Panel organized at the 18th IMISCOE Annual Conference Luxembourg 7, 8 and 9 July 2021
For a long time, racism has been studied without references to discrimination and was mainly conceived as a specific expression of prejudice. The turn to more subtle and systemic forms of racism has paved the way for studies on ethnic and racial discrimination and inequalities. Research on discrimination against immigrants and their descendants has grown significantly in the last twenty years, paralleling the settlement of immigrant populations. Studies document differential treatment and discrimination in different markets (e.g. labour market, housing) and social spheres regulated by principles of equality (e.g. school, health service, police). Patterns of discrimination are embedded in institutional contexts and a larger societal environment, characterized not only by economic uncertainties and increasing political polarization in public debate around immigrant related issues, but also by increasing diversity and opportunities of contact. Such changes in the context are likely to affect attitudes and ideology diffusion in majority and minority members. However, studies about discrimination do not refer specifically to racism, and the methodological gains in measuring discrimination did not transfer directly to the measurement of racism. How far racism and ethnic and racial discrimination are distinct, and how they relate to each other are key issues we would like to explore in this panel.
The panel will bring together researchers on discrimination, racism, and inequalities, tackling these issues from various disciplines, theoretical backgrounds and methods. We welcome empirical studies of discrimination patterns across a large variety of domains, theoretical perspectives on how the prevalence of ethnic discrimination and racism should be explained and conceptualized, and studies on the consequences of anti-discrimination policies and legislation, including considerations inequalities in health and racial inequalities and how these can be overcome. We also welcome papers which use and discuss theories about cross-country differences, ethnic hierarchies, and evolution over time.
Submit your abstract specifying the research question, data, methods and findings (200 words maximum) at http://neuchatel.eu.qualtrics.com/jfe/form/SV_5aQA4AnL2pxvRWt no later than 27 November 2020. For further information get in touch. The notification of acceptance will be made by 30 November 2020.
This post might serve as a reminder to myself and others doing research on immigrants and their descendent that nationality is not a mechanism. Put differently, if you discover that people with nationality A differ from people with nationality B in a given characteristic, you have not explained anything at all.
It feels rather obvious when put this way, but it’s usually harder when it comes to multiple regression models. So often we throw in a control variable like “foreign national” or “foreign born” without thinking why we do so, what alternative explanation we think we are capturing. Obviously, a person’s passport or place of birth is used as a shorthand or proxy of something else, but what exactly?
Let’s consider the commonly used variables of migration background or migration origin. Short of calling a particular section of society different in essence (which we probably don’t want to), there are a range of concepts we might be trying to capture, like the experience of (racial) discrimination, having a different skin colour, having a different religion, holding different values, having poor language skills, being of the working class, having additional cultural perspectives and experiences, transnational ties, or a combination of these.
Knowing what we’re after is essential for understanding. Sometimes it is necessary to use proxies like immigrant origin, but we need to specify the mechanism we’re trying to capture. Depending on the mechanism, who should be counted as of immigrant origin, for example, can be quite different, especially when it comes to children of immigrants, individuals of “mixed” background, and naturalized individuals. Having poor language skills, for example, is something most likely to affect (first generation) immigrants; but likely experience of racial discrimination is probably not disappearing just because it was my grandparents rather than me who came to this country.
In a new paper, Graham Brown and Arnim Langer introduce a general class of social distance measures. They follow the general feeling that many measure of diversity and disparity may be closely related by demonstrating how they are all related. By clarifying how these different measures are related, we should find it easier to choose an appropriate measure for the analysis at hand.
The one thing I’m still not convinced is the title of the paper: While they clearly define what they mean by social distance, my sociological training keeps interfering and social distance doesn’t seem fit to express a characteristic of a society. Perhaps it’s easier to talk of the more concrete instances of ethnic diversity, or income disparity.
Brown, Graham K., and Arnim Langer. 2016. ‘A General Class of Social Distance Measures’. Political Analysis, March, mpw002. doi:10.1093/pan/mpw002.
It’s the time of the year I make my students read codebooks (to choose a data set). It often strikes me how complex survey questions can be, especially once we take into account introductions and explanations. The quest is clear: precision, ruling out alternative understandings. Often, these are (or seem to be) the sole tools we have to ensure measurement validity.
Against this background, a paper by Sebastian Lundmark et al. highlights that minimally balanced questions are best for measuring generalized trust: asking whether “most people can be trusted or that you need to be very careful in dealing with people” (fully balanced) is beaten by questions that limit themselves to whether it is “possible to trust people.”
Lundmark, Sebastian, Mikael Gilljam, and Stefan Dahlberg. 2015. ‘Measuring Generalized Trust An Examination of Question Wording and the Number of Scale Points’. Public Opinion Quarterly, October, nfv042. doi:10.1093/poq/nfv042.
David Broockman has an important paper on political representation apparently forthcoming in LSQ.
He notes two ways to study the political representation of issues, policies, and preferences. On the one hand we can examine citizen-elite congruence issue by issue. On the other hand, we can calculate “policy scores” to capture ideal points of overall ideologies and compare these between citizens and the elite. The paper convincingly demonstrates that the latter approach is flawed in the sense that it doesn’t really capture political representation in the way we generally understand it.
Broockman, David E. 2015. “Approaches to Studying Policy Representation.” Legislative Studies Quarterly.