Merlin Schaeffer

Can competing diversity indices inform us about why ethnic diversity erodes social cohesion? A test of five diversity indices in Germany

An ever-growing number of studies investigates the relation between ethnic diversity and social cohesion, but these studies have produced mixed results. In cross-national research, some scholars have recently started to investigate more refined and informative indices of ethnic diversity than the commonly used Hirschman-Herfindahl Index. These refined indices allow to test competing theoretical explanations of why ethnic diversity is associated with declines in social cohesion. This study assesses the applicability of this approach for sub-national analyses. Generally, the results confirm a negative association between social cohesion and ethnic diversity. However, the competing indices are empirically indistinguishable and thus insufficient to test different theories against one another. Follow-up simulations suggest the general conclusion that the competing indices are meaningful operationalizations only if a sample includes: (1) contextual units with small and contextual units with large minority shares, as well as (2) contextual units with diverse and contextual units with polarized ethnic compositions. The results are thus instructive to all researchers who wish to apply different diversity indices and thereby test competing theories.

Ethnic diversity and social cohesion : immigration, ethnic fractionalization and potentials for civic action

Contents: Introduction The fragility of social cohesion in ethnically diverse societies: empirical evidence or spurious correlation? Elements of a theory on ethnic diversity and social cohesion: nothing but group threat? Measuring ethnic diversity: competing statistical indices, similar results? Beyond measured facts: perceptions of ethnic diversity and social cohesion Perceptions are not arbitrarily subjective: blaming ethnic minorities for neighbourhood problems The dilemma of inter-ethnic coexistence: sources of cohesion in ethnically diverse neighbourhoods Conclusion Appendix Bibliography Index.

Inter-Ethnic Neighbourhood Acquaintances of Migrants and Natives in Germany: On the Brokering Roles of Inter-Ethnic Partners and Children

Social scientists have long emphasised the importance of personal inter-ethnic contact for overcoming prejudices and enhancing social cohesion in mixed societies. But why do some people have more contact with their neighbours of other ethnicity? Using new data from a large-scale German survey, I analyse the brokering roles of children and inter-ethnic partners in explaining inter-ethnic neighbourhood acquaintances. Even on a contextual level, my results suggest that people living in regions with larger shares of children have more inter-ethnic neighbourhood acquaintances, which expands earlier findings on the general integrating function of children. However, I also argue that we should recognise brokering to be context-specific and exemplify this by showing how the brokering role of inter-ethnic partners is evident particularly in interaction with inter-ethnic encounters at local bars and restaurants, while that of children is evident particularly given their frequent inter-ethnic encounters in public parks and playgrounds. On a theoretical level, my results demonstrate the importance of studying the interaction of mechanisms in explaining personal (inter-ethnic) contact.

Contested boundaries: : Explaining where ethnoracial diversity provokes neighborhood conflict

Concerns about neighborhood erosion and conflict in ethnically diverse settings occupy scholars, policy makers, and pundits alike; but the empirical evidence is inconclusive. This article proposes the contested boundaries hypothesis as a refined contextual explanation focused on poorly defined boundaries between ethnic and racial groups. The authors argue that neighborhood conflict is more likely to occur at fuzzy boundaries defined as interstitial or transitional areas sandwiched between two homogeneous communities. Edge detection algorithms from computer vision and image processing allow them to identify these boundaries. Data from 4.7 million time- and geo-coded 311 service requests from New York City support their argument: complaints about neighbors making noise, drinking in public, or blocking the driveway are more frequent at fuzzy boundaries rather than crisp, polarized borders. By focusing on the broader sociospatial structure, the contested boundaries hypothesis overcomes the “aspatial” treatment of neighborhoods as isolated areas in research on ethnic diversity.

Relational diversity and neighbourhood cohesion. Unpacking variety, balance and in-group size

Ethnic diversity is typically measured by the well-known Hirschman-Herfindahl Index. This paper discusses the merits of an alternative approach, which is in our view better suited to tease out why and how ethnic diversity matters. The approach consists of two elements. First, all existing diversity indices are non-relational. From the viewpoint of theoretical accounts that attribute negative diversity effects to in-group favoritism and out-group threat, it should however matter whether, given a certain level of overall diversity, an individual belongs to a minority group or to the dominant majority. We therefore decompose diversity by distinguishing the in-group share from the diversity of ethnic out-groups. Second, we show how generalized entropy measures can be used to test which of diversitys two basic dimensions matters most: the variety of groups, or the unequal distribution (balance) of the population over groups. These measures allow us to test different theoretical explanations against each other, because they imply different expectations regarding the effects of in-group size, out-group variety, and out-group balance. We apply these ideas in an analysis of various social cohesion measures across 55 German localities and show that both in-group size and out-group diversity matter. For the native majority as well as for persons of immigration background, the variety component of diversity seems to be more decisive than has formerly been acknowledged. These findings provide little support for group threat and in-group favoritism as the decisive mechanisms behind negative diversity effects, and are most in line with the predictions of theories that emphasize coordination problems, asymmetric preferences, and network closure.

