974679434480897,-1.62233387843402,-.525172782627683,-.596106963095032,.795822425754221,.916829273218502,1.08596056320089,1.66075809312155,.0772971071081939,1.31414456777677,2.45967477524977,1.91001924492444,.260494036125864,.0658627325836015,-.959797958537171,.907333492480671,.0623208612742108,.841732899687212,14
9 +ARO-8,Migration,Jutland,2,3,1,2,3,3,4,2,4,2,1,1,2,2,2,-.060387745,-1.065151245,1.0047635,-.840819091235472,-1.07754865834964,-.974679434480896,-.374384741177081,.350115188418455,-1.44768833894508,-.530548283836148,.211575986127346,-.723973708800591,.0405062949541843,.0772971071081939,.171410161014361,-.521749194749951,-.724490058419616,.260494036125864,.0658627325836015,.239949489634293,-.185028520889403,-.727500845961619,-.0847538056352414,10
10 +ARO-9,Brega,Ireland,2,3,2,3,3,3,3,3,3,1,1,1,1,1,1,.014067762,-.499974744,.514042506,1.26122863685321,-2.0571383477584,-.974679434480896,-1.62233387843402,-1.40046075367382,-.596106963095032,-.530548283836148,-.493677300963809,.180993427200148,-.7696196041295,-.695673963973745,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,-.461705145140611,-.898248456764826,-.911788253507778,6
11 +ARO-10,Toledo,Central Spain,2,3,3,4,4,5,1,2,5,2,2,3,3,2,3,.025247981,-.551149754,.576397735,-.840819091235472,-.0979589689408756,1.94935886896179,-.374384741177081,-.525172782627683,.255474412755014,.795822425754221,.211575986127346,1.08596056320089,.0405062949541843,.0772971071081939,.171410161014361,.968962790249909,1.91001924492444,1.56296421675518,.0658627325836015,1.43969693780576,.442232475428966,.0610829496226158,1.01981934722221,15
12 +ARO-11,Rouran Khaganate,Orkhon Valley,2,2,2,1,3,3,1,1,1,3,1,1,3,3,3,-.02555553,-.754695114,.729139584,.210204772808869,-.0979589689408756,-.974679434480896,2.12151353333679,-1.40046075367382,-1.44768833894508,.795822425754221,-.493677300963809,.180993427200148,-.7696196041295,1.62323924927207,1.31414456777677,-.521749194749951,-.724490058419616,1.56296421675518,1.38311738425563,1.43969693780576,.267351639426626,-.264844864982502,.742280642237295,14
13 +ARO-12,Hephthalites,Sogdiana,1,2,2,2,3,2,1,1,1,2,1,2,3,3,3,-.058453975,-.405167154,.346713178,-.840819091235472,.881630720467889,-.974679434480896,2.12151353333679,-1.40046075367382,-.596106963095032,-.530548283836148,.211575986127346,.180993427200148,-.7696196041295,1.62323924927207,.171410161014361,-.521749194749951,.592764593252413,1.56296421675518,1.38311738425563,1.43969693780576,.143128154926783,-.134820331446757,.771367349722232,14
14 +ARO-13,Kofun,Kansai,2,2,3,5,3,3,3,4,4,3,1,1,1,2,2,-.118724839,-.452503118,.333778279,.210204772808869,-.0979589689408756,2.16422309957864E-016,.873564396079853,1.22540315946459,1.95863716445511,.795822425754221,.916829273218502,1.08596056320089,1.66075809312155,1.62323924927207,1.31414456777677,-.521749194749951,-.724490058419616,-1.04197614450346,.0658627325836015,.239949489634293,1.21652192091345,.694975087311258,-.11137643461306,10
15 +ARO-14,Early Imperial,Luoyang,2,2,3,3,3,4,3,5,3,1,1,2,1,3,1,.116577377,-.484981317,.601558694,-1.89184295527981,.881630720467889,2.16422309957864E-016,-.374384741177081,.350115188418455,.255474412755014,.132637070959037,.916829273218502,1.08596056320089,.0405062949541843,.0772971071081939,-.971324245748044,-.521749194749951,.592764593252413,-1.04197614450346,1.38311738425563,-.959797958537171,.450646061888161,-.129834562469256,-.253160927671763,9
16 +ARO-15,Liang,Lower Yangtze,2,3,3,3,3,4,3,3,3,1,1,2,1,1,1,.047728854,-.551956376,.59968523,.210204772808869,.881630720467889,2.16422309957864E-016,-.374384741177081,.350115188418455,.255474412755014,.795822425754221,.916829273218502,1.08596056320089,.850632194037869,-.695673963973745,-.971324245748044,-.521749194749951,.592764593252413,-1.04197614450346,-1.25139191908843,-.959797958537171,.590714098447547,.220506725545524,-.692245811562439,7
17 +ARO-16,Sasania,Susiana,1,2,3,3,3,3,3,3,3,1,1,1,1,1,1,-.090584955,-.490431978,.399847023,1.26122863685321,.881630720467889,.974679434480897,-.374384741177081,.350115188418455,1.10705578860506,.795822425754221,.916829273218502,-.723973708800591,.850632194037869,-.695673963973745,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,.228727244047251,.700054171274738,-.911788253507778,6
18 +ARO-17,Kadamba Empire,Deccan,1,2,3,3,4,4,2,2,4,1,2,2,2,2,2,-.140622492,-.401083838,.260461346,1.26122863685321,.881630720467889,2.16422309957864E-016,-.374384741177081,1.22540315946459,-.596106963095032,.795822425754221,.211575986127346,-.723973708800591,.0405062949541843,-.695673963973745,-.971324245748044,.968962790249909,.592764593252413,.260494036125864,.0658627325836015,.239949489634293,-.0743485931877167,.399628468752263,.192784899349673,11
19 +ARO-18,Gupta Empire,Ganges,1,3,3,3,3,4,4,2,4,1,1,2,2,2,2,-.113309933,-.474442349,.361132415,.210204772808869,.881630720467889,2.16422309957864E-016,.873564396079853,1.22540315946459,.255474412755014,.795822425754221,.916829273218502,.180993427200148,.850632194037869,.0772971071081939,-.971324245748044,-.521749194749951,.592764593252413,.260494036125864,.0658627325836015,.239949489634293,.564314885463787,.57437957692937,-.055667098150304,10
20 +ARO-19,Byzantine,Upper Egypt,1,2,3,1,5,5,2,3,2,3,3,3,2,1,2,-.142966804,-.383099953,.240133149,.210204772808869,.881630720467889,.974679434480897,.873564396079853,.350115188418455,1.10705578860506,.795822425754221,.916829273218502,-.723973708800591,.850632194037869,.0772971071081939,1.31414456777677,2.45967477524977,1.91001924492444,.260494036125864,-1.25139191908843,.239949489634293,.383321458263639,.732875050143504,.822148365770451,14
21 +ARO-20,Jenne-jeno III,Lower Niger,1,2,2,5,3,3,4,4,3,3,1,1,2,2,1,-.116526816,-.380498392,.263971576,.210204772808869,-2.0571383477584,-.974679434480896,-.374384741177081,.350115188418455,-1.44768833894508,-1.19373363863133,-1.19893058805496,-.723973708800591,-.7696196041295,.0772971071081939,1.31414456777677,-.521749194749951,-.724490058419616,.260494036125864,.0658627325836015,-.959797958537171,-.761792086501639,-.715595150189023,-.0942559792034179,10
22 +
Social resilience.csv
Author
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1 +xwiki:XWiki.Admin
Size
... ... @@ -1,0 +1,1 @@
1 +9.1 KB
Content
... ... @@ -1,0 +1,22 @@
1 +Case_Number,Case_Name,NGA,SigTempChng,Data_Source,CV_1,DV_1,DV_2,DV_3,DV_4_1,DV_4_2,DV_4_3,DV_1rec,DV_2rec,DV_3rec,DV_4_1rec,DV_4_2rec,DV_4_3rec,M486,M536,TempDiff,ZIV_2_1,ZIV_2_2,ZIV_2_3,ZIV_2_4,ZIV_2_5,ZIV_2_6,ZIV_3_1,ZIV_3_2,ZIV_3_3,ZIV_3_4,ZIV_3_5,ZDV_1rec,ZDV_2rec,ZDV_3rec,ZDV_4_1rec,ZDV_4_2rec,ZDV_4_3rec,ZCE_Index,ZTL_Full_Index,ZDV_Index,SC_Index
2 +ARO-1,Point Peninsula,Ontario,2,1,1,3,3,3,3,3,3,1,1,1,1,1,1,-.016927127,-.760167645,.743240518,-.840819091235472,-.0979589689408756,-.974679434480896,-.374384741177081,-1.40046075367382,.255474412755014,-1.85691899342652,-1.90418387514612,-1.62894084480133,-1.57974550321319,-1.46864503505568,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,-1.68768685032857,-.572138096125522,-.911788253507778,6
3 +ARO-2,Mund,Cahokia,2,1,1,3,3,3,3,2,2,1,1,1,1,2,2,-.035090798,-.737780036,.702689238,-1.89184295527981,-1.07754865834964,-.974679434480896,-.374384741177081,-1.40046075367382,.255474412755014,-1.85691899342652,-1.90418387514612,-1.62894084480133,-1.57974550321319,-1.46864503505568,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,.0658627325836015,.239949489634293,-1.68768685032857,-.910573688367706,-.492287903533862,8
4 +ARO-3,Pioneer/Formative,Gila River,1,1,1,4,3,3,4,4,3,2,1,1,2,2,1,-.020913683,-.765680713,.74476703,.210204772808869,-1.07754865834964,-.974679434480896,-.374384741177081,-.525172782627683,-1.44768833894508,-1.85691899342652,-1.90418387514612,-1.62894084480133,-1.57974550321319,-1.46864503505568,.171410161014361,-.521749194749951,-.724490058419616,.260494036125864,.0658627325836015,-.959797958537171,-1.68768685032857,-.698211530461918,-.284711713663819,9
5 +ARO-4,Monte Alban IIIB and IV,Oaxaca,1,2,2,1,4,3,1,1,1,3,2,1,3,3,3,-.139726824,-.290147404,.15042058,1.26122863685321,.881630720467889,1.94935886896179,.873564396079853,1.22540315946459,1.10705578860506,.795822425754221,.211575986127346,1.08596056320089,.850632194037869,1.62323924927207,1.31414456777677,.968962790249909,-.724490058419616,1.56296421675518,1.38311738425563,1.43969693780576,.913446083678479,1.21637359507207,.990732639737272,15
