Elias Naumann

We examine whether welfarechauvinistic attitudes, the preference for restricting immigrants’ access to welfare benefits, differ by benefit type and whether citizenship attenuates migrant penalties in welfare deservingness. Using a between-subjects multifactorial survey experiment embedded in a probability-based online panel (March 2019; N = 4,890), we asked respondents to evaluate an unemployed benefit claimant on three outcomes: support for earnings-related unemployment benefits, needs-based social assistance, and benefit sanctions. Across outcomes, migrant profiles are judged less deserving than otherwise identical ethnic German profiles. Penalties are of similar magnitude for unemployment insurance and social assistance while sanction differentials are smaller and limited to some, more culturally distant groups. Citizenship, as an institutional signal of integration, attenuates penalties within shared ethnic origin but does not fully close the gap to ethnic Germans, even under favorable deservingness cues.

A substantial body of evidence documents misperceptions among natives regarding the number of migrants and their integration. Using two experimental studies, we show that these misperceptions are context-dependent rather than universal. The first study examines whether the accuracy of natives’ perceptions varies with the spatial scale at which they are elicited. People consistently overestimate the share of migrants, and this misperception does not depend on scale. In contrast, perceptions of migrant integration improve at more localized levels: natives underestimate integration at the national scale but estimates become more accurate at the district and neighborhood levels. The second study shows that perceptions of labor market integration for both natives and migrants are generally inaccurate and vary across different migrant groups. Overall, our findings suggest that researchers studying (mis)perceptions about migrants should carefully consider the spatial context of their data. Misperceptions are more nuanced than previously recognized.

The same dataset can be analysed in different justifiable ways to answer the same research question, potentially challenging the robustness of empirical science1–3. In this crowd initiative, we investigated the degree to which research findings in the social and behavioural sciences are contingent on analysts’ choices. We examined a stratified random sample of 100 studies published between 2009 and 2018, where for one claim per study, at least five re-analysts independently re-analysed the original data. The statistical appropriateness of the re-analyses was assessed in peer evaluations, and the robustness indicators were inspected along a range of research characteristics and study designs. We found that 34% of the independent re-analyses yielded the same result (within a tolerance region of +/- 0.05 Cohen’s d) as the original report; with a four times broader tolerance region, this indicator rose to 57%. Regarding the conclusions drawn, 74% of analyses were reported to arrive at the same conclusion as in the original investigation; 24% to no effects/inconclusive result, and 2% to the opposite effect as in the original investigation. This exploratory study suggests that the common single-path analyses in social and behavioural research should not simply be assumed to be robust to alternative analyses4. Therefore, we recommend the development and use of practices to explore and communicate this neglected source of uncertainty.

The COVID-19 pandemic posed a major challenge for the implementation of population surveys, particularly longitudinal studies such as repeated cross-sectional and panel surveys. Since these surveys aim to measure change in many indicators over time, any modifications to their design must be carefully considered as they might compromise comparability over time. In our study, we examined how the pandemic affected the data collection of longitudinal surveys in particular survey design. Utilizing the metadata of 576 surveys conducted as part of 95 longitudinal survey programs in Germany, we showed how existing longitudinal surveys differed in their survey collection practices from the newly established longitudinal surveys. Existing surveys were less likely to implement changes compared to the newly established surveys, except for those existing surveys that relied on face-to-face interviews, which often switched their mode. In contrast, to speed up data collection, the newly established surveys frequently employed survey designs that differed from the high-quality survey designs of existing surveys.