Scoggins, BermondRobertson, Matthew P.2025-05-232025-05-23http://www.scopus.com/inward/record.url?scp=85200788437&partnerID=8YFLogxKhttps://hdl.handle.net/1885/733751923The scientific method is predicated on transparency - yet the pace at which transparent research practices are being adopted by the scientific community is slow. The replication crisis in psychology showed that published findings employing statistical inference are threatened by undetected errors, data manipulation and data falsification. To mitigate these problems and bolster research credibility, open data and preregistration practices have gained traction in the natural and social sciences. However, the extent of their adoption in different disciplines is unknown. We introduce computational procedures to identify the transparency of a research field using large-scale text analysis and machine learning classifiers. Using political science and international relations as an illustrative case, we examine 93 931 articles across the top 160 political science and international relations journals between 2010 and 2021. We find that approximately 21% of all statistical inference papers have open data and 5% of all experiments are preregistered. Despite this shortfall, the example of leading journals in the field shows that change is feasible and can be effected quickly.This study was supported by the Australian Government Research Training Program Scholarship, the ANU Library, Taylor & Francis, TeamViewer AG and the Google Cloud Research Credits program (award GCP19980904). Both authors would like to thank those who provided us invaluable feedback at the New Approaches for the Improvement of Quantitative Analysis panel at the 2022 Midwest Political Science Association Conference. This study was supported by the Australian Government Research Training Program Scholarship, the ANU Library, Taylor & Francis, TeamViewer AG and the Google Cloud Research Credits program (award GCP19980904). AcknowledgementsenPublisher Copyright: © 2024 The Authors.data sharingjournal policyopen sciencepreregistration202410.1098/rsos.24031385200788437