Multilevel networks and world
ethnography
Doug White and UC+ team
SFI noon seminar 12:15
Wed, Sept 1, 2010
UC+=UCI_imbs+UCSD_econ+sfi, project team
Scott D. White, UCI , One Spot
Halbert White UCSD
Karim Chalak BU, Econ
B. Tolga Oztan, IMBS
and aunt
Assist from
Judea Pearl
UCLA
Laura Fortunato, SFI
Ren Feng. Xi’an
Xiaotung Univ.
Tony Eff, MS, Econ
Language families
Folded image: Core, Semi-periphery1, SP2, Periphery1-2
Core
Semi-Peri1
Semi-Peri2
Periphery1
Periphery2
A structurally endogamous kinship network core of
a Turkish nomad clan
(White and Johansen 2005: 379; 76-79).
Standard Cross-Cultural Sample
(wikipedia page maps by Tony Eff
Afro-Eurasia drawn to a
slightly smaller scale
Causal graph, Pearl’s regression method
“Say for three variables you are trying to estimate the direct
effect c of X on Z given an indirect effect of Y. The causal
diagram model gives you a license to do it by the regression
method, where, for example
E(y|x, z) – E(y|x´, z)
a
X Y
c = —————————————
(1)
c
b
x – x´
,
Z
Controlling for the change from x to x´, E(y|x, z) and E(y|x´,
z) are the changes in variable Z due to unit changes in X
controlling for Y.” (email from Pearl see Pearl 2000:151;
Chalak and White 2010). Because the x,z in (y|x,z) is a joint
distribution, eqn (1) means that x→x´ changes y which
through the x-y-x path, considered as a joint distribution,
changes z. From this it follows, given the single door
criterion (Pearl 2000:150). that c + a•b = rxy.z, the coef for
total effect of X on Z.
Solving Galton’s problem, Two stage OLS
Two stage regression with peer effects (different notation)
Stage 1
Calculate the
Instruments
Stage 2 use
Instruments
in OLS
X1
X2
Y
13 linked regressions out of 2000+ SCCS variables
http://eclectic.ss.uci.edu/~drwhite/courses/SCCCodes.htm
Nodes are variables in regression analyses of variables from the Standard Cross-Cultural Sample of 186 societies (SCCS).
Lines represent independent variables. They point down to 13 dependent variables in successive colored layers.
Black lines are positive effects, red lines negative effects from regression results.
Colors of nodes for variables show depth in a causal hierarchy with net effects estimated as causal graphs (Pearl 2000).
At level 4 the Evil eye dependent variable has a triangular relationship with money and milked domestic animals.
The regressions control for peer effects of spatial transmission (distance) and cultural transmission (language phylogeny),
incorporated as Instrumental Variables in a second-stage regression, with the IVs estimated in a first-stage regression.
Node sizes reflect the significance of spatial transmission peer effects. Language effects are sometimes negative.
v1189 Belief in evil eye
v238 Moral gods==4
238.
HIGH GODS
18
. = Missing data
68
1 = Absent or not reported
47
2 = Present but not active in human affairs
13
3 = Present and active in human affairs but not supportive
of human morality
40
4 = Present, active, and specifically supportive of human morality
v1189 Belief in evil eye (dichotomy)
Large nodes red
Small nodes orange
155. SCALE
77
14
43
27
25
v155 True money==5
7- MONEY (here, an independent variable)
1 = None
2 = Domestically usable articles
3 = Alien currency
4 = Elementary forms
5 = True money
v1189 Belief in evil eye
v272 Caste stratification
272. CASTE STRATIFICATION (ENDOGAMY) (two cases have secondary
castes)
5 . = Missing data
(154) 0 = (Omitted from map) Absent or insignificant
17 1 = Despised occupational group(s)
3 2 = Ethnic stratification
7 3 = Complex
v1189 Belief in evil eye
v245 Milked animals
v1189 Belief in evil eye
Model 1
Description Re: Evil eye
Eff-Dow
coef
pvalue
-0.247
0.775
NA
(Intercept)
VIF
Var.
