In 2021, the German Longitudinal Election Study (GLES), in collaboration with the journal German Political Science Quarterly (PVS) and the German Society for Electoral Studies (DGfW) organized the GLES Open Science Challenge 2021. After 16 years of Angela Merkel as chancellor, the 2021 German federal election marked a watershed in German politics. The race for her successor was wide open. Simultaneously, it was unclear how long the COVID-19 pandemic and its corresponding restrictions would dominate the political agenda in Germany. Under these volatile circumstances, we invited open topic submissions for studies that employ 2021 GLES survey data to examine research questions in these times of political change and crises.
The call for open topic submissions for a Special Issue featuring Registered Reports based on the data of the GLES Cross-Section 2021 pre-election survey or the GLES Rolling Cross-Section 2021 was answered by many scholars from different disciplines. The main characteristic of this Special Issue is that the study proposals were reviewed prior to data publication to assess their merits based on the relevance of the research question(s) and the appropriateness of the theoretical and methodical approaches irrespective of the empirical results of the analyses. The combination of pre-registration and review process prior to data publication is known as Registered Reports.
The result of this pioneering initiative is a Special Issue featuring seven Registered Reports that bring together a diverse set of studies on relevant questions during times of political change and crises in the context of the 2021 German federal election.
The GLES Open Science Challenge 2021 provides a model of how Registered Reports can be applied to secondary data analysis, thereby providing a case study of how this format can be used in electoral research.
Call for Papers (175 kB)
Guidelines for Authors (200 kB)
Code Submission Guidelines (131 kB)
Guidelines for Reviewers (143 kB)
Frequently Asked Questions (FAQs) (66 kB)
The GLES Open Science Challenge 2021 was a pioneering initiative in quantitative political science. The project combined the rigor of registered reports—a new publication format in which studies are evaluated prior to data collection/access and analysis—with quantitative political science research in the context of the 2021 German federal election. The special issue, which features seven registered reports that resulted from the project, shows that transparent research following open science principles benefits our discipline and substantially contributes to quantitative political science. All contributions are based on GLES data and available open access.
Bucher, H., Stroppe, A., Burger, A., Faas, T., Schoen, H., Debus, M. & Roßteutscher, S. (2023). Special Issue Introduction. GLES Open Science Challenge 2021: A Pilot Project on the Applicability of Registered Reports in Quantitative Political Science. Polit Vierteljahresschr 64(1): 1-17. doi.org/10.1007/s11615-022-00436-0
Welz, R. (2023). At Least Agree on the Important Things: The Impact of Issue Distance, Intracoalition Heterogeneity, and Salience on Voters’ Coalition Preferences. Polit Vierteljahresschr 64(1): 19-49. doi.org/10.1007/s11615-022-00415-5
Unkelbach, F., John, M. & Vogel, V. (2023). Jumping on the Bandwagon: The Role of Voters’ Social Class in Poll Effects in the Context of the 2021 German Federal Election. Polit Vierteljahresschr 64(1): 51-78. doi.org/10.1007/s11615-022-00417-3
Schnaudt, C. (2023). Exit or Voice? Behavioral Implications of Electoral-Integrity Beliefs in Germany. Polit Vierteljahresschr 64(1): 79-105. doi.org/10.1007/s11615-022-00403-9
Steiner, N.D., Schimpf, C.H. & Wuttke, A. (2023). Left Behind and United by Populism? Populism’s Multiple Roots in Feelings of Lacking Societal Recognition. Polit Vierteljahresschr 64(1): 107-132. doi.org/10.1007/s11615-022-00416-4
Huber, R.A., Jankowski, M. & Wegscheider, C. (2023). Explaining Populist Attitudes: The Impact of Policy Discontent and Representation. Polit Vierteljahresschr 64(1): 133-154. doi.org/10.1007/s11615-022-00422-6
Menzner, J., Traunmüller, R. (2023). Subjective Freedom of Speech: Why Do Citizens Think They Cannot Speak Freely?. Polit Vierteljahresschr 64(1): 155-181. doi.org/10.1007/s11615-022-00414-6
Cohen, D. (2023). Preferences for Rent Control: Between Political Geography and Political Economy. Polit Vierteljahresschr 64(1): 183-205. doi.org/10.1007/s11615-022-00404-8
Bucher, H., Stroppe, A., Burger, A., Faas, T., Schoen, H., Debus, M., Roßteutscher, S., Cohen, D., Huber, R., Jankowski, M., John, M., Menzner, J., Schimpf, C., Schnaudt, C., Steiner, N., Traunmüller, R., Unkelbach, F., Vogel, V., Wegscheider, C., Welz, R. & Wuttke, A. (2023). Special Issue Conclusion. The GLES Open Science Challenge 2021 in Hindsight: Experiences Gained and Lessons Learned.Polit Vierteljahresschr 64(1): 207-219. doi.org/10.1007/s11615-022-00437-z
You can find a list of published Registered Reports in this Zotero library.
Chambers, C. D. (2013). Registered Reports: A new publishing initiative at Cortex. Cortex 49: 609–610.
Findley, M. G., Jensen, N. M., Malesky, E. J., & Pepinsky, T. B. (2016). Can Results-Free Review Reduce Publication Bias? The Results and Implications of a Pilot Study. Comparative Political Studies 49(13): 1667–1703. doi.org/10.1177/0010414016655539
Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. K. (2019). Recommendations for Increasing the Transparency of Analysis of Preexisting Data Sets. Advances in Methods and Practices in Psychological Science 2(3): 214–227. doi.org/10.1177/2515245919848684
Bischof, D., & Van der Velden, M. (2019). The Use and Usefulness of p‐Values in Political Science: Introduction. Swiss Political Science Review 25(3): 276-280.
Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The pre-registration revolution. Proceedings of the National Academy of Sciences of the United States of America 115(11): 2600-2606. doi.org/10.1073/pnas.1708274114
Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. K. (2019). Recommendations for Increasing the Transparency of Analysis of Preexisting Data Sets. Advances in Methods and Practices in Psychological Science 2(3): 214–227. doi.org/10.1177/2515245919848684