6 +ARO-5,Early Classic,Tikal,1,1,2,4,3,3,4,5,5,2,1,1,2,3,3,-.138150449,-.290298822,.152148373,-.840819091235472,-.0979589689408756,.974679434480897,-.374384741177081,1.22540315946459,1.10705578860506,.132637070959037,.211575986127346,1.08596056320089,.0405062949541843,.0772971071081939,.171410161014361,-.521749194749951,-.724490058419616,.260494036125864,1.38311738425563,1.43969693780576,.30959540446993,.332329263532853,.334746544338674,12
7 +ARO-6,Early Medieval,Paris Basin,2,2,3,3,3,3,3,3,3,1,1,1,1,1,1,.049944951,-.743630537,.793575488,.210204772808869,-.0979589689408756,2.16422309957864E-016,-.374384741177081,.350115188418455,.255474412755014,.132637070959037,.211575986127346,.180993427200148,.0405062949541843,.0772971071081939,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,.128601977269782,.0572417773107302,-.911788253507778,6
8 +ARO-7,Ostrogoths,Latium,2,1,3,1,5,5,2,2,3,3,3,3,2,2,1,-.015152511,-.705394836,.690242324,1.26122863685321,.881630720467889,.974679434480897,-1.62233387843402,-.525172782627683,-.596106963095032,.795822425754221,.916829273218502,1.08596056320089,1.66075809312155,.0772971071081939,1.31414456777677,2.45967477524977,1.91001924492444,.260494036125864,.0658627325836015,-.959797958537171,.907333492480671,.0623208612742108,.841732899687212,14
9 +ARO-8,Migration,Jutland,2,3,1,2,3,3,4,2,4,2,1,1,2,2,2,-.060387745,-1.065151245,1.0047635,-.840819091235472,-1.07754865834964,-.974679434480896,-.374384741177081,.350115188418455,-1.44768833894508,-.530548283836148,.211575986127346,-.723973708800591,.0405062949541843,.0772971071081939,.171410161014361,-.521749194749951,-.724490058419616,.260494036125864,.0658627325836015,.239949489634293,-.185028520889403,-.727500845961619,-.0847538056352414,10
10 +ARO-9,Brega,Ireland,2,3,2,3,3,3,3,3,3,1,1,1,1,1,1,.014067762,-.499974744,.514042506,1.26122863685321,-2.0571383477584,-.974679434480896,-1.62233387843402,-1.40046075367382,-.596106963095032,-.530548283836148,-.493677300963809,.180993427200148,-.7696196041295,-.695673963973745,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,-.461705145140611,-.898248456764826,-.911788253507778,6
11 +ARO-10,Toledo,Central Spain,2,3,3,4,4,5,1,2,5,2,2,3,3,2,3,.025247981,-.551149754,.576397735,-.840819091235472,-.0979589689408756,1.94935886896179,-.374384741177081,-.525172782627683,.255474412755014,.795822425754221,.211575986127346,1.08596056320089,.0405062949541843,.0772971071081939,.171410161014361,.968962790249909,1.91001924492444,1.56296421675518,.0658627325836015,1.43969693780576,.442232475428966,.0610829496226158,1.01981934722221,15
12 +ARO-11,Rouran Khaganate,Orkhon Valley,2,2,2,1,3,3,1,1,1,3,1,1,3,3,3,-.02555553,-.754695114,.729139584,.210204772808869,-.0979589689408756,-.974679434480896,2.12151353333679,-1.40046075367382,-1.44768833894508,.795822425754221,-.493677300963809,.180993427200148,-.7696196041295,1.62323924927207,1.31414456777677,-.521749194749951,-.724490058419616,1.56296421675518,1.38311738425563,1.43969693780576,.267351639426626,-.264844864982502,.742280642237295,14
13 +ARO-12,Hephthalites,Sogdiana,1,2,2,2,3,2,1,1,1,2,1,2,3,3,3,-.058453975,-.405167154,.346713178,-.840819091235472,.881630720467889,-.974679434480896,2.12151353333679,-1.40046075367382,-.596106963095032,-.530548283836148,.211575986127346,.180993427200148,-.7696196041295,1.62323924927207,.171410161014361,-.521749194749951,.592764593252413,1.56296421675518,1.38311738425563,1.43969693780576,.143128154926783,-.134820331446757,.771367349722232,14
14 +ARO-13,Kofun,Kansai,2,2,3,5,3,3,3,4,4,3,1,1,1,2,2,-.118724839,-.452503118,.333778279,.210204772808869,-.0979589689408756,2.16422309957864E-016,.873564396079853,1.22540315946459,1.95863716445511,.795822425754221,.916829273218502,1.08596056320089,1.66075809312155,1.62323924927207,1.31414456777677,-.521749194749951,-.724490058419616,-1.04197614450346,.0658627325836015,.239949489634293,1.21652192091345,.694975087311258,-.11137643461306,10
15 +ARO-14,Early Imperial,Luoyang,2,2,3,3,3,4,3,5,3,1,1,2,1,3,1,.116577377,-.484981317,.601558694,-1.89184295527981,.881630720467889,2.16422309957864E-016,-.374384741177081,.350115188418455,.255474412755014,.132637070959037,.916829273218502,1.08596056320089,.0405062949541843,.0772971071081939,-.971324245748044,-.521749194749951,.592764593252413,-1.04197614450346,1.38311738425563,-.959797958537171,.450646061888161,-.129834562469256,-.253160927671763,9
16 +ARO-15,Liang,Lower Yangtze,2,3,3,3,3,4,3,3,3,1,1,2,1,1,1,.047728854,-.551956376,.59968523,.210204772808869,.881630720467889,2.16422309957864E-016,-.374384741177081,.350115188418455,.255474412755014,.795822425754221,.916829273218502,1.08596056320089,.850632194037869,-.695673963973745,-.971324245748044,-.521749194749951,.592764593252413,-1.04197614450346,-1.25139191908843,-.959797958537171,.590714098447547,.220506725545524,-.692245811562439,7
17 +ARO-16,Sasania,Susiana,1,2,3,3,3,3,3,3,3,1,1,1,1,1,1,-.090584955,-.490431978,.399847023,1.26122863685321,.881630720467889,.974679434480897,-.374384741177081,.350115188418455,1.10705578860506,.795822425754221,.916829273218502,-.723973708800591,.850632194037869,-.695673963973745,-.971324245748044,-.521749194749951,-.724490058419616,-1.04197614450346,-1.25139191908843,-.959797958537171,.228727244047251,.700054171274738,-.911788253507778,6
18 +ARO-17,Kadamba Empire,Deccan,1,2,3,3,4,4,2,2,4,1,2,2,2,2,2,-.140622492,-.401083838,.260461346,1.26122863685321,.881630720467889,2.16422309957864E-016,-.374384741177081,1.22540315946459,-.596106963095032,.795822425754221,.211575986127346,-.723973708800591,.0405062949541843,-.695673963973745,-.971324245748044,.968962790249909,.592764593252413,.260494036125864,.0658627325836015,.239949489634293,-.0743485931877167,.399628468752263,.192784899349673,11
19 +ARO-18,Gupta Empire,Ganges,1,3,3,3,3,4,4,2,4,1,1,2,2,2,2,-.113309933,-.474442349,.361132415,.210204772808869,.881630720467889,2.16422309957864E-016,.873564396079853,1.22540315946459,.255474412755014,.795822425754221,.916829273218502,.180993427200148,.850632194037869,.0772971071081939,-.971324245748044,-.521749194749951,.592764593252413,.260494036125864,.0658627325836015,.239949489634293,.564314885463787,.57437957692937,-.055667098150304,10
20 +ARO-19,Byzantine,Upper Egypt,1,2,3,1,5,5,2,3,2,3,3,3,2,1,2,-.142966804,-.383099953,.240133149,.210204772808869,.881630720467889,.974679434480897,.873564396079853,.350115188418455,1.10705578860506,.795822425754221,.916829273218502,-.723973708800591,.850632194037869,.0772971071081939,1.31414456777677,2.45967477524977,1.91001924492444,.260494036125864,-1.25139191908843,.239949489634293,.383321458263639,.732875050143504,.822148365770451,14
21 +ARO-20,Jenne-jeno III,Lower Niger,1,2,2,5,3,3,4,4,3,3,1,1,2,2,1,-.116526816,-.380498392,.263971576,.210204772808869,-2.0571383477584,-.974679434480896,-.374384741177081,.350115188418455,-1.44768833894508,-1.19373363863133,-1.19893058805496,-.723973708800591,-.7696196041295,.0772971071081939,1.31414456777677,-.521749194749951,-.724490058419616,.260494036125864,.0658627325836015,-.959797958537171,-.761792086501639,-.715595150189023,-.0942559792034179,10
22 +
Supplement_Data_April2018.csv
Author
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1 +xwiki:XWiki.Admin
Size
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1 +27.7 KB
Content
... ... @@ -1,0 +1,188 @@
1 +SCCS_ID,Language.family,socname,focyear,region,Social_Complexity,ResourceStressFac,Famine,Other_Hazards,Chronic_Scarcity,LS1_Resolved,LS2_Res_IA_2,LS3_Res_IA_2,LS4_Res_IA_2,LS5_Res_IA_2,LS2LS3Sum_IA_2,LS2LS3LS4Sum_IA_2,S1Resolved,S2_Resolved_IA_TR,S3_Resolved_IA_TR,S4_Resolved_IA_TR,SumS2S3_corrected,S5Resolved,S6Resolved,S8Resolved,S2bRes_outside,S3bRes_outside,S4bRes_outside,S5bRes_outside,S6bRes_outside,S2cRes_nonkin,S3cRes_nonkin,S4cRes_nonkin,S5cRes_nonkin,S6cRes_nonkin,LS2d_outside_Res,LS2e_nonkin_Res,LS3d_outside_Res,LS3e_nonkin_Res,LS4d_outside_Res,LS4e_nonkin_Res,LS5d_outside_Res,LS5e_nonkin_Res
2 +1,Khoe-Kwadi,Nama Hottentot,1860,Africa,18,NA,NA,2,NA,1,0,1,NA,NA,1,NA,1,NA,NA,0,NA,1,1,NA,NA,NA,NA,0,NA,NA,NA,NA,1,1,0,0,0,0,NA,NA,NA,NA
3 +2,Kxa,Kung Bushmen,1950,Africa,12,NA,NA,4,3,1,1,1,0,0,2,2,1,1,1,0,2,1,1,1,0,1,NA,1,1,0,0,NA,1,1,0,1,0,1,0,0,0,NA
4 +3,Atlantic-Congo,Thonga,1865,Africa,30,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,1,0,0,1,1,NA,NA,0,NA,NA,0,NA,0,NA,NA,0,NA,NA,NA,NA,NA,NA,NA,NA,NA
5 +4,Atlantic-Congo,Lozi,1900,Africa,30,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
6 +5,Atlantic-Congo,Mbundu,1890,Africa,32,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
7 +6,Atlantic-Congo,Suku,1920,Africa,30,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
8 +7,Atlantic-Congo,Bemba,1897,Africa,28,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