Probit
coef
1.1715
0.12
0.6944
0.00004
-0.2267
0.38
Wy fydd
Spatial transmission
0.763
.0000022
3.452
NA
Wy fyll
Cultural transmission
-0.228
0.362
2.329
NA
Milk
Milking of animals
0.664
0.080
2.328
245
*
0.3235
0.48
CaststratLDg
Degree of caste stratification
1.372
0.017
1.225
272
**
0.5078
0.04
Money >1>3>4
Degree of monetization
0.597
0.017
1.152
155~v17
**
0.1011
0.05
Moral gods
Degree of morality of gods
0.294
0.020
1.664
238
**
0.1161
0.04
Diagnostics
Fstat
df
***
pvalue
pvalue
Fstat
RESET test. H0: model has right functional form
3.400
1801.470
0.065
0.717
0.397
Wald test. H0: appropriate variables dropped
0.476
308.949
0.491
0.431
0.512
Breusch-Pagan test. H0: residuals homoskedastic
1.193
3282.405
0.275
8.753
0.003
16.146
9268.270
0.000
3.618
0.057
LM test. H0: Cultural lag (language) not needed
0.713
1877017.
0.398
1.086
0.297
LM test. H0: Spatial lag (distance) not needed
1.768
20982.58
0.184
2.214
0.137
Shapiro-Wilk test. H0: residuals normal
Notes: R2 = 0.513; N=186; number of imputations=10; standard errors and R2 adjusted for two-stage least squares.
“***” p-value ≤ 0.01, “**” p-value ≤0.05, “*” p-value ≤ 0.10. Language non-significant (p > .33).
v155 Money
Model 2
Description Re: Money
(Intercept)
Eff-Dow
coef
pvalue
-0.775
VIF
Var.
Probit
coef
Pvalue
0.002
NA
0.2316
.0000279
3.644
NA
***
0.9057
3.758
***
-0.9220
4.309
0.1005
1.228
Wy fydd
Spatial transmission
0.954
Wy fyll
Cultural (language) transmission
-0.928
0.003
4.190
NA
Foodtrade
Imported food
0.430
0.134
1.219
819
Fratgrpstr
Fraternal interest group strength+
0.120
0.092
1.840
570
*
0.1663
1.757
Milk
Milking of animals
-0.393
0.012
1.560
245
*
-0.2394
1.478
Caststrat LGd
Degree of caste stratification+,++
0.430
0.134
1.219
272
Moral gods
Degree of morality of gods+.++
0.102
0.142
1.502
238
0.1021
0.142
Popdens
Population density
0.206
.0000053
1.552
156
0.3147
1.627
Superjh PCsize
Supra cmnty jurisdictional hier.
0.304
.0000002
1.633
Diagnostics
RESET test. H0: model has right functional form
Fstat
df
pvalue
237
***
***
Fstat
1.943
5301.617
0.163
2.187
0.139
Wald test. H0: appropriate variables dropped
15.266
17.503
0.001
13.332
0.000
Breusch-Pagan test. H0: residuals homoskedastic
13.833
950.560
0.000
4.995
0.027
Shapiro-Wilk test. H0: residuals normal
0.267
282.276
0.606
0.363
0.548
LM test. H0: Cltural lag (language) not needed
1.287
657642.
0.257
1.773
0.183
LM test. H0: Spatial lag (distance) not needed
1.352
991.504
0.245
1.902
0.168
Notes: R2 = 0.490; N=186; number of imputations=10; standard errors and R2 adjusted for two-stage least squares.
“***” p-value ≤ 0.01, “**” p-value ≤0.05, “*” p-value ≤ 0.10. Language non-significant (p > .33).
Probit note: R2 = 0.481; IV(distance)=0.9911; (language)=0.9957 see last two columns for coef and pvalue.
v238 Moral gods
Model 3
Description Re: Moral gods
(Intercept)
Eff-Dow
coef
pvalue
VIF
Var.
