Migration-trust Networks

Migration-trust Networks

Social Cohesion in Mexican US-bound Emigration

eBook - 2013
Rate this:
Texas A & M Univ
In an important new application of sociological theories, Nadia Y. Flores-Yeffal offers fresh insights into the ways in which social networks function among immigrants who arrive in the United States from Mexico without legal documentation. She asks and examines important questions about the commonalities and differences in networks for this group compared with other immigrants, and she identifies “trust” as a major component of networking among those who have little if any legal protection.

Revealing the complexities behind social networks of international migration, Migration-Trust Networks: Social Cohesion in Mexican US-Bound Emigration provides an empirical and theoretical analysis of how social networks of international migration operate in the transnational context. Further, the book clarifies how networking creates chain migration effects observable throughout history.

Flores-Yeffal’s study extends existing social network theories, providing a more detailed description of the social micro- and macrodynamics underlying the development and expansion of social networks used by undocumented Mexicans to migrate and integrate within the United States, with trust relationships as the basis of those networks. In addition, it incorporates a transnational approach in which the migrant’s place of origin, whether rural or urban, becomes an important variable. Migration-Trust Networks encapsulates the new realities of undocumented migration from Latin America and contributes to the academic discourse on international migration, advancing the study of social networks of migration and of social networks in general.


Texas A
& M Univ

In an important new application of sociological theories, Nadia Y. Flores-Yeffal offers fresh insights into the ways in which social networks function among immigrants who arrive in the United States from Mexico without legal documentation. She asks and examines important questions about the commonalities and differences in networks for this group compared with other immigrants, and she identifies “trust” as a major component of networking among those who have little if any legal protection.

Revealing the complexities behind social networks of international migration, Migration-Trust Networks: Social Cohesion in Mexican US-Bound Emigration provides an empirical and theoretical analysis of how social networks of international migration operate in the transnational context. Further, the book clarifies how networking creates chain migration effects observable throughout history.

Flores-Yeffal’s study extends existing social network theories, providing a more detailed description of the social micro- and macrodynamics underlying the development and expansion of social networks used by undocumented Mexicans to migrate and integrate within the United States, with trust relationships as the basis of those networks. In addition, it incorporates a transnational approach in which the migrant’s place of origin, whether rural or urban, becomes an important variable.Migration-Trust Networks encapsulates the new realities of undocumented migration from Latin America and contributes to the academic discourse on international migration, advancing the study of social networks of migration and of social networks in general.


Publisher: College Station : Texas A & M University Press, ©2013
Edition: 1st ed
ISBN: 9781603449632
1603449639
Characteristics: 1 online resource (xxi, 200 pages) : illustrations

Opinion

From the critics


Community Activity

Comment

Add a Comment

There are no comments for this title yet.

Age Suitability

Add Age Suitability

There are no age suitabilities for this title yet.

Summary

Add a Summary

There are no summaries for this title yet.

Notices

Add Notices

There are no notices for this title yet.

Quotes

Add a Quote

There are no quotes for this title yet.

Explore Further

Recommendations

Subject Headings

  Loading...

Find it at WPL

  Loading...
[]
[]
To Top