Nate Breznau

Principal Investigator &

Postdoctoral Researcher

SOCIUM Research Center on Inequality and Social Policy

'The Global Dynamics of Social Policy'

Collaborative Research Center (SFB 1342)

University of Bremen

Contact / Bio

Curriculum Vitae as pdf

Google Scholar Page


office: SOCIUM 5.4040

Postal Address:

Universität Bremen

SOCIUM Forschungszentrum Ungleichheit und Sozialpolitik

Postfach 33 04 40

28334 Bremen


I did a BA double major in Sociology and African-American Studies at Bates College in Lewiston, Maine, USA from 1997-2002. Then I worked in the tourism and journalism industries in Lake Tahoe, California, USA from 2002-2006. I returned to academia to do an MA in Sociology at the University of Nevada, Reno from 2006-2008 where I became interested in survey research and in particular the relationship of public opinion and social policy. I used this interest and my MA Thesis (eventually published as a journal article) to write a convincing research proposal that got me a fellowship at the Bremen International Graduate School of Social Sciences (BIGSSS) at the University of Bremen, Germany. There I did my PhD in Sociology from 2009-2013. I then worked as a Postdoctoral researcher at BIGSSS for two years and got a another Postdoc at the Mannheim Center for European Social Research (MZES) at the University of Mannheim, Germany. During my time at the MZES I became deeply interested in open science and I co-developed a side project to investigate what happens when many independent teams engage in replication and then what happens when many teams test the same data with the same hypothesis. This 'Crowdsourced Replication Initiative' became a major undertaking and took much longer than expected. In order to help make the results publicly accessible I received a Freies-Wissen Fellowship (Open Science Fellowship) from the Wikimedia Foundation. During my Postdoc I also developed my first successful German Science Foundation (DFG) grant application on the 'Reciprocal Relationship of Public Opinion and Social Policy'. As the reviewing procedure took two rounds, my time at the MZES ended and I found a third Postdoc position back at the University of Bremen but this time in their Collaborative Research Center (SFB1342) "The Global Dynamics of Social Policy" in a project coding and analyzing the history of social security laws (pensions, unemployment, work-injury) in 187 countries since 1880. While working on this and my own DFG project, I was awarded a second DFG grant based on my crowdsourced research project on the topic of "The Role of Theory in (Resolving) the Reproducibility Crisis" in social science. I took part in the application process for the 2nd phase of CRC funding and it was successful, thus I am now co-Principal Investigator in the project "Global Dynamics of Coverage and Generosity in Work-Injury Compensation, Unemployment and Old-Age Pensions" aimed at coding the inclusivity and coverage (replacement rates) of the social security laws.

You can read more about my research in the following areas on my professional website:

Open Science


Public Opinion and Social Policy

Recent Scientific Output


Working paper with a guide for instructors on how to teach replication or integrate replication into their courses. 

Results from 162 researchers in 73 teams testing the same hypothesis with the same data reveals a universe of unique possibilities in the process of data analysis. Contrary to our expectations, variance in results and subjective conclusions are only partially explained - less than 18% - by the model specifications and the characteristics of the researchers in each team. Although there were common specifications across many teams regarding sample selection, variance components, estimator and additional independent variables, each of the 1,261 test models submitted by the teams was ultimately a unique combination of specifications. As such, the extreme variation in substantive research outcomes and researcher conclusions suggests that researcher-specific if not model-specific idiosyncratic variation is an important source of unreliability in science. Preprint. Watch Video.
We are constructing a public bibliography of all empirical studies analyzing the relationship of public opinion and social policy. Our application allows the user to search through the title and abstract - with deeper text-based searches planned. Based on a Zotero library. 
Talk prepared for the Social Welfare Association of Taiwan Annual Conference, May 14th, 2021. Presents results of four studies investigating the relationship of welfare states, inequality, public perceptions and behaviors, media sentiment and infection rates in up to 164 countries. Slides available. Also, a related blog post with a reproducible workflow scraping data on media sentiment in addition to policy response, public opinion and infection rates.
A review of the events surrounding the Heinsberg Study in Germany and the lessons learned for open science practices and communications. 
The Novel Coronavirus Pandemic causes heightened risk perceptions, in particular related to health, mortality and economic security. In 'normal' times, these are risks covered by social welfare states via social insurance and protection policies. My research question is what role the welfare state plays in a global emergency - here the SARS-Cov-2 pandemic. I test for an impact of the welfare state on risk perceptions using COVIDiSTRESS data comparing 70 countries in April, 2020. Adjusting for local timing and severity of outbreak, I demonstrate that strength of the welfare state predicts lower risk perceptions. However, this depends on the speed of government intervention: rapid intervention removes the effect of the welfare state. Therefore, I conclude from this study that when governments fail to take swift measures, the welfare state plays a major role in alleviating risk perceptions. 
Crowdsourcing enables novel forms of research and knowledge production. It uses cyberspace to collect diverse research participants, coordinate projects and keep costs low. Recently social scientists began crowdsourcing their peers to engage in mass research targeting a specific topic. This enables meta-analysis of many analysts’ results obtained from a single crowdsourced research project, leading to exponential gains in credibility and scientific utility. Initial applications demonstrate positive returns for both original and replication research using various research instruments, and secondary or experimental data. It can provide more reliable Bayesian priors for selecting models and is an untapped mode of theory production that greatly benefit social science. Finally, in addition to the credibility and reproducibility gains, crowdsourcing embodies many core values of the Open Science Movement because it promotes community and equality among scientists.