9 +8,Atlantic-Congo,Nyakyusa,1934,Africa,28,-1.099696823,1,2,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,NA,0,NA,NA,0,1,1,NA,NA,1,1,0,1,NA,NA,NA,NA,NA,0
10 +9,Hadza,Hadza,1930,Africa,10,-0.734297595,1,3,1,1,0,NA,NA,NA,NA,NA,1,1,0,NA,1,NA,NA,NA,0,NA,NA,NA,NA,1,NA,NA,NA,NA,0,0,NA,NA,NA,NA,NA,NA
11 +10,Atlantic-Congo,Luguru,1925,Africa,29,NA,NA,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
12 +11,Atlantic-Congo,Kikuyu,1920,Africa,29,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
13 +12,Atlantic-Congo,Ganda,1875,Africa,37,NA,3.5,2,NA,1,0,1,0,1,1,1,1,0,1,0,1,1,NA,NA,NA,0,NA,NA,NA,NA,1,NA,0,NA,0,0,0,1,NA,NA,0,0
14 +13,Atlantic-Congo,Mbuti,1950,Africa,10,-1.465096051,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,0,0,NA,NA,NA,1,1,NA,NA,NA,1,0,1,NA,NA,NA,NA,0,1
15 +14,Atlantic-Congo,Nkundo Mongo,1930,Africa,30,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
16 +15,Atlantic-Congo,Banen,1935,Africa,29,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
17 +16,Atlantic-Congo,Tiv,1920,Africa,29,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
18 +17,Atlantic-Congo,Ibo,1935,Africa,34,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
19 +18,Atlantic-Congo,Fon,1890,Africa,40,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
20 +19,Atlantic-Congo,Ashanti,1895,Africa,34,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
21 +20,Mande,Mende,1945,Africa,32,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
22 +21,Atlantic-Congo,Wolof,1950,Circum-Mediterranean,39,0.497676403,2,3,3,1,1,0,1,0,1,2,1,0,1,1,1,1,1,NA,NA,1,NA,NA,1,NA,0,NA,NA,0,0,1,NA,NA,0,1,NA,NA
23 +22,Mande,Bambara,1902,Africa,38,NA,NA,3,NA,1,NA,NA,1,NA,NA,NA,1,0,1,1,1,1,NA,1,NA,NA,NA,0,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,0,1,NA,NA
24 +23,Atlantic-Congo,Tallensi,1934,Africa,32,0.453084369,2,4,2,1,NA,1,1,1,1,2,1,0,1,1,1,1,1,0,NA,1,1,NA,NA,NA,0,1,NA,NA,NA,NA,1,1,0,0,0,1
25 +24,Songhay,Songhai,1940,Circum-Mediterranean,36,NA,NA,2,NA,1,NA,NA,1,NA,NA,NA,1,0,NA,1,NA,1,NA,1,NA,NA,0,0,NA,NA,NA,1,1,NA,NA,NA,NA,NA,0,0,NA,NA
26 +25,Atlantic-Congo,Pastoral Fulani,1951,Circum-Mediterranean,16,0.499676613,3,3,2,1,0,NA,1,NA,NA,NA,1,0,NA,1,NA,1,NA,1,NA,NA,1,1,NA,NA,NA,0,1,NA,0,0,NA,NA,0,0,NA,NA
27 +26,Afro-Asiatic,Hausa,1900,Circum-Mediterranean,43,1.277067314,4,4,2,1,1,1,1,1,2,3,1,0,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,0,0,NA,1,0,1,0,1
28 +27,Afro-Asiatic,Massa (Masa),1910,Africa,27,-0.275713877,3,2,1,1,0,1,1,0,1,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,0,1,NA,NA
29 +28,Atlantic-Congo,Azande,1905,Africa,31,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
30 +29,Furan,Fur (Darfur),1880,Circum-Mediterranean,37,-0.68770535,2,2,1,1,1,0,1,0,1,2,1,NA,NA,1,NA,1,NA,NA,NA,NA,0,1,NA,NA,NA,1,1,NA,0,NA,NA,NA,0,NA,NA,NA
31 +30,Heibanic,Otoro Nuba,1930,Africa,28,2.097049838,4,4,4,1,0,1,1,1,1,2,1,0,1,0,1,1,NA,1,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,0,0,0,1,0,1,0,1
32 +31,Nilotic,Shilluk,1910,Africa,33,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
33 +32,Blue Nile Mao,Mao,1939,Africa,25,NA,NA,2,1,NA,NA,NA,NA,NA,NA,NA,1,0,1,1,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA
34 +33,Ta-Ne-Omotic,Kaffa (Kafa),1905,Circum-Mediterranean,35,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
35 +34,Nilotic,Masai,1900,Africa,19,NA,3,4,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,0,1,NA,1,1,NA,NA,NA,0,1,1,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,NA,NA
36 +35,Afro-Asiatic,Konso,1935,Circum-Mediterranean,34,NA,2,NA,1,1,NA,1,NA,NA,NA,NA,1,0,1,0,1,1,1,1,NA,NA,NA,NA,NA,NA,1,NA,1,NA,NA,NA,0,1,NA,NA,NA,NA
37 +36,Afro-Asiatic,Somali,1900,Circum-Mediterranean,28,NA,2,2,NA,1,0,1,0,1,1,1,1,0,1,0,1,1,1,NA,NA,NA,NA,1,1,NA,0,NA,1,1,NA,NA,1,1,NA,NA,1,1
38 +37,Afro-Asiatic,Amhara,1953,Circum-Mediterranean,42,-1.053104578,2,1,1,1,0,0,1,1,0,1,1,0,1,1,1,1,1,NA,NA,1,0,1,1,NA,0,1,1,1,0,0,0,0,0,0,0,1
39 +38,Afro-Asiatic,Bogo,1855,Circum-Mediterranean,27,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
40 +39,Nubian,Kenuzi Nubians,1900,Circum-Mediterranean,34,NA,3.5,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
41 +40,Saharan,Teda,1950,Circum-Mediterranean,21,1.685058366,3,4,4,1,0,1,NA,NA,1,NA,1,0,1,0,1,1,1,NA,NA,NA,NA,0,1,NA,NA,NA,1,1,0,0,0,NA,NA,NA,NA,NA
42 +41,Afro-Asiatic,Tuareg,1900,Circum-Mediterranean,26,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
43 +42,Afro-Asiatic,Riffians,1926,Circum-Mediterranean,42,0.132277175,2,2,3,1,0,1,1,1,1,2,1,0,1,0,1,1,1,1,NA,NA,NA,NA,NA,NA,NA,NA,1,1,NA,NA,0,1,0,1,0,1
44 +43,Afro-Asiatic,Egyptians,1950,Circum-Mediterranean,47,NA,NA,4,2,1,NA,1,NA,NA,NA,NA,1,0,1,1,1,1,1,NA,NA,0,0,0,1,NA,0,0,0,1,NA,NA,0,NA,NA,NA,NA,NA
45 +44,Afro-Asiatic,Hebrews,-621,Circum-Mediterranean,46,NA,2,2,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
46 +45,Afro-Asiatic,Babylonians,-1750,Circum-Mediterranean,49,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
47 +46,Afro-Asiatic,Rwala Bedouin,1913,Circum-Mediterranean,23,NA,3,4,NA,1,NA,1,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,NA,NA
48 +47,Turkic,Turks,1950,Circum-Mediterranean,48,1.275067104,3,4,3,NA,0,NA,NA,NA,NA,NA,1,0,NA,1,NA,1,1,NA,NA,NA,0,1,1,NA,NA,0,1,NA,0,0,NA,NA,NA,NA,NA,NA
49 +48,Indo-European,Gheg Albanians,1910,Circum-Mediterranean,36,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
50 +49,Indo-European,Romans,110,Circum-Mediterranean,49,NA,2,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
51 +50,Basque,Basques,1934,Circum-Mediterranean,47,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
52 +51,Indo-European,Irish,1932,Circum-Mediterranean,47,NA,NA,NA,2,1,0,1,1,1,1,2,1,0,1,1,1,1,1,1,NA,NA,1,0,1,NA,1,1,0,1,0,0,0,1,0,1,0,0
53 +52,Uralic,Lapps,1950,Circum-Mediterranean,18,NA,1,1,NA,1,1,0,1,0,1,2,1,1,1,0,2,1,1,NA,0,1,NA,1,1,NA,NA,NA,1,1,0,0,NA,NA,0,0,NA,NA
54 +53,Uralic,Yurak Samoyed,1894,East Eurasia,18,0.865075841,3,4,2,1,NA,NA,1,NA,NA,NA,1,NA,NA,0,NA,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,0,1,NA,NA
55 +54,Indo-European,Russians,1955,Circum-Mediterranean,48,NA,NA,4,1,1,1,0,1,0,1,2,1,0,NA,0,NA,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,0,NA,0,1,NA,NA,0,1,NA,NA
56 +55,Abkhaz-Adyge,Abkhaz,1880,Circum-Mediterranean,36,NA,NA,3,1,1,0,1,1,0,1,2,1,NA,NA,1,NA,1,1,1,NA,NA,NA,0,1,NA,NA,NA,1,1,NA,NA,0,1,1,1,NA,NA
57 +56,Indo-European,Armenians,1843,Circum-Mediterranean,43,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
58 +57,Indo-European,Kurd,1951,Circum-Mediterranean,43,NA,1,1,NA,1,0,NA,NA,NA,NA,NA,1,0,0,1,0,1,1,NA,NA,NA,0,0,NA,NA,NA,1,1,NA,0,0,NA,NA,NA,NA,NA,NA
59 +58,Indo-European,Basseri,1958,East Eurasia,25,-1.099696823,1,2,1,1,1,1,0,0,2,2,1,0,0,1,0,1,NA,0,NA,NA,1,1,NA,NA,NA,1,1,NA,0,0,0,NA,NA,NA,NA,NA
60 +59,Indo-European,Punjabi (West),1950,East Eurasia,45,0.499676613,3,3,2,1,0,1,1,1,1,2,1,0,1,1,1,1,1,NA,NA,0,0,0,1,NA,1,1,1,1,NA,NA,1,1,1,1,1,1
61 +60,Dravidian,Gond,1938,East Eurasia,27,-1.465096051,1,1,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,NA,NA,0,NA,1,1,NA,1,NA,1,1,0,NA,NA,NA,NA,NA,0,1
62 +61,Dravidian,Toda,1900,East Eurasia,19,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
63 +62,Austroasiatic,Santal,1940,East Eurasia,31,NA,NA,2,3,1,NA,NA,NA,1,NA,NA,1,0,0,1,0,1,NA,NA,NA,NA,0,1,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,NA,0,1
64 +63,Indo-European,Uttar Pradesh,1945,East Eurasia,50,NA,NA,2,NA,0,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,NA,NA,NA,NA
65 +64,Burushaski,Burusho,1934,East Eurasia,33,NA,NA,1,2,1,1,0,1,1,1,2,1,NA,NA,NA,NA,NA,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,1,NA,NA,1,0,0,1
66 +65,Turkic,Kazak,1885,East Eurasia,30,0.294680982,3,3,1.5,1,0,1,1,1,1,2,1,NA,NA,0,NA,1,1,NA,NA,NA,NA,0,1,NA,NA,NA,1,1,0,0,0,0,0,NA,0,NA
67 +66,Mongolic,Khalka Mongols,1920,East Eurasia,32,NA,2,4,NA,1,1,1,1,0,2,3,1,0,1,NA,1,NA,1,NA,NA,1,NA,NA,1,NA,1,NA,NA,1,0,NA,1,1,1,1,NA,NA
68 +67,Sino-Tibetan,Lolo,1910,East Eurasia,35,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
69 +68,Sino-Tibetan,Lepcha,1937,East Eurasia,32,-1.465096051,1,1,1,1,0,NA,1,1,NA,NA,1,0,NA,1,NA,1,1,NA,NA,NA,1,1,1,NA,NA,1,1,1,NA,NA,NA,NA,0,1,0,1
70 +69,Sino-Tibetan,Garo,1955,East Eurasia,31,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
71 +70,Sino-Tibetan,Lakher,1930,East Eurasia,31,NA,3,3,NA,1,NA,1,NA,NA,NA,NA,1,0,1,0,1,1,0,NA,NA,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,NA
72 +71,Sino-Tibetan,Burmese,1965,East Eurasia,48,NA,NA,NA,1,1,0,0,1,1,0,1,1,1,0,1,1,1,1,NA,0,NA,1,NA,1,1,NA,1,1,1,NA,NA,NA,NA,0,1,0,1
73 +72,Austroasiatic,Lamet,1940,East Eurasia,19,0.134277385,3,2,2,NA,NA,NA,NA,NA,NA,NA,1,0,1,0,1,1,NA,NA,NA,0,NA,0,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA
