Contact / Bio
Crowdid - social inequality, crowdsourcing, the Crowdsourced Replication Initiative, open science and...
Meta-reproducibility crisis: Software edition. May 2nd, 2022.
Sci-hub. Good for science, otherwise mostly harmless. March 20th, 2022.
Teaching to empower students as public, open and citizen scientists. Jan. 20th, 2022.
Legacy of Jon Tennant, "Open science is just good science". Jan. 4th, 2022.
Global inequalities in science are bigger than those in the economy. June 23rd, 2021.
Social insurance: Global, exclusive, overstated as an institution. March 7th, 2021.
Overcoming replication fears. Feb. 2nd, 2021.
Open science in sociology. What, why and now. Oct. 6th, 2020.
Novel Coronavirus Pandemic and the limits of open science. April 9th, 2020
Behind the specification curve. Jan. 27th, 2020
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.
SPPfilter - A searchable bibliography of social policy preferences research
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.