Probit
Coef
0.725
0.477
NA
0.917
.00000003
2.526
NA
***
pvalue
1.076
0.166
0.881
.0000007
-.471
0.311
Fydd
Spatial transmission
Fyll
Cultural-language-transmission
-0.700
0.140
2.579
NA
PCAP
PC Agricultural potential
-0.038
0.075
1.148
921
*
-.097
0.059
PCsize
PC Juris. Hierarchy
0.554
0.035
23.844
63^2
**
0.212
0.002
PCsize2
PC Juris. Hierarchy squared
-0.076
0.107
23.404
245
0.344
0.022
Milk
Milking of animals
0.403
0.065
2.287
245^2
0.135
0.031
Foodstress
Chronic food stress
0.207
0.152
1.103
1685
-.190
0.003
Eextwar
Frequency of external war
-0.032
0.006
1.124
1650
-.187
0.024
bridewealth
Bridewealth payments
0.194
0.221
1.307
208=1
0.155
0.146
caststratLgd
Log of Caste stratification
0.704
0.030
1.276
272
0.183
0.035
Diagnostics
Fstat
Df
Pvalue
*
**
**
Fstat
RESET test. H0: model has right functional form
0.236
182.981
0.628
0.287
0.593
Wald test. H0: appropriate variables dropped
1.602
24.460
0.217
1.958
0.165
Breusch-Pagan test. H0: residuals homoskedastic
3.115
121.839
0.080
2.133
0.144
Shapiro-Wilk test. H0: residuals normal
7.527
1106.014
0.006
1.201
0.273
LM test. H0: Cultural lag (language) not needed
1.486
29167.282
0.223
1.228
0.268
LM test. H0: Spatial lag (distance) not needed
0.921
46574.050
0.337
0.809
0.368
Notes: R2 = 0.504; N=186; number of imputations=10; standard errors and R2 adjusted for two-stage least squares.
“***” p-value ≤ 0.01, “**” p-value ≤0.05, “*” p-value ≤ 0.10. Language non-significant (p > .33).
Probit note: R2 = 0.481; IV(distance)=0.9942; (language)=0.9861 see last two columns for coef and pvalue.
Table 4: Transmission effects (Galton’s problem): Spatial and cultural
Peer Effect
Spatial
Transmission
(Distance)
Cultural
Transmission
(Language)
Variable
Money
Moral gods
Evil eye
Money
Moral gods
Evil eye
coef
.960
.824
.767
-.988
-.672
-.228
pvalue
.0000009
.0000014
.000002
.002
p > 0.14
p > 0.36
The negative peer effects for language indicate that, for each of these dependent
variables, there is a tendency, strong for Money and weak for the other two variables, NOT to
be the result of cultural tradition but of innovation that differentiates the societies with
Money, Moral gods and Evil eye from the norms in their respective language families. This
tendency is nearly significant (pvalue < 0.15) for societies with Moral gods.
Figure 3: Causal graph with multiple triangular regression coefficients,
excluding peer effects (numbers are the regression coefficients)
-0.393
Milking animals A
B Money (v155)
(v245)
0.484
0.102 p<0.14
Moral gods D
(v238)
0.294
0.792
0.430
0.597
0.664
1.372
C Evil eye (v1188)
Caststrat LGd E
Table 6: Causal graph total effects and bivariate table regression slopes
Independent
Variable
Dependent
Variable
Money
Moral gods
Milking
Evil eye
Evil eye
Evil eye
Net effects=Direct and Indirect Causal
=Tota Fig.
Graph Effects
l
Slope
effects
0.597
0.597 .741
0.294+(0.102*.597)
0.355 .950
0.664+(-.393*.597)+(.484*.104*.597)
0.744 .810
Moral gods
Milking
Money
Money
0.102
-.393+(0.484*.102)
0.102
-0.344
.482
.244
Other kinds of cross-cultural data structures and analyses:
Statistical Entailment Analyses:
Society sets for variables tend to form chains of sets
Galois duality lattice (Concept lattices):
Society sets for variables tend to form chains of sets
and intersections, and opposite ordering of
Sets of variables that tend to form chains of sets
VS1 VS2 VS3 VS4
A B C D
A B C D
Intrasocietal network structure overlays on genealogy
For each society these will define new variables such as
1) sidedness, reciprocal marriage to opposites.