74 +73,Austroasiatic,Vietnamese,1930,East Eurasia,47,NA,1,4,NA,1,0,1,0,0,1,1,1,0,NA,1,NA,1,1,NA,NA,NA,NA,0,0,NA,NA,NA,1,NA,0,0,0,1,0,0,NA,NA
75 +74,Austronesian,Rhade,1962,East Eurasia,29,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
76 +75,Austroasiatic,Khmer,1292,East Eurasia,46,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
77 +76,Tai-Kadai,Siamese,1955,East Eurasia,50,-0.734297595,1,3,1,1,0,1,1,1,1,2,1,0,1,1,1,1,NA,NA,NA,0,0,0,NA,NA,1,1,1,NA,0,0,0,1,0,1,0,NA
78 +77,Austroasiatic,Semang,1925,East Eurasia,12,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
79 +78,Austroasiatic,Nicobarese,1870,East Eurasia,27,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
80 +79,Great Andamanese,Andamanese,1860,East Eurasia,14,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
81 +80,Indo-European,Vedda,1860,East Eurasia,16,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
82 +81,Austronesian,Tanala,1925,East Eurasia,27,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
83 +82,Austronesian,Negri Sembilan,1958,East Eurasia,45,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
84 +83,Austronesian,Javanese,1954,Insular Pacific,49,NA,1,3,NA,1,0,1,1,1,1,2,1,0,0,1,0,1,NA,NA,NA,NA,1,0,NA,NA,NA,1,1,NA,0,0,0,1,1,1,0,1
85 +84,Austronesian,Balinese,1958,Insular Pacific,48,NA,NA,2,1,1,0,1,0,1,1,1,1,0,0,1,0,0,0,NA,NA,NA,0,NA,NA,NA,NA,1,NA,NA,0,0,0,1,NA,NA,0,1
86 +85,Austronesian,Iban,1950,Insular Pacific,23,NA,NA,2,NA,1,0,0,1,1,0,1,1,0,1,1,1,1,NA,NA,NA,0,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,1,0,0,0
87 +86,Austronesian,Badjau,1963,Insular Pacific,15,NA,NA,1,1,1,0,1,0,1,1,1,1,0,0,1,0,1,NA,NA,NA,NA,0,1,NA,NA,NA,0,1,NA,0,0,0,0,NA,NA,0,1
88 +87,Austronesian,Toradja,1910,Insular Pacific,28,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
89 +88,North Halmahera,Tobelorese,1900,Insular Pacific,31,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
90 +89,Timor-Alor-Pantar,Alorese,1938,Insular Pacific,30,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
91 +90,Tiwi,Tiwi,1929,Insular Pacific,12,-1.465096051,1,1,1,1,0,1,0,1,1,1,1,0,1,0,1,1,1,NA,NA,1,NA,1,1,NA,0,NA,NA,0,0,0,0,NA,NA,NA,NA,NA
92 +91,Pama-Nyungan,Aranda,1896,Insular Pacific,13,NA,2,2,NA,1,NA,1,NA,NA,NA,NA,1,NA,NA,1,NA,1,NA,NA,NA,NA,0,0,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA
93 +92,Nuclear Trans New Guinea,Orokaiva,1925,Insular Pacific,20,NA,1,NA,2,1,0,1,1,1,1,2,1,1,0,0,1,1,1,NA,0,NA,NA,1,1,NA,NA,NA,NA,1,0,0,0,1,0,1,1,1
94 +93,Kolopom,Kimam,1960,Insular Pacific,22,NA,3,4,NA,1,1,0,1,0,1,2,1,0,1,0,1,1,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,0,1,NA,NA
95 +94,Nuclear Trans New Guinea,Kapauku,1955,Insular Pacific,29,NA,1,NA,1,1,0,1,0,1,1,1,1,NA,NA,NA,NA,1,1,NA,NA,NA,NA,1,1,NA,NA,NA,1,1,0,0,0,0,NA,NA,0,0
96 +95,Sepik,Kwoma,1960,Insular Pacific,28,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
97 +96,Austronesian,Manus,1937,Insular Pacific,26,-1.465096051,1,1,1,1,0,1,0,1,1,1,1,0,NA,0,NA,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,NA,0,0,NA,0,NA,NA,1,1
98 +97,Austronesian,New Ireland,1930,Insular Pacific,26,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
99 +98,Austronesian,Trobrianders,1914,Insular Pacific,26,1.277067314,4,4,2,1,0,1,1,0,1,2,1,0,1,1,1,1,NA,NA,NA,1,NA,1,NA,NA,1,NA,0,NA,NA,NA,0,1,0,NA,NA,NA
100 +99,South Bougainville,Siuai,1939,Insular Pacific,27,NA,3,NA,1,1,1,0,1,1,1,2,1,0,1,0,1,1,1,NA,NA,NA,NA,NA,0,NA,NA,NA,1,1,0,1,NA,NA,0,0,0,0
101 +100,Austronesian,Tikopia,1930,Insular Pacific,28,0.865075841,3,4,2,1,1,1,0,0,2,2,1,1,1,1,2,1,1,NA,0,1,NA,1,NA,NA,1,NA,0,0,0,0,0,0,NA,NA,NA,NA
102 +101,Austronesian,Pentecost,1953,Insular Pacific,23,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
103 +102,Austronesian,Mbau Fijians,1840,Insular Pacific,32,NA,NA,1,1,1,0,1,0,1,1,1,1,NA,NA,0,NA,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,1,NA,NA,NA,0,NA,NA,NA,NA,1
104 +103,Austronesian,Ajie,1845,Insular Pacific,26,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
105 +104,Austronesian,Maori,1820,Insular Pacific,24,1.275067104,3,4,3,1,1,1,1,1,2,3,1,0,1,0,1,1,1,NA,NA,1,NA,1,1,NA,NA,NA,1,1,0,0,0,NA,1,1,1,1
106 +105,Austronesian,Marquesans,1800,Insular Pacific,27,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
107 +106,Austronesian,Western Samoans,1829,Insular Pacific,28,0.043093106,2,4,1,1,0,1,0,1,1,1,1,NA,NA,0,NA,1,1,NA,NA,NA,NA,NA,1,NA,NA,NA,1,1,NA,NA,0,1,NA,NA,0,1
108 +107,Austronesian,Gilbertese,1890,Insular Pacific,29,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
109 +108,Austronesian,Marshallese,1900,Insular Pacific,29,0.499676613,3,3,2,1,0,1,1,1,1,2,1,1,0,NA,1,0,1,NA,0,NA,NA,NA,1,1,NA,NA,NA,1,NA,NA,1,1,0,NA,0,NA
110 +109,Austronesian,Trukese,1947,Insular Pacific,28,NA,NA,2,NA,1,1,1,0,0,2,2,1,1,1,1,2,1,1,1,0,1,NA,NA,1,0,0,1,1,1,0,0,0,1,NA,NA,NA,NA
111 +110,Austronesian,Yapese,1910,Insular Pacific,32,NA,NA,4,NA,1,0,1,0,1,1,1,1,NA,NA,1,NA,1,1,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,1,1
112 +111,Austronesian,Palauans,1947,Insular Pacific,29,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
113 +112,Austronesian,Ifugao,1910,Insular Pacific,31,-0.734297595,1,3,1,1,0,1,1,0,1,2,1,0,1,0,1,1,1,1,NA,0,NA,1,NA,NA,1,NA,NA,NA,NA,NA,0,0,0,0,NA,NA
114 +113,Austronesian,Atayal,1930,Insular Pacific,27,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
115 +114,Sino-Tibetan,Chinese,1936,East Eurasia,50,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
116 +115,Tungusic,Manchu,1915,East Eurasia,36,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
117 +116,Koreanic,Koreans,1947,East Eurasia,48,0.132277175,2,2,3,1,0,1,0,1,1,1,1,NA,NA,0,NA,1,1,NA,NA,NA,NA,0,1,NA,NA,NA,1,1,NA,NA,0,1,NA,NA,0,1
118 +117,Japonic,Japanese,1950,East Eurasia,50,NA,1,2,NA,1,0,0,0,1,0,0,1,0,1,1,1,1,1,NA,NA,0,1,0,NA,NA,NA,1,1,NA,0,0,0,0,0,0,1,1
119 +118,Ainu,Ainu,1880,East Eurasia,17,-0.643113316,2,1,2,1,0,1,1,1,1,2,1,0,1,0,1,1,1,NA,NA,1,NA,1,NA,NA,1,NA,1,NA,0,0,0,1,0,0,1,1
120 +119,Nivkh,Gilyak,1890,East Eurasia,19,0.911668086,4,3,2,1,0,1,1,1,1,2,1,NA,1,0,NA,1,1,1,NA,0,NA,0,1,NA,1,NA,1,1,NA,NA,0,0,0,0,0,0
121 +120,Yukaghir,Yukaghir,1850,East Eurasia,17,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
122 +121,Chukotko-Kamchatkan,Chukchee,1900,East Eurasia,18,-0.322306122,2,3,1,1,NA,NA,1,NA,NA,NA,1,0,1,1,1,1,1,NA,NA,1,NA,1,1,NA,1,NA,1,1,NA,NA,NA,NA,0,0,NA,NA
123 +122,Athapaskan-Eyak-Tlingit,Ingalik,1885,North America,19,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
124 +123,Eskimo-Aleut,Aleut,1800,North America,21,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
125 +124,Eskimo-Aleut,Copper Eskimo,1915,North America,16,1.277067314,4,4,2,1,1,NA,NA,NA,NA,NA,1,1,1,NA,2,NA,1,NA,0,1,NA,NA,1,0,1,NA,NA,1,0,NA,NA,NA,NA,NA,NA,NA
126 +125,Algic,Montagnais,1910,North America,15,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
127 +126,Algic,Micmac,1650,North America,17,NA,2,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
128 +127,Algic,Saulteaux,1930,North America,20,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
129 +128,Athapaskan-Eyak-Tlingit,Slave,1940,North America,18,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
130 +129,Athapaskan-Eyak-Tlingit,Kaska,1900,North America,14,NA,2,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
131 +130,Athapaskan-Eyak-Tlingit,Eyak,1890,North America,16,NA,1,1,NA,1,1,1,1,0,2,3,1,1,0,0,1,1,1,NA,0,NA,NA,1,NA,1,NA,NA,1,NA,0,0,0,1,0,1,NA,NA
132 +131,Haida,Haida,1875,North America,23,NA,NA,1,1,1,NA,1,NA,NA,NA,NA,1,0,NA,0,NA,1,1,NA,NA,NA,NA,1,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA
133 +132,Salishan,Bellacoola,1880,North America,22,-1.465096051,1,1,1,1,0,1,1,0,1,2,1,0,1,1,1,1,1,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,NA,0,NA,NA,NA
134 +133,Salishan,Twana,1860,North America,22,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
135 +134,Algic,Yurok,1850,North America,18,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
136 +135,Pomoan,Pomo (Eastern),1850,North America,22,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
137 +136,Yokutsan,Yokuts (Lake),1850,North America,21,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
138 +137,Uto-Aztecan,Paiute (North.),1870,North America,14,NA,2,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
139 +138,Klamath-Modoc,Klamath,1860,North America,14,-0.277714088,2,2,2,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,0,NA,1,1,1,NA,NA,NA,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
