The Inter-Ethnic Friendships of Immigrants with Host-Society Members: Revisiting the Role of Ethnic Residential Segregation
In: Journal of ethnic and migration studies: JEMS, Band 38, Heft 1, S. 77-91
ISSN: 1469-9451
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In: Journal of ethnic and migration studies: JEMS, Band 38, Heft 1, S. 77-91
ISSN: 1469-9451
In: Journal of ethnic and migration studies: JEMS, Band 38, Heft 1, S. 77-92
ISSN: 1369-183X
In: Journal of ethnic and migration studies: JEMS, Band 38, Heft 1, S. 77-91
ISSN: 1469-9451
In: Journal of ethnic and migration studies: JEMS, Band 48, Heft 9, S. 2148-2167
ISSN: 1469-9451
In: Frontiers in sociology, Band 5, S. 1-10
ISSN: 2297-7775
What factors shape immigrants' worries about becoming targets of ethnic harassment? This is an important question to ask, but most previous studies restricted their focus to the microlevel only. By contrast, few if any studies examined the possible macrolevel antecedents driving harassment-related worries among immigrants. This study aims to help fill this gap. Focusing on a 19-years period from 1986 to 2004 in Germany, we apply multilevel regression modeling techniques to repeated cross-sectional survey data collected among immigrants of Greek, Italian, Spanish, Turkish, and (ex-) Yugoslavian origin, linked with contextual characteristics. Our central finding is that German citizens' anti-immigrant prejudice is the key driver of longitudinal differences in immigrants' harassment-related worries. This association holds net of rival variables, such as fluctuations in media attention to ethnic harassment, as well as across all immigrant groups under study. These results bring us one important step further toward a better understanding of interethnic relations between immigrants and host society members.
In: Methods, data, analyses: mda ; journal for quantitative methods and survey methodology, Band 12, Heft 2, S. 211-232
ISSN: 2190-4936
Segregation between ethnic or sociodemographic groups represents a longstanding key independent and dependent variable for the social sciences. However, researchers have only recently begun to take advantage of inferential rather than descriptive statistical techniques
in order to assess various aspects of segregation. Specifically, this paper shows that the multilevel binomial response approach suggested by Leckie et al. (2012) provides a particularly flexible framework for describing and explaining segregation in ways not previously possible. Taking the index of dissimilarity (D) as an example we demonstrate how the multilevel binomial response approach helps to reduce the problem of small unit bias, allows to asses segregation at different scales and enables researchers to better understand the role of individual- and contextual-level explanatory variables in shaping segregation. To this end, we employ three case studies focusing on different manifestations of ethnic and gender segregation using survey data from urban, national and cross-national settings.
In: Journal of ethnic and migration studies: JEMS, Band 46, Heft 3, S. 649-664
ISSN: 1469-9451
In: International journal of public opinion research, Band 31, Heft 1, S. 93-120
ISSN: 1471-6909
In: Proceedings of the National Academy of Sciences of the United States of America (PNAS), Band 119, Heft 44, S. 1-8
This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.