Binational Social Networks and Assimilation

Mouw, Ted; Chávez, Sergio Jorge; Edelblute, Heather; Verdery, Ashton M.

doi:10.1525/sp.2014.12192

Cited by 43 publications

(18 citation statements)

References 103 publications

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“…Given the results presented here, this does not appear to be the case because the variance estimators are so biased as to be effectively meaningless. However, further work may correct these issues, and other approaches to RDS estimation and diagnostic [ 10 , 13 , 24 , 39 , 40 , 43 , 44 ] and chain referral sampling [ 11 , 42 , 45 – 47 ] are being developed. These approaches, combined with renewed attention to the issue of estimating sampling variance in RDS, should pave the way for more accurate sampling variance estimation and a renewed emphasis on collecting additional network data as part of the sampling process.…”

Section: Discussionmentioning

confidence: 99%

“…More importantly, however, these results suggest the constraints that emerge from the typical RDS sampling methodology which focuses solely on recruiter-recruit links to the neglect of other relevant network data. We argue that a more fruitful approach may be to collect additional network data, either ego-networks [ 24 , 39 – 41 ] or more complete structures [ 11 , 42 ].…”

Section: Improvements To the Vhementioning

confidence: 99%

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Network Structure and Biased Variance Estimation in Respondent Driven Sampling

Verdery¹,

Mouw²,

Bauldry³

et al. 2015

PLoS ONE

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This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

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Section: Discussionmentioning

confidence: 99%

Section: Improvements To the Vhementioning

confidence: 99%

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

Verdery¹,

Mouw²,

Bauldry³

et al. 2015

PLoS ONE

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“…As such, network sampling and network data can be used to a) recruit members of the relevant set of non-migrants who comprise the transnational social field, and b) to measure how migrants and non-migrants are connected each other within this field. Transnational social fields cannot be comprehensively studied with individual level data without consideration of individuals’ position and degree of participation in the border-spanning social network generated by migration (Mouw et al 2014, 330). The first step is to understand the architecture of migrant networks, how the number and intensity of its interaction pathways between and among various groups structure the potential for communication flows.…”

Section: Introductionmentioning

confidence: 99%

Communication flows and the durability of a transnational social field

et al. 2018

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We draw on unique data on communication flows between migrants and non-migrants in a bi-national, cross-border social network to test competing theories of the process of social incorporation. While advocates of the assimilation perspective argue that social incorporation is largely a one-way street, a recent literature on immigrant transnationalism challenges this view by arguing that changes in communication technologies and reductions in travel costs have made it possible for migrants to retain meaningful connections to their origin communities. In the context of this debate, we argue that communication flows-as measured by a combination of the number of social ties and the frequency of communication with them-provide an empirical test of the potential durability of cross-border networks. In our analysis, we find mixed support for both transnationalism and assimilation: while the classic assimilation perspective is correct that the strength of migrants' ties to origin attenuates as time in the destination increases, we also find evidence of a striking persistence in cross-border communication that is reinvigorated by migrant return visits, consistent with an attenuated view of transnationalism.

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“…Baker contends that the voting public discusses politics and “openly deliberate [s] over their choices with family and friends, accepting advice and new information from others while at times attempting themselves to persuade...citizens are embedded in social networks that sustain politically relevant interpersonal exchanges” (Baker, 2006 , p. 6). Those networks can span territorial boundaries because in opting for life in a new country and leaping over the borders separating home and host societies, international migrants paradoxically knit those societies together (Mouw, Chavez, Edelblute, & Verdery, 2014 ).…”

Section: Theoretical Expectationsmentioning

confidence: 99%

Foreign connections and the difference they make: how migrant ties influence political interest and attitudes in Mexico

Duquette-Rury

Waldinger

Lim

2018

CMS

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Beyond the economic and social effects of international migration researchers show regular exchanges between immigrants and stay-at-homes produce political spillovers in sending countries. As a broad body of literature demonstrates, most migrants maintain at least some form of contact with key connections back home, whether through long-distance communication, remittance sending, or in person visits. We investigate if exposure to international migration affects non-migrant citizens political interest, awareness, and attitudes about the efficacy of elections using longitudinal survey data from the Mexico 2006 Panel Study. We use a novel statistical approach combining Double Robust estimation technique with propensity score weighting. Our results suggest that Mexican non-migrant citizens exposed to international migration through social connections and remittances are more likely to be politically aware than those without. We also offer theoretical pathways to explain how ideational and material resources embedded in migrant social networks influences the political interest of stay-at-home citizens.Electronic supplementary materialThe online version of this article (10.1186/s40878-018-0098-y) contains supplementary material, which is available to authorized users.

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Binational Social Networks and Assimilation

Cited by 43 publications

References 103 publications

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

Communication flows and the durability of a transnational social field

Foreign connections and the difference they make: how migrant ties influence political interest and attitudes in Mexico

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