140 +139,Kutenai,Kutenai,1890,North America,18,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
141 +140,Algic,Gros Ventre,1880,North America,18,NA,2,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
142 +141,Siouan,Hidatsa,1836,North America,24,-0.277714088,2,2,2,1,NA,NA,1,NA,NA,NA,1,0,1,1,1,1,1,NA,NA,1,NA,0,1,NA,1,NA,1,1,NA,NA,NA,NA,0,1,NA,NA
143 +142,Caddoan,Pawnee,1867,North America,25,1.273066893,2,4,4,1,NA,NA,NA,1,NA,NA,1,0,1,1,1,NA,1,NA,NA,0,NA,NA,1,NA,1,NA,NA,1,NA,NA,NA,NA,NA,NA,0,0
144 +143,Siouan,Omaha,1860,North America,25,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
145 +144,Iroquoian,Huron,1634,North America,28,NA,4,4,NA,1,0,1,1,0,1,2,1,0,1,1,1,1,1,1,NA,0,0,0,NA,NA,1,1,1,NA,NA,NA,0,0,0,0,NA,NA
146 +145,Muskogean,Creek,1800,North America,29,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
147 +146,Natchez,Natchez,1718,North America,32,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
148 +147,Uto-Aztecan,Comanche,1870,North America,17,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
149 +148,Athapaskan-Eyak-Tlingit,Chiricahua,1870,North America,15,NA,1,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
150 +149,Zuni,Zuni,1880,North America,35,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
151 +150,Cochimi-Yuman,Havasupai,1918,North America,20,NA,NA,4,NA,NA,NA,NA,NA,NA,NA,NA,1,1,0,1,1,NA,1,NA,NA,NA,NA,NA,NA,1,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA
152 +151,Uto-Aztecan,Papago,1910,North America,27,0.865075841,3,4,2,1,1,0,1,1,1,2,1,1,1,1,2,1,1,1,0,1,1,0,1,0,0,NA,0,1,0,1,NA,NA,NA,0,0,1
153 +152,Uto-Aztecan,Huichol,1890,North America,28,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
154 +153,Uto-Aztecan,Aztec,1520,North America,44,NA,4,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
155 +154,Mixe-Zoque,Popoluca,1940,North America,29,NA,1,NA,1,1,0,1,0,1,1,1,1,0,NA,1,NA,1,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,1,NA,NA,NA,0,1,NA,NA,0,1
156 +155,Mayan,Quiche,1930,South America,35,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
157 +156,Misumalpan,Miskito,1921,South America,27,NA,NA,1,1,1,0,1,1,1,1,2,1,1,0,1,1,1,1,NA,0,NA,1,0,1,1,NA,1,1,1,0,0,0,0,0,NA,0,1
158 +157,Chibchan,Bribri,1917,South America,23,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
159 +158,Chibchan,Cuna (Tule),1927,South America,33,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
160 +159,Arawakan,Goajiro,1947,South America,20,0.453084369,2,4,2,1,0,1,1,1,1,2,1,0,1,1,1,1,1,1,NA,NA,NA,1,NA,NA,NA,1,1,1,0,0,0,1,0,1,NA,0
161 +160,Indo-European,Haitians,1935,South America,45,1.273066893,2,4,4,1,1,NA,NA,NA,NA,NA,1,1,1,1,2,1,0,NA,NA,0,NA,0,NA,NA,1,NA,1,NA,0,1,NA,NA,NA,NA,NA,NA
162 +161,Cariban,Callinago,1650,South America,26,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
163 +162,Warao,Warrau,1935,South America,16,NA,NA,4,NA,1,0,1,NA,NA,1,NA,1,0,1,0,1,1,0,NA,NA,0,NA,NA,NA,NA,1,NA,NA,NA,0,0,0,1,NA,NA,NA,NA
164 +163,Yanomamic,Yanomamo,1965,South America,18,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
165 +164,Cariban,Carib (Barama),1932,South America,18,-0.322306122,2,3,1,1,0,1,0,1,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,0,0,NA,NA,0,0
166 +165,Indo-European,Saramacca,1928,South America,26,NA,2,2,NA,1,0,1,1,1,1,2,1,0,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,0,NA,NA,1,1,0,1,0,1
167 +166,Tupian,Mundurucu,1850,South America,21,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
168 +167,Tucanoan,Cubeo (Tucano),1939,South America,20,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
169 +168,Barbacoan,Cayapa,1908,South America,24,-1.465096051,1,1,1,1,0,1,0,1,1,1,1,NA,NA,1,NA,NA,1,NA,NA,NA,0,NA,1,NA,NA,1,NA,1,NA,NA,1,0,NA,NA,1,1
170 +169,Chicham,Jivaro,1920,South America,18,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
171 +170,Pano-Tacanan,Amahuaca,1960,South America,18,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
172 +171,Quechuan,Inca,1530,South America,36,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
173 +172,Aymaran,Aymara,1940,South America,34,NA,NA,4,4,1,0,0,1,1,0,1,1,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,0,0,NA,NA,0,0,NA,1
174 +173,Tupian,Siriono,1942,South America,14,-1.055104788,1,1,2,1,1,0,0,1,1,1,1,0,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,NA,NA,NA,NA,0,0
175 +174,Nambiquaran,Nambicuara,1940,South America,16,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
176 +175,Trumai,Trumai,1938,South America,20,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
177 +176,Nuclear-Macro-Je,Timbira,1915,South America,23,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
178 +177,Tupian,Tupinamba,1550,South America,24,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
179 +178,Nuclear-Macro-Je,Botocudo,1884,South America,11,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
180 +179,Nuclear-Macro-Je,Shavante,1958,South America,15,NA,NA,1,1,1,0,0,1,1,0,1,1,1,0,0,1,1,NA,NA,0,NA,NA,0,NA,0,NA,NA,1,NA,0,0,NA,NA,0,0,0,1
181 +180,Nuclear-Macro-Je,Aweikoma,1932,South America,11,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
182 +181,Tupian,Cayua,1890,South America,16,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
183 +182,Lengua-Mascoy,Lengua,1889,South America,18,NA,NA,4,NA,1,NA,1,NA,NA,NA,NA,1,0,1,0,1,1,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,NA,NA,NA,NA,NA
184 +183,Guaicuruan,Abipon,1750,South America,19,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
185 +184,Araucanian,Mapuche,1950,South America,33,0.08568493,1,3,3,1,1,0,1,1,1,2,1,NA,NA,1,NA,1,1,1,NA,NA,NA,1,NA,NA,NA,1,1,1,0,0,NA,NA,1,0,1,0
186 +185,Chonan,Tehuelche,1870,South America,16,NA,NA,4,1,1,1,1,0,0,2,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,0,0,0,0,NA,NA,NA,NA
187 +186,Yámana,Yahgan,1865,South America,11,-0.368898366,1,4,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,0,NA,NA,NA,1,1,NA,NA,NA,1,0,1,NA,NA,NA,NA,1,1
188 +
Supplement_Data_April2018.sav
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Supplementary data ReadMeRevised2.pdf
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ThrIndS_Combined_ann.xlsx
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ThrIndS_tmin_combined.xlsx
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Variables in subdiv_data_rev2020.xlsx
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WCS_ARO.spv
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WCS_ARO.spv [Document1].pdf
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WCS_readme.txt
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1 +The nine files here provide all the data and supporting information for Peter N. Peregrine "Social resilience to climate change during the Late Antique Little Ice Age: A replication study."
2 +
3 +Codebook. This is the codebook for the project for which this study is only one part. As such there are many variables in the codebook not present in the analyzed data.
4 +
5 +It should be noted that the dependent variables in the codebook are all scored on a five-point scale. These were re-coded into a three-point scale for analysis using the following formula:
6 +
7 +1=3 (Much)
8 +2=2 (Some)
9 +3=1 (None)
10 +4=2 (Some)
11 +5=3 (Much)
12 +
13 +Social Change Data (csv) contains all the data used in the analysis in csv format. Again, not all the variables listed in the codebook are included, only those used in the study. In addition, however, are both the original and recoded versions of the dependent variables, as well as the standardized versions of the independent variables used to create the Corporate-Exclusionary and Looseness-Tightness indexes.
14 +
15 +Social Change Data (SPSS) contains the data used in the analysis in SPSS format. This format provides full variable titles and score labels.
16 +
17 +SPSS Output (pdf) and (SPSS) are identical. They latter is an SPSS output file. All the analyses reported in the article are given in these files, indcluding the code used to create the indices, the factor analyses of those indices, and the full Bayesian analyses.
18 +
19 +The Raw Coding Data Excel file contains all the supporting information for each coded value.
20 +
21 +The Raw Coding Data Bibliography Excel file contains the bibliographic notes for each piece of supporting information in the Raw Coding Data file.
22 +
23 +The Raw Coding Data RDF file contains both the supporting information for each coded value and linked bibliographic notes in RDF triplestore format.
24 +
25 +The Raw Coding Data RDF Ontology file contains the ontology associated with the Raw Coding Data RDF triplestore file.