The Costs of Simplicity: Why Multilevel Models May Benefit from Accounting for Cross-Cluster Differences in the Effects of Controls

Context effects, where a characteristic of a higher-level unit or “cluster” (e.g., a country) affects outcomes and relationships at a lower level (e.g., that of the individual), are a primary object of sociological inquiry. During recent decades, sociologists have increasingly investigated context effects using quantitative methods. We show that quantitative multilevel studies in leading sociology journals nearly always assume that the effects of lower-level control variables do not vary across clusters. This “invariant coefficients assumption” is often implausible. Based on analytical reasoning and Monte Carlo evidence, we argue that this assumption can have severe consequences for the estimation of context effects. Comparing mixed effects (random intercept and slope) models, cluster-robust pooled OLS, and two-step approaches, we show that models neglecting cluster differences in the effects of control variables can be dramatically less efficient than models that allow for such heterogeneity. That is, they tend to miss the true strength of the relationship of interest by larger amounts. Efficiency losses are largest when there is pronounced cross-cluster heterogeneity in the coefficients of control variables, when there are marked compositional differences among clusters, and when the number of clusters is small. Thus, the costs of assuming invariant control slopes should be highest in country comparisons. We end with concrete recommendations for applied researchers.

Der Halo-Effekt in einheimisch-homogenen Nachbarschaften

Zusammenfassung Dieser Beitrag untersucht, ob Menschen in einheimisch-homogenen Nachbarschaften, die an ethnisch-divers zusammengesetzte Nachbarschaften angrenzen oder von diesen sogar umgeben sind, besonders zu xenophoben Einstellungen neigen. Diese als „Halo“ (auf Deutsch „Ring“) bezeichnete sozial-räumliche Konstellation synthetisiert zwei prominente theoretische Ansätze zur Erklärung von Xenophobie: Weil die homogen-zusammengesetzte direkte Nachbarschaft kaum Möglichkeiten zu positivem Intergruppenkontakt birgt, können die umgebenden ethnisch-diversen Nachbarschaften umso ungebremster subjektive Wettbewerbsängste und Bedrohungsgefühle auslösen, die letztendlich in Xenophobie münden. Jenseits von klassischen Hypothesen über die Kontexteffekte von Bevölkerungsanteilen, liegt das Augenmerk dieses Ansatzes somit auf der Bedeutung der Einbettung von Nachbarschaften in ihre lokale Umgebung. Unsere Analysen auf Basis des geokodierten ALLBUS 2014 finden jedoch keine Bestätigung für die Halo-Effekt-Hypothese, weder im Allgemeinen noch für besonders Xenophobie affine Subpopulationen. Unser Artikel verdeutlicht dennoch, auf einer theoretisch generelleren Ebene, dass die Einbettung von Nachbarschaften in ihre lokale Umgebung bedeutsam sein kann und demonstriert die methodischen Besonderheiten einer solchen räumlichen Analyse der geokodierten ALLBUS-Daten. Im Fazit werden darüber hinaus plausible Gründe diskutiert, warum unsere Ergebnisse von Studien aus anderen Ländern abweichen.

Diversity erfassen: Statistische Diversitätsindizes

Dieses Kapitel stellt die statistische Erfassung von Diversity vor. Es umfasst zunachst konzeptionelle Uberlegungen zur Definition von Diversitat und fuhrt die drei Dimensionen ein, aus denen Diversitat sich zusammensetzt: Balance, Variabilitat und Disparitat. Es werden sodann statistische Diversitatsindizes erlautert, die diese drei Dimensionen in einer Diversitatsmaszahl auszudrucken versuchen. Die gangigen Diversitatsindizes messen jedoch die Vielfalt oder Verschiedenartigkeit der Bevolkerung nur im Hinblick auf eine Eigenschaft, wie etwa Nationalitat oder Religion. In einem kurzen Abschnitt wird daher auch auf Faultline- bzw. Kreuzkategorisierungsindizes eingegangen, die – ganz der Idee der Intersektionalitat entsprechend – die Uberlappung verschiedener Eigenschaften in einer Population erfassen.