Research

My research asks how ethno-racial diversity, immigrant integration, and the struggle over discrimination shape solidarity, trust, and political conflict in contemporary democracies. I pursue these questions by theorizing the social mechanisms that link individual cognition and behavior to macro-level outcomes, and by testing them through survey, field, and behavioral experiments. A commitment to causal inference and comparative research design runs across all three strands. Earlier methodological work — on the conditions under which multilevel models produce reliable estimates of cross-level interaction effects, and on improved likelihood-based methods for small-cluster inference — appeared in the American Sociological Review, European Sociological Review, and British Journal of Political Science.

Discrimination — Causes, Misperceptions, and Contestation

Why do contemporary democracies struggle so persistently with ethno-racial discrimination — and why does that struggle so rarely lead to resolution? My research argues that answering this question requires moving beyond the conventional focus on detecting discrimination and identifying its perpetrators. Discrimination is not only a social fact to be measured; it is also a perceived reality that diverges systematically across social groups, and a politically contested concept whose very definition is subject to ongoing struggle. These three dimensions are analytically distinct but causally connected: the gap between how discrimination is actually experienced and how it is perceived is not random noise, but a predictable product of social position and political context. Far-right electoral victories, for instance, causally exacerbate discriminatory behavior by street-level bureaucrats — widening the real disparity in access to healthcare — while simultaneously shaping the normative environment in which majorities evaluate whether such disparities even constitute discrimination. My current theoretical work develops this into a general framework: the societal struggle over the definition and prevalence of discrimination is not a communication failure correctable by better evidence, but a structural feature of democratic societies in which the meaning of the state’s own founding commitments is continually renegotiated.

Key publications

  • Schaeffer, Krakowski & Olsen (2026). “Correcting Misperceptions about Ethno-Racial Discrimination: The Limits of Evidence-Based Awareness Raising.” American Journal of Political Science 70(1): 54–75.
  • Schaeffer & Kas (2025). “The Integration Paradox: Does Awareness of the Extent of Ethno-Racial Discrimination Increase Reports of Discrimination?” Political Psychology 46(3): 623–636.
  • Schaeffer, Romarri, Rosenberg & Krakowski (conditionally accepted). “When Politics Enters the Waiting Room: Far-Right Electoral Victories Exacerbate Discrimination in Access to Healthcare.” American Political Science Review.

Current working paper: “Contested Discrimination: A Theory of the Societal Struggle over Definition and Prevalence.” Under review.

Immigrant Integration and Social Cohesion

How does immigrant integration transform the societies that receive it — and how does it affect the immigrants themselves? My research on this question treats integration as both a social process and an outcome in its own right. On one side, I have studied how the scale and character of ethnic diversity shapes solidarity, social trust, and the willingness of majority populations to cooperate across group boundaries — drawing on comparative survey data, neighborhood-level field experiments, and meta-analytic synthesis across dozens of studies. A recurrent finding is that the consequences of diversity depend critically on how it is measured, at what spatial scale, and in what institutional context. On the other side, I study integration from the perspective of immigrants and their descendants: how residential exposure to coethnics, access to ethno-religious community infrastructures — mosques, associations, minority-owned businesses — and the experience of boundary crossing shape migrants’ subjective well-being and sense of belonging. Across both sides of this research, the micro-level mechanisms through which individual experiences and interactions aggregate into macro-level patterns of cohesion or conflict remain the central theoretical concern.

Key publications

  • Legewie & Schaeffer (2016). “Contested Boundaries: Explaining Where Ethnoracial Diversity Provokes Neighborhood Conflict.” American Journal of Sociology 122(1): 125–161. ★ ASA Mathematical Sociology Award 2017; ASA Distinguished Contribution to Scholarship in Population 2016.
  • Dinesen, Schaeffer & Sønderskov (2020). “Ethnic Diversity and Social Trust: A Narrative and Meta-Analytical Review.” Annual Review of Political Science 23: 441–465.
  • Wiedner, Schaeffer, Carol & Böller (2026). “Local Communities, Distant Origins: How Cultural Distance and Local Context Shape Immigrant Ethno-Religious Infrastructures.” American Journal of Sociology.

Comparative Methods and Causal Inference

Establishing causal claims from observational data in comparative social research poses well-known challenges that are frequently underacknowledged in applied work. A parallel thread running through my research concerns the statistical and design tools that comparative sociologists and political scientists use to study macro-level questions, and the conditions under which these produce reliable inferences. This work has focused in particular on multilevel models — the default tool for analyzing cross-nationally nested data — and on the design and analysis of survey and field experiments as a route to credible causal identification in comparative settings. A central contribution has been to show, through formal argument and Monte Carlo simulation, that widely used multilevel specifications systematically misestimate cross-level interaction effects when they fail to account for cluster-level heterogeneity in the effects of control variables — a problem that affects a substantial share of published comparative research.

Key publications

  • Heisig, Schaeffer & Giesecke (2017). “The Costs of Simplicity: Why Multilevel Models May Benefit from Accounting for Cross-Cluster Differences in the Effects of Controls.” American Sociological Review 82(4): 796–827.
  • Heisig & Schaeffer (2019). “Why You Should Always Include a Random Slope for the Lower-Level Variable Involved in a Cross-Level Interaction.” European Sociological Review 35(2): 258–279. ★ Runner-up, Best ESR Article 2019.
  • Elff, Heisig, Schaeffer & Shikano (2021). “Multilevel Analysis with Few Clusters: Improving Likelihood-Based Methods to Provide Unbiased Estimates and Accurate Inference.” British Journal of Political Science 51(1): 412–426.