26 +
allfactors.xlsx
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climaterawdata.csv
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1 +Case_Number,Case_Name,NGA,Data_Source,CV_2_2_2,CV_2_3_1,DV_1rec,DV_2rec,DV_3rec,DV_4_1rec,DV_4_2rec,DV_4_3rec,SC_Index,M486,M536,TempDiff,SigTempChng,ACEZscore,PNASZscore,ACE_Rnd_Dist,PNAS_Rnd_Dist
2 +ARO-1,Point Peninsula,Ontario,IBSS,210-239,11-20%,None,None,None,None,None,None,6,-.016927127,-.760167645,.743240518,Temperature Change,-49.5454545454545,-4994,6.00000672321271,6.00002008527001
3 +ARO-2,Mund,Cahokia,IBSS,210-239,0-10%,None,None,None,None,Some,Some,8,-.035090798,-.737780036,.702689238,Temperature Change,-47.5454545454545,-4992,6.00000986603562,6.000014718347
4 +ARO-3,Pioneer/Formative,Gila River,IBSS,0 days,0-10%,Some,None,None,Some,Some,None,9,-.020913683,-.765680713,.74476703,No Temperature Change,-46.5454545454545,-4991,6.0000090080266,6.0000291002972
5 +ARO-4,Monte Alban IIIB and IV,Oaxaca,Seshat,180-209,11-20%,Much,Some,None,Much,Much,Much,15,-.139726824,-.290147404,.15042058,No Temperature Change,-40.5454545454545,-4985,6.00000870241031,6.00001840191182
6 +ARO-5,Early Classic,Tikal,IBSS,300-329,11-20%,Some,None,None,Some,Much,Much,12,-.138150449,-.290298822,.152148373,No Temperature Change,-43.5454545454545,-4988,6.00000331858103,6.00001991157593
7 +ARO-6,Early Medieval,Paris Basin,Seshat,210-239,11-20%,None,None,None,None,None,None,6,.049944951,-.743630537,.793575488,Temperature Change,-49.5454545454545,-4994,6.00000363859332,6.0000281814298
8 +ARO-7,Ostrogoths,Latium,IBSS,270-299,0-10%,Much,Much,Much,Some,Some,None,14,-.015152511,-.705394836,.690242324,Temperature Change,-41.5454545454545,-4986,6.000008857778,6.00001871580242
9 +ARO-8,Migration,Jutland,ARO,210-239,11-20%,Some,None,None,Some,Some,Some,10,-.060387745,-1.065151245,1.0047635,Temperature Change,-45.5454545454545,-4990,6.00001588199576,6.00001808861078
10 +ARO-9,Brega,Ireland,ARO,300-329,21-30%,None,None,None,None,None,None,6,.014067762,-.499974744,.514042506,Temperature Change,-49.5454545454545,-4994,6.00000932829195,6.0000241726212
11 +ARO-10,Toledo,Central Spain,ARO,180-209,0-10%,Some,Some,Much,Much,Some,Much,15,.025247981,-.551149754,.576397735,Temperature Change,-40.5454545454545,-4985,6.00000885894241,6.00001411519869
12 +ARO-11,Rouran Khaganate,Orkhon Valley,Seshat,60-89,0-10%,Much,None,None,Much,Much,Much,14,-.02555553,-.754695114,.729139584,Temperature Change,-41.5454545454545,-4986,6.00000877460378,6.00001997933567
13 +ARO-12,Hephthalites,Sogdiana,Seshat,60-89,0-10%,Some,None,Some,Much,Much,Much,14,-.058453975,-.405167154,.346713178,No Temperature Change,-41.5454545454545,-4986,6.00000582278536,6.00002634680446
14 +ARO-13,Kofun,Kansai,Seshat,270-299,0-10%,Much,None,None,None,Some,Some,10,-.118724839,-.452503118,.333778279,Temperature Change,-45.5454545454545,-4990,6.00001513811508,6.00001169102576
15 +ARO-14,Early Imperial,Luoyang,Seshat,240-269,11-20%,None,None,Some,None,Much,None,9,.116577377,-.484981317,.601558694,Temperature Change,-46.5454545454545,-4991,6.00000686063956,6.00001831687876
16 +ARO-15,Liang,Lower Yangtze,ARO,270-299,11-20%,None,None,Some,None,None,None,7,.047728854,-.551956376,.59968523,Temperature Change,-48.5454545454545,-4993,6.00000838915802,6.00001532216351
17 +ARO-16,Sasania,Susiana,Seshat,120-149,0-10%,None,None,None,None,None,None,6,-.090584955,-.490431978,.399847023,No Temperature Change,-49.5454545454545,-4994,6.00000357326582,6.00001811270818
18 +ARO-17,Kadamba Empire,Deccan,Seshat,180-209,0-10%,None,Some,Some,Some,Some,Some,11,-.140622492,-.401083838,.260461346,No Temperature Change,-44.5454545454545,-4989,6.00000451317762,6.00001316517603
19 +ARO-18,Gupta Empire,Ganges,ARO,150-179,0-10%,None,None,Some,Some,Some,Some,10,-.113309933,-.474442349,.361132415,No Temperature Change,-45.5454545454545,-4990,6.00001364702006,6.00002688459726
20 +ARO-19,Byzantine,Upper Egypt,Seshat,0 days,0-10%,Much,Much,Much,Some,None,Some,14,-.142966804,-.383099953,.240133149,No Temperature Change,-41.5454545454545,-4986,6.00001264609965,6.00002812809028
21 +ARO-20,Jenne-jeno III,Lower Niger,Seshat,90-119,0-10%,Much,None,None,Some,Some,None,10,-.116526816,-.380498392,.263971576,No Temperature Change,-45.5454545454545,-4990,6.00001210211626,6.00001266655795
22 +
climatetemperature.csv
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1 +Year,Kadamba,Gupta,Wei,Liang,Kansai,Rouran,Hephthalites,Sasania,Ontario,Cahokia,Hohokam,Maya,MonteAlban,Paris,Jutland,Brega,JenneJeno,Egypt,Susa,Latium,Toledo,Average,prepost536
2 +525,-.109408,-.660033,.386344,.102179,-.0847318,.289367,.554856,.156971,-.0927177,-.135895,-.240736,.0390853,-.0393096,.0653293,-.271834,.0981758,-.0393096,-.118636,.156971,-.336748,-.135895,-.0198083476190476,1
3 +526,-.735678,-.980051,-.832177,-.960864,-.303903,-.823382,-1.17039,-.583939,-.669726,-.490205,-.662117,-.993171,-.953969,-.647976,-.719853,-.557846,-.953969,-.528068,-.583939,-.429911,-.490205,-.71768280952381,1
4 +527,-.011805,-.024066,.00783455,-.112432,-.121225,-.146176,.559105,.143461,-.518651,-.30591,-.0579444,.186839,.144392,-.454923,-.273252,-.302473,.144392,.254786,.143461,-.286065,-.30591,-.0636458023809524,1
5 +528,-.591407,-.0344158,-.514619,-.44566,-.0870013,-.546066,-.363514,-.559559,-.606525,-.402729,-.579822,-.701369,-.598932,-.769673,-.832919,-.41778,-.598932,-.574259,-.559559,-.405858,-.402729,-.504444195238095,1
6 +529,.0873399,.0393551,-.0620017,-.264943,-.338775,.436148,-.238311,-.511665,-.0516001,.0630822,-.182154,.0909187,.181705,-.051049,-.3,-.324843,.181705,-.373198,-.511665,-.144232,.0630822,-.10529050952381,1
7 +530,-.516176,-.724842,.196311,-.324858,-.14872,-.265097,.818901,.217474,.0676108,.0304321,.0384136,-.328699,-.50652,-.0988159,-.529084,-.341559,-.50652,-.0296229,.217474,.038528,.0304321,-.126901771428571,1
8 +531,-.530348,-.932402,-.966907,-.698334,-.630281,-.536716,-1.03858,-.856739,-.381006,-.409797,-.885578,-.908143,-.686835,-.344362,-.0840242,-.0430853,-.686835,-.886704,-.856739,-.489787,-.409797,-.631571404761905,1
9 +532,-.293054,-.633382,-.399671,-.0447705,.226808,-.0897465,-.464483,-.567386,-.0796745,-.250058,-.777467,-.534839,-.6343,.185888,.257419,.275501,-.6343,-.446748,-.567386,-.372544,-.250058,-.290202452380952,1
10 +533,-.210415,.13057,-.0951585,.00175958,.000977749,-.212607,-.62592,-.506965,-.260318,-.298184,-.584938,-.447966,-.0297403,-.226828,-.347936,-.325124,-.0297403,-.15573,-.506965,-.289247,-.298184,-.253269465285714,1
11 +534,-.0215901,.0391562,.290559,-.126187,-.134852,.398902,-.0107837,-.0388575,.145884,.181079,-.00129217,.168327,.152408,.3615,.354422,.294062,.152408,-.0144722,-.0388575,.178614,.181079,.11959562047619,1
12 +535,-.0210308,-.338361,1.28593,.709971,.681205,1.10521,.688383,.0952552,.826572,.572705,.616497,.270539,.32628,.854385,.686411,.920646,.32628,-.0278419,.0952552,.632288,.572705,.518061128571429,1
13 +536,-.383745,-.884111,-.498599,-.509156,-.36006,-.748831,-.324571,-.274253,-.334472,-.196468,-.0815335,-.420347,-.433056,-.591337,-1.01838,-.777334,-.433056,-.248214,-.274253,-.269126,-.196468,-.440827166666667,2
14 +537,-.220431,-.134139,-.155364,-.223393,-.141808,-.21907,-.635118,.0597825,-.386948,-.237821,-.158088,.104836,-.107371,-.716318,-1.5325,-1.29269,-.107371,.00545161,.0597825,-.22339,-.237821,-.309513732857143,2
15 +538,-.393953,-.695633,-.356983,-.536643,-.394598,-.25571,-.195072,-.292607,-.187048,-.142598,.0339795,-.669118,-.641239,-.494774,-.731897,-.694738,-.641239,-.581493,-.292607,-.299694,-.142598,-.409822023809524,2
16 +539,-.210529,-.348252,-.209575,-.0661633,-.134241,-.274808,.00113251,-.350986,-.222398,.0140985,.197676,-.178475,-.272755,-.583344,-.62178,-.604702,-.272755,-.356075,-.350986,-.0647839,.0140985,-.233123937619048,2
17 +540,-.339455,-.381355,-.735902,-.496426,-.418166,-.776472,-.351506,-.446014,-.915009,-.774244,-.789635,-.171723,-.256426,-1.08471,-1.31357,-1.15612,-.256426,-.306438,-.446014,-.869087,-.774244,-.621854380952381,2
18 +541,-.11657,-.166738,-.281156,-.331333,-.277728,-.503015,.00450932,-.0960046,-.294881,-.0961571,.0268986,.080893,-.0446771,-.594294,-1.0916,-.804468,-.0446771,.112702,-.0960046,-.0940959,-.0961571,-.228788265714286,2
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25 +548,-.179324,-.152742,-.546221,-.149177,.05071,-.54031,-.0011892,-.133589,-.524533,-.539726,-.451948,.0399956,-.0826871,-.913576,-1.20037,-.953401,-.0826871,-.0656652,-.133589,-.59764,-.539726,-.366542619047619,
26 +549,-.493098,-.675705,-.233159,-.328588,-.499285,-.904224,-.274727,-.800092,-.179806,.0184094,.103412,-.546464,-.635124,-.533226,-.798727,-.812294,-.635124,-.529493,-.800092,.0232788,.0184094,-.453129447619048,
27 +550,.000742656,-.855865,-.10456,-.479239,-.286171,-.386918,-.107433,.0452135,-.00691962,.111013,-.13495,.204176,.262472,.0760923,-.411376,-.100415,.262472,-.303993,.0452135,-.169269,.111013,-.106128603047619,
28 +551,-.0351996,.118502,-.441082,-.241692,-.573413,-.675063,-.34672,-.246192,-.654782,-.483313,-.314653,.261443,.217334,-.959901,-1.13521,-.937828,.217334,-.199787,-.246192,-.518861,-.483313,-.365647076190476,
29 +552,.115349,.203263,.00178578,.036996,.0535491,-.13867,-.182025,-.045611,-.00269716,.0252463,-.0203739,.18863,.227391,-.36389,-.740806,-.806461,.227391,.12259,-.045611,-.166955,.0252463,-.0612220276190476,
30 +553,-.173378,-.072143,.258507,.149456,-.104243,-.519055,.170046,.457656,.174268,.153514,-.512205,.0633198,.26833,-.0128898,-.542142,.131949,.26833,.0933924,.457656,-.0982016,.153514,.0364609904761905,
31 +554,-.103185,-.0574538,.438893,.24306,.208247,.609837,.588681,-.0922044,.227096,.274639,.381986,.170507,.0607579,.0335459,-.443253,-.28179,.0607579,-.232905,-.0922044,.316374,.274639,.123144052380952,
32 +555,-.247883,-.0863596,-.592586,-.49332,-.443284,-.648233,-.653739,-.467163,-.728281,-.6583,-.549807,-.117414,-.251791,-.851657,-1.01755,-.979466,-.251791,-.126147,-.467163,-.68908,-.6583,-.522824504761905,
33 +556,-.231273,-.92579,-.199358,-.438156,-.366296,-.883839,-.0510092,-.276556,-.438019,-.392195,-.450415,-.184304,-.0105437,-.409006,-.690086,-.420274,-.0105437,-.438402,-.276556,-.493061,-.392195,-.379898933333333,
