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Acculturation revisited A model of personal network change

Acculturation revisited A model of personal network change. José Luis Molina Universitat Aut ò noma de Barcelona Miranda J. Lubbers Universitat Aut ò noma de Barcelona Chris McCarty University of Florida. National Science Foundation - BCS-0417429. Acculturation .

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Acculturation revisited A model of personal network change

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  1. Acculturation revisitedA model of personal network change José Luis Molina Universitat Autònoma de Barcelona Miranda J. Lubbers Universitat Autònoma de Barcelona Chris McCarty University 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

  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.

  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)

  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 acculturation 1: 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

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

  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)

  15. Cluster characteristics (b)(unstandardized)

  16. Cluster characteristics (c)(unstandardized)

  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.

  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 2 Cluster 1 Cluster 4 Cluster 3 Years of residence

  29. One option would be... Cluster 2 Cluster 1 Cluster 4 Cluster 3 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!

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