2) structurally endogamous groups
3) marriage-type census as against random simulation
4) distribution of structural features over generations
Multilevel analysis e.g. regional or world system effects
local societies.
on
Fig. 3: An exact world
entailment digraph for the
sexual division of labor
Late Task A Early Task B
Female
Male
Female
Male
Fig. 3: An exact world
ethnographic lattice of kin
avoidances has a four-dimensional
partial ordering of distributions: 1)
parents of Hu, Wi (opp/same sex,
within circles), 2) siblings and
siblings-in-law of Hu and Wife
(opp/same sex, in parallelograms),
3) opposite sex siblings & parents
siblings & parallel cousins (White
1995). Lower types of avoidances
entail upper ones features in
perfect inclusion relations, found
by statistical entailment analysis
(White 1999b). Of the 250
societies, names attached to each
node show each subset of
avoidance relations.
Table 1
Pajek Repast Simulation
X
X
Peer Effects
ArcGIS.com
New Codes
New Ethnogr. Cases
X
X
3
400 foragers2
X
X
(Binford & Boehm)
85 World-system 3
X
X
1294 Atlas4
X
X
0
186 SCCS5
28 1945-19656
30 Post 19657
X
X
0
X
X
X
28 (SCCS)
X
X
X
308 (eSCCS)
80KinSources1
X
Cohesion
2
(country data)
1 http://kinsource.net/kinsrc/bin/view/KinSources archives kinship network data
contributed by anthropologists. Only three KS ethnographies remain for conversion from
paper-based genealogies to e-networks for analysis with Pajek, but others will be added.
2,5 Binford’s (2001) Constructing Frames of Reference forager database has been
spreadsheeted by Boehm and Hill. Non-foragers from the SCCS will be analyzed separately.
Extensive testing of “peer effects” methods have established their validity.
3 Smith and White (1992) have postwar WS commodity flow time series in 5yr intervals;
capital and migration flow will be added.
4 Murdock’s Ethnographic Atlas (EA) in Spss format has been supplemented by newly
authored installments 30-31.
5 Murdock and White’s (1969) Standard Cross-Cultural Sample dataset on 186 societies in
Spss and R formats has coded data contributions from 80+ different authors on 2008+
variables. Citations to SCCS are now 95+/year and growing.
Table 1
80 KinSources1
Pajek
X
Repast Simulation
X
Cohesion
X
Peer Effects
ArcGIS.com
New Codes
New Ethnogr. Cases
X
X
3
400 foragers2
X
X
(Binford & Boehm)
85 Wrld-system3
X
X
1294 Atlas4
X
X
0
186 SCCS5
X
X
0
28 1945-19656
X
X
X
28 (SCCS)
30 Post 19657
X
X
X
308 (eSCCS)
2
(country data)
5 Murdock and White’s (1969) Standard Cross-Cultural Sample dataset on 186 societies in
Spss and R formats has coded data contributions from 80+ different authors on 2008+
variables. Citations to SCCS are now 95+/year and growing.
6 109 missing codes for 28 SCCS variables 1006-1115 will be coded for 28 SCCS societies on
the world-system impacts variables partially coded in White and Burton’s (1985-1988) NSF
8507685 funded research on “World-Systems and Ethnological Theory.”
7 To bring the SCCS societies up to date for post-1965 societies, 30 well described post-1965
ethnographic cases will be added to an (expanded) eSCCS and coded for EA variables and
the CDC Cultural Diversity Codebook of 180 SCCS variables.
8 Given that the SCC Sample was published in 1969, the eSCCS additions to the sample will
bring it up to date temporally. This will allow study of world-system impacts on 37 welldescribed ethnographic cases in the contemporary post-war period.
A structurally endogamous kinship network core of
a Turkish nomad clan (White and Johansen 2005:
379; 76-79).
Fig. 1.A. Gmap of Cultural Survival
(2010) 100+ recent trouble spot
study cases: Gmaps extend to
networks at the global level,
clicking into cases at the local level.
Live: http://bit.ly/c1funC
Fig. 1.B. This google map tracks
cases of swine flu in 2009, types of
cases are color coded, fatal cases
have no dot, clicking a region gives
a more detailed map of cases within
the region.
Similarly, Wolf (1982) drills down at several
hundred ethnographically data points to
analyze how commodity exchange affected
indigenous societies in the 1500-1980 period
of overseas conquest and modern worldsystems.
Interactive maps provide for drilling down
from a network at one level (network spread
of disease not shown here) by clicking a node
to see a more detailed map or a network
within that node. The upper level nodes can
be societies with organizations networks
reached by a click of a given node.