34 +557,-.252103,-.377353,.0779655,.0161219,-.00995208,-.314777,.154373,-.228246,.159669,.178516,.0491991,-.317127,-.290862,-.0555166,-.613006,-.467465,-.290862,-.391425,-.228246,.158488,.178516,-.136385341904762,
35 +558,-.0491973,.415182,-.546068,-.170833,-.255506,-.741371,-.0932753,-.518807,.108967,.0622072,-.0385518,-.33389,-.152632,.338284,.505732,.336936,-.152632,-.309739,-.518807,.0580576,.0622072,-.0949398285714285,
36 +559,-.177356,-.581628,-.566376,-.329568,-.199078,-.612596,-.46601,-.495606,.0275097,.0254702,.0542205,-.143215,-.209164,-.0904925,-.405753,-.35187,-.209164,-.463136,-.495606,-.0579253,.0254702,-.272470152380952,
37 +560,-.28861,-.334265,.110905,-.155531,.0833819,.0925336,.540187,-.153482,-.180486,.00244396,-.00791114,-.0313543,-.242305,-.448744,-.412649,-.355986,-.242305,-.0845792,-.153482,-.0472117,.00244396,-.109857424761905,
38 +561,.0173375,-.0598442,.194121,.225085,-.0689548,-.289735,-.0229784,.00884813,.44528,.345472,.248522,.00221676,-.084461,.461246,-.111168,.138337,-.084461,-.200373,.00884813,.269394,.345472,.0851525771428572,
39 +562,-.0730026,-.128108,-.251182,-.226511,-.111338,-.189962,-.424138,-.261001,-.408507,-.15584,-.0763695,.0657994,-.01079,-.616828,-.231814,-.285013,-.01079,.166725,-.261001,-.157002,-.15584,-.181072033333333,
40 +563,-.54574,-1.02863,.0717458,-.410678,-.261655,-.355959,-.500836,-.48947,-.586059,-.604498,-1.0797,-.779462,-.793634,-.56169,-.296948,-.0678189,-.793634,-.364406,-.48947,-.736219,-.604498,-.537107576190476,
41 +564,-.39222,-.200166,.340945,.127581,.288133,.0495269,.00381155,-.333816,.219856,-.0500711,.0959955,-.0316194,.173026,.20969,-.320029,.0352055,.173026,-.285627,-.333816,.054126,-.0500711,-.0107863404761905,
42 +565,-.44758,-.696927,-.294589,-.350404,-.581509,-.657909,-.265074,-.631175,-.813762,-.772024,-.910963,-.43803,-.511995,-.962519,-.732421,-.698815,-.511995,-.463242,-.631175,-.881751,-.772024,-.620280142857143,
43 +
coef_var.xlsx
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csdi_combined_ann.xlsx
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gap_fill_sens.zip
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gap_filled_sens.zip
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methods_for_dataset.docx
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readme_final_excel.docx
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readme_final_excel_sens.docx
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readme_final_excel_sens.txt
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1 +Gap-Filled Sensitivity Data
2 +
3 +ThrIndS_Combined_sens.xlsx: Seasonal and annual values of r95, r99, r05, r01, prcptot, r95, r99, r20, r10
4 +ThrIndS_tmin_combined_sens.xlsx: Seasonal and annual values of tmin and fd
5 +ThrIndS_tmax_combined_sens.xlsx: Seasonal and annual values of tmax and su
6 +rx5s_Combined_sens.xlsx: Seasonal and annual values of rx5
7 +rx1s_Combined_sens.xlsx: Seasonal and annual values of rx1
8 +SDIIS_Combined_sens.xlsx: Seasonal and annual values of sdiis
9 +
10 +CDD_CWD_Combined_sens.xlsx: Seasonal CDD and CWD indices (including both hunter/gatherer/pastoral and agricultural societies)
11 +CDD_CWD_Combined_ann_sens.xls: annual CDD and CWD indices
12 +
13 +CSDI_Combined_sens.xlsx: Seasonal CSDI indices (including both hunter/gatherer/pastoral and agricultural societies)
14 +CSDI_combined_ann_sens.xlsx: annual values of CSDI index for each site
15 +WSDI_Combined_sens.xlsx: Seasonal WSDI indices (including both hunter/gatherer/pastoral and agricultural societies)
16 +WSDI_combined_ann_sens.xlsx: annual values of WSDI index for each site
17 +
18 +daily_coef_var_sens.csv � coefficients of variation
19 +
20 +annuals_for_factors_reform_sens.xlsx: values used for factor analysis and resulting factors
21 +
22 +predictability_sens folder: predictability data for each of the variables
23 +
24 +Redone Dry and Dry Predictability Factor Analysis
25 +
26 +Factors_revised_2020.xls
27 +
28 +
29 +
rx1s_Combined_ann.xlsx
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rx5s_Combined_ann.xlsx
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subdiv_data_rev2020.csv
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1 +id,socname,Revised.latitude,Revised.longitude,Variable..Variance.in.monthly.temperature.means,fam_orig,oth_orig,chrs_orig,FC1A,SCCS_Abundance_imp,SCCS_Stability_imp,DepGath_v203,DepHunt_v204,DepFish_v205,DepAnHusb_v206,DepAg_v207,IntensityCultivation_v232,EASubDIvCorr_Rev,SubType,util_rev
2 +1,Nama_Hottentot,-27.5,17,10.59263669,NA,2,NA,0,-1.110426279,-0.151609738,1,3,1,5,0,1,8,Mixed,6
3 +2,Kung_Bushmen,NA,NA,NA,NA,4,3,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
4 +3,Thonga,NA,NA,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
5 +4,Lozi,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
6 +5,Mbundu,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
7 +6,Suku,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
8 +7,Bemba,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
9 +8,Nyakyusa,-9.5,34,7.994229965,1,2,1,0,1.359407527,-0.40857176,0,1,1,2,6,5,8,Intensive_Agr,3
10 +9,Hadza,-3.75,35.18,2.786357605,1,3,1,0,1.038279333,-0.167191931,6,4,0,0,0,1,4,HG,2
11 +10,Luguru,NA,NA,NA,NA,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
12 +11,Kikuyu,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
13 +12,Ganda,0.33,32.5,1.036121133,3.5,2,NA,1,1.039498936,0.521125447,0,1,1,1,7,5,6,Intensive_Agr,8
14 +13,Mbuti,1.5,28.33,0.294615692,1,1,1,1,1.406768811,0.566510396,3,7,0,0,0,1,4,HG,3
15 +14,Nkundo_Mongo,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
16 +15,Banen,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
17 +16,Tiv,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
18 +17,Ibo,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
19 +18,Fon,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
20 +19,Ashanti,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
21 +20,Mende,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
22 +21,Wolof,13.75,-15.33,3.044509334,2,3,3,0,-0.871992271,0.754006776,0,0,1,3,6,3,6,Horticulturalist,6
23 +22,Bambara,12.5,-7,6.772644427,NA,3,NA,0,-0.292002963,0.396749301,2,0,1,2,5,5,10,Agr_past,4
24 +23,Tallensi,10.66,-0.57,3.811400769,2,4,2,0,-0.011906629,0.47055019,1,0,0,2,7,5,6,Intensive_Agr,4
25 +24,Songhai,16.58,-1.67,29.92172658,NA,2,NA,0,-1.541326519,0.228921442,0,0,2,3,5,5,8,Agr_past,2
26 +25,Pastoral_Fulani,15,7.5,20.945364,3,3,2,0,-1.301598485,0.235338483,0,0,0,9,1,2,2,Pastoralist,4
27 +26,Hausa,10.5,7.5,2.752774799,4,4,2,0,0.313676203,0.386406705,1,0,0,3,6,6,6,Intensive_Agr,1
28 +27,Massa_Masa,NA,NA,NA,3,2,1,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
29 +28,Azande,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
30 +29,Fur_Darfur,13.5,25.5,12.98935722,2,2,1,0,-1.242422091,0.158305561,0,0,1,3,6,5,6,Intensive_Agr,1
31 +30,Otoro_Nuba,11.33,30.67,4.111629945,4,4,4,0,-0.724205135,0.59044116,0,2,0,2,6,5,8,Intensive_Agr,1
32 +31,Shilluk,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
33 +32,Mao,9.27,34.67,2.312127458,NA,2,1,0,-0.001028103,0.702238174,1,1,1,1,6,3,8,Horticulturalist,2
34 +33,MISSING_Kafa_Kaffa,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
35 +34,Masai,-3.5,36.75,3.28556643,3,4,NA,0,1.083773715,-0.374438321,0,1,0,9,0,1,2,Pastoralist,2
36 +35,Konso,5.25,37.5,3.600164802,2,NA,1,0,0.026704249,0.272530062,0,0,0,2,8,5,4,Intensive_Agr,1
37 +36,Somali,9,47.25,6.748995934,2,2,NA,0,-1.305540471,0.484723755,0,0,0,9,1,5,2,Pastoralist,5
38 +37,Amhara,12.5,37.75,3.842058505,2,1,1,0,-0.339668453,0.268001654,0,0,1,3,6,5,6,Intensive_Agr,6
39 +38,Bogo,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,2,NA,NA,NA
40 +39,Kenuzi_Nubians,NA,NA,NA,3.5,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
41 +40,Teda,20.5,17.5,45.56660607,3,4,4,0,-2.876038126,0.360967326,2,0,0,3,5,6,8,Agr_past,5
42 +41,Tuareg,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
43 +42,Riffians,34.92,-3.25,35.37451605,2,2,3,0,-1.36930785,-0.19552153,0,1,1,3,5,5,8,Agr_past,8
44 +43,Egyptians,24.75,33,55.98120443,NA,4,2,0,-2.66273082,0.304432609,0,0,1,3,6,6,6,Intensive_Agr,1
45 +44,Hebrews,NA,NA,NA,2,2,1,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
46 +45,Babylonians,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
47 +46,Rwala_Bedouin,33.25,38.5,80.1892964,3,4,NA,0,-2.214468868,-0.28498785,1,1,0,8,0,1,4,Pastoralist,2
48 +47,Turks,39.33,34.25,72.20179292,3,4,3,0,-0.411152163,-0.99179557,0,0,0,4,6,5,4,Intensive_Agr,3
49 +48,Gheg_Albanians,NA,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
50 +49,Romans,NA,NA,NA,2,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
51 +50,Basques,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
52 +51,Irish,53.5,-10,8.422231814,1,1,1,0,-0.030757432,-0.275576766,0,1,0,4,5,5,6,Agr_past,6
53 +52,Lapps,68.7,21.5,91.64819994,1,1,NA,0,-0.766077663,-1.598770422,0,2,2,6,0,1,8,Pastoralist,7
54 +53,Yurak_Samoyed,68,51.5,144.9889046,3,4,2,0,-0.976789891,-1.751425819,0,3,3,4,0,1,8,PrimarilyHG,9
55 +54,Russians,52.67,41.33,133.6090259,NA,4,1,0,0.241671524,-1.818936595,0,0,0,3,7,6,4,Intensive_Agr,3
56 +55,Abkhaz,43.13,40.77,50.15138085,NA,3,1,0,0.085190164,-0.723003519,1,0,0,6,3,5,6,Pastoralist,3
57 +56,Armenians,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
58 +57,Kurd,36.5,44.5,120.0464559,1,1,NA,0,-1.252771783,-0.512474938,0,0,1,4,5,6,6,Agr_past,5
59 +58,Basseri,29,53,88.36224178,1,2,1,0,-1.957393684,-0.029256674,0,1,0,8,1,2,4,Pastoralist,3
60 +59,Punjabi_West,32.5,74,82.82722977,3,3,2,0,-1.213571865,0.153850258,0,0,0,2,8,5,4,Intensive_Agr,1
61 +60,Gond,19.63,80.92,18.28860998,1,1,1,1,-0.213627236,0.349559862,2,1,0,2,5,3,10,Agr_past,5
62 +61,Toda,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
63 +62,Santal,23.5,87.17,33.0366254,NA,2,3,0,-0.441295394,0.305015625,0,1,1,1,7,6,6,Intensive_Agr,6
64 +63,Uttar_Pradesh,25.92,83,50.37229997,NA,2,NA,0,-0.804549287,0.354458988,0,0,0,2,8,6,4,Intensive_Agr,1
65 +64,Burusho,36.43,74.58,135.0992607,NA,1,2,0,-0.639041621,-1.096099997,0,0,0,4,6,6,4,Intensive_Agr,3
66 +65,Kazak,42.5,75.5,119.7090915,3,3,1.5,0,-0.296912891,-1.496695491,0,1,0,8,1,2,4,Pastoralist,3
67 +66,Khalka_Mongols,47.17,96.08,243.6511698,2,4,NA,0,-0.20565455,-1.860169063,0,1,0,8,1,2,4,Pastoralist,3
68 +67,Lolo,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
