The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report.

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process

Policy, social capital and health: the multiple implications of immigrant economic incorporation

For many the success of a migration decision depends on making a successful transition into the new labor market. The objective of this dissertation is to shine light on the link between the labor market outcomes of first-generation immigrants and the policy configuration of their host country. The body of this dissertation consists of three empirical chapters. The first assesses a policy shift in Austria to highlight its impact on the education-occupation mismatch. The second assesses the role of social networks in post-migration employment and occupational mobility in Australia. The third tackles the interplay between immigration, obesity and wages in Australia, focusing on the way in which obesity is measured. The general conclusions attest to the multi-faceted nature of the immigrant experience and, moreover, to the importance, especially when discussing policy, of a comprehensive perspective accounting for both the start point and the trajectory of immigrants subsequent to arrival.Para muchos el éxito de una decisión migratoria depende de una transición exitosa hacia el nuevo mercado laboral. El objetivo de esta disertación es arrojar luz sobre la relación entre los resultados obtenidos por inmigrantes de primera generación en el mercado laboral y la configuración de las políticas del país de acogida. Esta disertación está conformada por tres capítulos empíricos. El primero evalúa un cambio en la política de inmigración de Austria con el fin de resaltar su impacto en el desajuste entre educación y ocupación. El segundo evalúa el papel que juegan las redes sociales en el empleo y en la movilidad ocupacional post-migratorios en Australia. El tercero aborda la interrelación entre la inmigración, la obesidad y los salarios en Australia, enfocándose en la forma en la que se mide la obesidad. Las conclusiones generales avalan la naturaleza polifacética de la experiencia del inmigrante y, además, la importancia, especialmente cuando se habla de políticas, de una perspectiva global que dé cuenta tanto del punto de partida como de la trayectoria de los inmigrantes con posterioridad a la llegada

Observing Many Researchers Using the Same Data and Hypothesis Reveals a Hidden Universe of Uncertainty

Breznau N, Rinke EM, Wuttke A, et al. Observing Many Researchers Using the Same Data and Hypothesis Reveals a Hidden Universe of Uncertainty. 2021.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 include conscious and unconscious decisions that researchers make during data analysis and that may lead to diverging results. 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 research based on secondary data, we find that research teams reported widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predicted the wide variation in research outcomes. More than 90% of the total variance in numerical results remained unexplained even after accounting for research decisions identified via qualitative coding of each team’s workflow. This reveals a universe of uncertainty that is hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a new explanation for why many scientific hypotheses remain contested. It calls for greater humility and clarity in reporting scientific findings

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

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

The Crowdsourced Replication Initiative

Crowdsourced Research on Immigration and Social Policy Preference

The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report

Breznau N, Rinke EM, Wuttke A, et al. The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report. 2019