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An Interval Graph Method for Cross-Cultural Comparison of Life Histories* Sean Fitzhugh 1 , Carter Butts 1,2 , Joy Pixley 1 MURI AHM 6.03.2011 1 Department of Sociology: University of California, Irvine 2 Institute of Mathematical Behavioral


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An Interval Graph Method for Cross-Cultural Comparison of Life Histories*

Sean Fitzhugh1, Carter Butts1,2, Joy Pixley1

MURI AHM 6.03.2011

1 Department of Sociology: University of California, Irvine 2 Institute of Mathematical Behavioral Sciences: University of California, Irvine

*This material is based on research supported by the Office of Naval Research under award N00014-08-1-1015

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Outline

 Introduction to interval graphs  Exploratory results  Future directions

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MURI

 Several MURI projects advance methods in analysis of a

single, large graph

 Focus here is analysis and comparison of large numbers

(i.e. thousands) of graphs

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Introduction: Life History Concepts

 Lives are composed of a series of subintervals (spells)

and life history is the collection of these spells

 Start and end dates of spells (school, work, marriages,

etc) allow for surprisingly deep insight into one’s life

 Timing of spells has lasting impact on timing (or even

existence) of subsequent spells (Elder 1998)

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Introduction: Why Networks?

 We need a method for analyzing life history which

preserves maximal information on context and timing of spells

 Butts and Pixley (2004): Structural approach to

representing life history data

 Understand life history as a series of intervals and their

temporal overlap

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Introduction: Why Networks?

 Interval graph: takes a set of spells as the vertex set and

coterminousness as the edge set (Butts and Pixley 2004)

 Why are we interested in spell simultaneity?

 When activities are coterminous, they are linked together

in a meaningful way

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Introduction: Why Networks?

 Example: Four lives

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Introduction: Why Networks?

 Example: Four lives

 School

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Introduction: Why Networks?

 Example: Four lives

 School  School + Work

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Introduction: Why Networks?

 Example: Four lives

 School  School + Work  School + Work + Marriage

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Introduction: Why Networks?

 Example: Four lives

 School  School + Work  School + Work + Marriage  School + Work + Marriage + Children

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Introduction: Why Networks?

 Example: Four lives

 School  School + Work  School + Work + Marriage  School + Work + Marriage + Children

 Context is important!

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Methods: Interval Graphs

 How do we construct an interval graph?

School School School Work Work Marriage Children Children

Time:

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Methods: Interval Graphs

 How do we construct an interval graph?

School School School Work Work Marriage Children Children

Time:

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Methods: Interval Graphs

School 1 School 2 School 3 Work 1 Work 2 Marriage Child 1 Child 2 School 1 1 School 2 1 School 3 1 1 Work 1 1 1 1 Work 2 1 1 1 1 Marriage 1 1 1 1 1 1 Child 1 1 1 1 1 1 Child 2 1 1 1 1

  • Interval graph: tie indicates coterminousness
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Methods: Interval Graph Comparison

 Comparison across multiple lives:

 Construct an interval graph for each actor  Find the graph distances between all actors

 Direct comparison is inappropriate here: spells are

not comparable across domains

 We must use a partial labeling function to identify

which sets of vertices (spells) are equivalent in our comparison (Butts and Carley, 2005)

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Methods: Interval Graphs

School 1 School 2 School 3 Work 1 Work 2 Marriage Child 1 Child 2 School 1 1 School 2 1 School 3 1 1 Work 1 1 1 1 Work 2 1 1 1 1 Marriage 1 1 1 1 1 1 Child 1 1 1 1 1 1 Child 2 1 1 1 1

  • Exchangeability list: we treat spells within domains as

comparable and allow permutation within domains

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Methods: Interval Graph Comparison

 Distance matrix: n x n matrix where the (i,j) cell is

the distance between i and j

 In this context, graph distance corresponds to

differences in life histories

 Use multidimensional scaling (MDS) to visualize the

distances

 MDS represents similarities and differences among a

set of items as Euclidean distances in k-dimensional space (Kruskal and Wish 1978)

 Actors grouped together in MDS space have similar

life histories

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Data

 Retrospective life history data: individuals provide start

and end dates for a variety of spells

 Vietnam Life History Survey (Hirschman et al., 1991)  Wisconsin Longitudinal Study (Hauser and Sewell,

2010)

 Life Histories and Social Change in Contemporary China

(Treiman and Walder, 1998)

 Domains of interest: education, work, marriage,

children, military participation

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Results: Vietnam

 MDS: Banding is explained by number of children

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Results: Vietnam

 MDS: Within bands, actors are primarily differentiated

by military participation

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Results: Vietnam

 Which covariates explain patterning?

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Results: Vietnam

 What is associated with differences in lives?

 Family size  Military

 Might we see differences in China?

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Results: China

 Number of children and CCP membership explain much

  • f the differences among lives
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Results: China

 Gender and farming are associated with differences

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Results: China

 3D plots allow us to explore further

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

No schooling/illiterate Primary school Middle school

University

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Results: China

 We can see a spectrum of education levels here

No schooling/illiterate Primary school Middle school

University

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Results: China

 What is associated with differences in lives?

 Family size  Education  Party membership  Gender  Involvement in agriculture

 What patterns might we see in the United States?

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Results: United States

 Jobs instead of children!

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Results: United States

 Some differences between those with 0/1 and 2+

marriages…

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Results: United States

 Back to the 3D plots

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

Attended college Did not attend college

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Results: United States

 College education plays an important role in

differentiating lives

Attended college Did not attend college

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Results: United States

 More 3D plots

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

Military participation No military participation

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Results: United States

 Military participation also differentiates American lives

Military participation No military participation

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Results: United States

 One more plot

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

Male Female

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Results: United States

 Distinct clustering according to gender

Male Female

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Results: United States

 What is associated with differences in American lives?

 Employment  Education  Military  Marriages  Gender

 Any common themes?

 Where and why might family life play a bigger role in

differentiating people’s lives? Why would we expect education/work to play a role in other cases? In which cases would military participation matter?

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Future Directions

 More data! Eastern European cases: Russia, Poland,

several other former Soviet States

 Model-based scaling to overcome sampling issues

(missingness, censoring)

 Application of latent variable models

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Thank you!

An Interval Graph Method for Cross-Cultural Comparison

  • f Life Histories

Sean Fitzhugh, Carter Butts, Joy Pixley sean.fitzhugh@uci.edu