Acculturation revisitedA model of personal network change

José Luis MolinaUniversitat Autònoma de Barcelona

Miranda J. LubbersUniversitat Autònoma de Barcelona

Chris McCartyUniversity of Florida

National Science Foundation - BCS-0417429

2

Acculturation ...

We are interested in Acculturation: the consequence of two cultures coming into contact.

… And we think that personal networks can help us to understand this process …

For our example we will look at migrants of Africa and South America moving to Spain

3

Samples of first and second generation immigrants

N %

"Argentina" 84 27,8

"Amazig" 72 23,8

"Dominicano" 64 21,2

"Gambia" 24 7,9

"Guinea Ecuatorial" 11 3,6

"Senegal" 46 15,2

Total 301 100,0

< 1 año 1 año - < 2 años

2 años - <5 años

5 - 10 años > 10 años 2 generacion

Años de residencia

0

10

20

30

40

Po

rcen

taje

Años de residencia

4

Sociocentric and egocentric networks … A sociocentric network refers to the

pattern of relations within a defined (bounded) group.

These could be a corporate office, a classroom of children, a church ...

An egocentric network is the subset of ties surrounding a given ego within the sociocentric network.

So within a corporate office you might want to compare the characteristics of the networks of two staff members.

So, sociocentric and egocentric networks refer to a single social setting.

Alter

Alter

Alter

EgoAlter

5

Personal Networks

A Personal Network is the unconstrained set of network members that surround a person.

Personal networks represent all of the sociocentric networks that a person belongs to (their family, work, clubs, church, etc.).

Typically we use one or more Name Generators to get respondents to list alters, AND a Tie Definition for connecting her alters.

If the list of alters is long enough (30 or more on average) most social settings in which ego participates will be represented (kin, friends, coworkers …).

6

East York … (Wellman, 1999)

KinClose

Extended

Neighbours

Friends Cow orkers

Active closeties

W eak active ties

EastYork

Person

7

Research questions

Do the structure and composition of the personal networks of migrants vary with their years of residence in Spain?

If so ... What are the trends of those changes?

8

Hypothesis (Spanish data) Three stages of acculturation1: one dense cluster, largely consisting of alters

from the country of origin.2: multiple clusters, some primarily from Spain,

some from country of origin, high betweenness.

3: the multiple clusters from stage 2 become interconnected and form 1 loosely connected cluster.

9

Method

For each personal network (excluding ego), we calculated structural and compositional characteristics

´Meta-analysis´ over 250 networks for which we had complete data about composition and structure Bivariate correlations between years of residence and

various network characteristics K-means cluster analysis of various network characteristics

(see slide 13), to identify homogeneous groups of networks ANOVA to relate cluster membership to years of residence

10

Results: Significant bivariate correlations (p < .05) with years of residence

Percentage of alters who are originally from Spain

r = .36

Percentage of alters who live in Spain r = .33

Average age of alters r = .25

Average number of years ego knows alters r = .22

SD number of years ego knows alters r = .18

Diversity of roles r = .13

Average closeness r = -.13

11

Results: Significant bivariate correlations with years of residence.. age effects

Percentage of alters who are originally from Spain

r = .36

Percentage of alters who live in Spain r = .33

Average age of alters r = .25

Average number of years ego knows alters r = .22

SD number of years ego knows alters r = .18

Diversity of roles r = .13

Average closeness r = -.13

12

K-means cluster analysis

Based on the variables (all standardized): Proportion of alters whose country of origin is

Spain Proportion of alters who live in Spain Number of clusters within network Cluster homogeneity regarding living in Spain Density Network betweenness centralization Average frequency of contact (scale 1-7) Average closeness (scale 1-5) Diversity of roles (scale 1-13)

13

Results cluster analysis

Four-cluster solution was best interpretable Characteristics that most contributed to the cluster

partition: Number of clusters, percentage of alters living in Spain,

density, and number of alters originally from Spain.

Cluster sizes: Cluster 1: N = 41 Cluster 2: N = 86 Cluster 3: N = 33 Cluster 4: N = 90

14

Cluster characteristics (a) (unstandardized)

00,10,20,30,40,50,60,70,80,9

1

Cl.1 Cl.2 Cl.3 Cl.4

Proportion ofalters originallyfrom Spain

Proportion ofalters who live inSpain

Clusterhomogeneity

Density

15

Cluster characteristics (b) (unstandardized)

00,5

11,5

22,5

33,5

44,5

5

Cl.1 Cl.2 Cl.3 Cl.4

Number ofclusters

Averagefrequency ofcontact (scale1-7)

Averagecloseness(scale 1-5)

16

Cluster characteristics (c) (unstandardized)

0

5

10

15

20

25

Cl.1 Cl.2 Cl.3 Cl.4

Diversity ofroles (scale 1-13)

Networkbetweennesscentralization

17

Summary of characteristics cluster 1 (N = 41)

On average 1 quite homogeneous cluster High density & low betweenness Low percentages of alters who are originally from

Spain and who live in Spain Relatively low diversity of roles

18

Meet our representative of cluster 1, Senegalese, 1 year in Spain...

19

Meet our representative of cluster 1, Senegalese, 1 year in Spain...

20

Summary of characteristics cluster 2 (N = 86)

On average 1 or 2 rather heterogeneous clusters Low density & high betweenness Somewhat higher percentages of alters who are

originally from Spain and who live in Spain than those in cluster 1

21

Our second representative (cl.2), Dominican, 4 years in Spain...

22

Summary of characteristics cluster 3 (N = 33)

High number of quite homogeneous clusters (4 to 5 on average).

The whole network is more heterogeneous with respect to alters´ country of origin and alters´ country of living.

Very low density.

23

Representative of cluster 3, from Argentina, also 4 years in Spain

24

Summary of characteristics cluster 4 (N = 90)

On average 1 to 2 rather homogeneous clusters

High betweenness Relatively high average frequency of contact Highest percentages of alters who are

originally from and live in Spain

25

Representative of cluster 4, Moroccan, 14 years in Spain

26

Is partition related to years of residence?

ANOVA: F (3, 229)= 4,932 p = .002

Post hoc tests Cl. 2 & 3 n.s. Cl. 3 & 4 n.s.

0

1

2

3

4

5

6

7

Cl. 1 Cl. 2 Cl. 3 Cl. 4

Average years of residence

27

Is years of residence a predictor of cluster membership?

Multinominal logistic regression YES; years of residence predicts cluster

membership Sex and employment status did not have a

significant effect (and neither did age) Country of origin, however, influenced

cluster membership significantly: e.g., Senegambians had a higher probability to be in cluster 1 than the others

28

How do personal networks change over time?

Cluster 1

Cluster 2

Cluster 3

Cluster 4

Years of residence

29

One option would be...

Cluster 1

Cluster 2

Cluster 3

Cluster 4

Years of residence

30

Need for a longitudinal model

To investigate whether there are different trajectories of network change, depending on (e.g.) culture and entry situation

At the disaggregated level: investigate which alter characteristics (such as centrality), ego-alter characteristics (such as closeness to ego, role in ego’s network), or alter-alter characteristics (such as similarity country of origin) predict future edges

31

Longitudinal study ...

The ECRP Project (Dynamics of actors and networks across levels: individuals, groups, organizations and social settings) will allow us to perform two more waves to a selection of informants from each cluster and study the evolution of their personal networks in order to test the model …

… and gain a better understanding of the sources of change in personal networks, beliefs and behaviors.

32

Thanks!