69 +68,Lepcha,27.5,89,39.42342866,1,1,1,0,1.213261184,-0.499568395,0,1,0,3,6,5,6,Intensive_Agr,3
70 +69,Garo,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
71 +70,Lakher,22.33,93,18.32906196,3,3,NA,1,0.497973312,0.24868449,0,2,1,1,6,3,8,Horticulturalist,4
72 +71,Burmese,22,95.67,16.7040508,NA,NA,1,0,0.025559785,0.20171909,0,0,0,2,8,6,4,Intensive_Agr,3
73 +72,Lamet,20,100.67,20.45249536,3,2,2,1,1.227529072,-0.243632926,1,2,0,2,5,3,10,Agr_past,3
74 +73,Vietnamese,20.5,106.25,31.54052685,1,4,NA,0,0.391418033,-0.121134706,0,0,2,2,6,6,8,Intensive_Agr,4
75 +74,Rhade,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
76 +75,Khmer,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
77 +76,Siamese,14,100.85,8.550653512,1,3,1,0,0.041075496,0.370618684,0,0,1,1,8,6,4,Intensive_Agr,4
78 +77,Semang,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
79 +78,Nicobarese,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
80 +79,Andamanese,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
81 +80,Vedda,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
82 +81,Tanala,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
83 +82,Negri_Sembilan,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
84 +83,Javanese,-7.7,112.22,0.434914972,1,3,NA,0,0.25272541,1.370815876,0,0,0,2,8,6,4,Intensive_Agr,1
85 +84,Balinese,-8.5,115.33,0.554782468,NA,2,1,0,-0.430263798,1.664369789,0,0,0,3,7,6,4,Intensive_Agr,1
86 +85,Iban,2,113,NA,NA,2,NA,1,0.931190849,1.483953279,0,0,2,2,6,3,8,Horticulturalist,4
87 +86,Badjau,5,120,0.219546455,NA,1,1,0,NA,NA,0,0,8,0,2,4,4,PrimarilyHG,2
88 +87,Toradja,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
89 +88,Tobelorese,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
90 +89,Alorese,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
91 +90,Tiwi,-11.38,131,1.691451885,1,1,1,1,NA,NA,5,3,2,0,0,1,8,HG,5
92 +91,Aranda,-24.25,133.5,36.607207,2,2,NA,0,-1.38039561,-0.117636998,6,4,0,0,0,1,4,HG,5
93 +92,Orokaiva,-8.5,148,0.905342429,1,NA,2,1,0.695596149,1.052952599,1,1,2,1,5,4,10,Mixed,8
94 +93,MISSING_Kimam,-7.5,138.5,0.768917344,3,4,NA,0,-0.76201153,1.813735279,2,1,1,0,6,5,8,Intensive_Agr,7
95 +94,Kapauku,-4,136,0.360267781,1,NA,1,1,0.342954258,1.619022709,0,1,1,2,6,3,8,Horticulturalist,11
96 +95,Kwoma,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
97 +96,Manus,-2.17,147.17,0.160421822,1,1,1,0,-1.266562874,2.358705991,0,0,9,1,0,2,2,HG,2
98 +97,New_Ireland,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
99 +98,Trobrianders,-8.54,151.01,0.810055509,4,4,2,1,-1.737923154,2.054854381,1,0,3,1,5,4,8,Mixed,4
100 +99,Siuai,-6.76,155.45,0.2837929,3,NA,1,1,-0.483457234,2.034076463,2,1,0,2,5,4,10,Mixed,4
101 +100,Tikopia,-12.29,168.83,0.642731268,3,4,2,1,NA,NA,0,0,5,0,5,4,4,Mixed,7
102 +101,Pentecost,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
103 +102,Mbau_Fijians,-18,178.58,2.821134649,NA,1,1,1,NA,NA,1,0,5,0,4,4,6,PrimarilyHG,6
104 +103,Ajie,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
105 +104,Maori,-35.33,174.17,9.378743708,3,4,3,1,NA,NA,3,1,2,0,4,3,10,PrimarilyHG,12
106 +105,Marquesans,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
107 +106,Western_Samoans,-13.94,-171.77,0.623528039,2,4,1,1,NA,NA,0,0,3,1,6,4,6,Horticulturalist,2
108 +107,Gilbertese,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
109 +108,Marshallese,6.28,169.49,0.082967644,3,3,2,1,NA,NA,1,0,5,0,4,4,6,PrimarilyHG,4
110 +109,Trukese,7.34,151.6,0.086232883,NA,2,NA,1,NA,NA,0,0,5,0,5,4,4,Mixed,6
111 +110,Yapese,9.52,138.16,0.151060734,NA,4,NA,1,NA,NA,0,0,4,1,5,4,6,Mixed,7
112 +111,Palauans,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,4,NA,NA,NA
113 +112,Ifugao,16.83,121.17,3.017132284,1,3,1,1,-0.047927208,1.079881631,0,2,1,1,6,6,8,Intensive_Agr,4
114 +113,Atayal,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
115 +114,Chinese,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
116 +115,Manchu,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
117 +116,Koreans,37.6,126.42,100.1607204,2,2,3,0,-0.010504153,-0.77598861,0,0,2,2,6,6,8,Intensive_Agr,1
118 +117,Japanese,34.67,133.67,67.50235953,1,2,NA,0,-0.028266043,-0.309220543,0,0,0,1,9,6,2,Intensive_Agr,1
119 +118,Ainu,42.83,143,108.1514634,2,1,2,0,-0.103598293,-1.17498514,2,3,4,0,1,3,10,HG,10
120 +119,Gilyak,53,142,229.6694279,4,3,2,0,0.032461396,-1.825106828,2,3,5,0,0,1,8,HG,4
121 +120,Yukaghir,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
122 +121,Chukchee,66.5,179.6,158.9184121,2,3,1,0,NA,NA,0,2,3,5,0,1,8,Mixed,5
123 +122,Ingalik,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
124 +123,Aleut,NA,NA,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
125 +124,Copper_Eskimo,68.72,-112.53,287.366131,4,4,2,0,-1.33027634,-1.615649901,0,4,6,0,0,1,4,HG,7
126 +125,Montagnais,NA,NA,NA,3,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
127 +126,Micmac,NA,NA,NA,2,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
128 +127,Saulteaux,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
129 +128,Slave,NA,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
130 +129,Kaska,NA,NA,NA,2,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
131 +130,Eyak,60.5,-145,39.3437819,1,1,NA,0,-0.284366587,-1.190743511,2,3,5,0,0,1,8,HG,9
132 +131,Haida,54,-132.5,12.44302066,NA,1,1,0,-0.943756356,-0.404059147,2,2,6,0,0,1,8,HG,4
133 +132,Bellacoola,52.33,-126.5,48.66593005,1,1,1,0,0.162389228,-1.247685718,2,2,6,0,0,1,8,HG,6
134 +133,MISSING_Twana,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
135 +134,MISSING_Yurok,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
136 +135,MISSING_Pomo_Eastern,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
137 +136,Yokuts_Lake,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
138 +137,Paiute_North,NA,NA,NA,2,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
139 +138,MISSING_Klamath,42.63,-121.67,49.63424628,2,2,2,0,0.329048341,-1.076971688,3,2,5,0,0,1,8,HG,6
140 +139,MISSING_Kutenai,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
141 +140,Gros_Ventre,NA,NA,NA,2,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
142 +141,Hidatsa,47,-101,187.5572978,2,2,2,0,-0.2257957,-1.75316834,1,2,1,0,6,5,8,Intensive_Agr,6
143 +142,Pawnee,NA,NA,NA,2,4,4,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
144 +143,MISSING_Omaha,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
145 +144,MISSING_Huron,44.5,-79,134.7726297,4,4,NA,0,0.421468875,-1.69225188,1,1,3,0,5,3,8,Mixed,6
146 +145,Creek,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
147 +146,MISSING_Natchez,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
148 +147,Comanche,NA,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
149 +148,Chiricahua,NA,NA,NA,1,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,2,NA,NA,NA
150 +149,Zuni,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
151 +150,Havasupai,35.83,-112.17,95.48394104,NA,4,NA,0,-0.472718402,-0.972513838,3,2,0,0,5,6,8,Mixed,7
152 +151,Papago,32,-112,62.26395819,3,4,2,0,-1.177386251,-0.186107997,3,2,0,0,5,6,8,Mixed,3
153 +152,Huichol,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
154 +153,Aztec,NA,NA,NA,4,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
155 +154,Popoluca,18.25,-94.83,7.057895546,1,NA,1,1,0.925953627,0.131409526,0,1,1,0,8,3,4,Horticulturalist,4
156 +155,Quiche,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
157 +156,Miskito,15,-83,0.977782661,NA,1,1,1,-0.260933681,1.212561613,3,2,2,1,2,3,14,PrimarilyHG,9
158 +157,Bribri,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
159 +158,Cuna_Tule,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
160 +159,Goajiro,11.92,-71.75,1.224917293,2,4,2,0,-0.40850352,0.825271971,0,1,1,7,1,2,6,Pastoralist,5
161 +160,Haitians,NA,NA,NA,2,4,4,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
162 +161,Callinago,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,5,NA,NA,NA
163 +162,Warrau,9.08,-62,0.782840991,NA,4,NA,1,0.932068444,0.720240232,4,3,2,0,1,2,10,HG,9
164 +163,Yanomamo,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
165 +164,Carib_Barama,7.42,-60.17,1.063731471,2,3,1,1,1.476017453,0.325458982,2,2,2,0,4,3,12,PrimarilyHG,4
166 +165,Saramacca,3.5,-55.75,1.815951677,2,2,NA,1,1.688527752,0.140643056,1,2,2,0,5,3,10,Mixed,4
167 +166,Mundurucu,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
168 +167,Cubeo_Tucano,NA,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
169 +168,Cayapa,1,-79,0.256428972,1,1,1,1,1.262964904,0.772678245,1,1,2,1,5,4,10,Mixed,5
170 +169,Jivaro,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
171 +170,Amahuaca,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
172 +171,Inca,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,6,NA,NA,NA
173 +172,Aymara,-16,-65.75,4.046270155,NA,4,4,0,1.762522666,-0.102535509,0,0,1,3,6,3,6,Horticulturalist,4
174 +173,Siriono,-14.5,-63.5,2.743355668,1,1,2,1,0.89186057,0.413596779,3,5,1,0,1,3,8,HG,6
175 +174,MISSING_Nambicuara,NA,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
176 +175,Trumai,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
177 +176,MISSING_Timbira,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
178 +177,Tupinamba,NA,NA,NA,NA,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
179 +178,MISSING_Botocudo,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
180 +179,Shavante,-13.5,-51.5,3.676206736,NA,1,1,1,0.715858042,0.297210666,4,3,1,0,2,3,10,PrimarilyHG,5
181 +180,Aweikoma,NA,NA,NA,NA,NA,2,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
182 +181,Cayua,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,3,NA,NA,NA
183 +182,Lengua,-23,-58.5,12.59318972,NA,4,NA,1,0.21346346,-0.058906766,2,5,2,0,1,2,10,HG,7
184 +183,Abipon,NA,NA,NA,1,NA,1,NA,NA,NA,NA,NA,NA,NA,NA,1,NA,NA,NA
185 +184,Mapuche,-38.5,-72.58,12.11903845,1,3,3,0,-0.471587071,-0.045734452,1,0,1,2,6,5,8,Intensive_Agr,8
186 +185,Tehuelche,-40.5,-68,36.63056224,NA,4,1,0,-0.900761568,-0.857217141,2,7,1,0,0,1,6,HG,8
187 +186,Yahgan,-55.5,-69.5,3.620117842,1,4,1,0,NA,NA,1,2,7,0,0,1,6,HG,7
188 +
tmax_combined.xlsx
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Copyright 1949-2023 Human Relations Area Files, Yale University
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