Abstract
ABSTRACT We provide the first replication study of political science research published in Brazil by attempting to replicate every quantitative article published in five major Brazilian journals between 2012 and 2016. We also tested whether replication rates varied between established fields, more traditional and where the use of quantitative data is more common, and emerging fields. Our results show that transparency and reproduction are still in a development stage in Brazilian Political Science. Of the 650 articles reviewed, we asked for data to 197 quantitative articles. From those, only 28% agreed to share datasets and computed codes. We were able to attempt a replication for only 14%, and successfully reproduce the results of less than 5%. We conclude by suggesting the adoption of transparency and replicability procedures that are standard in other scientific communities.
Highlights
Scientific disciplines are facing a credibility crisis
Our results show that transparency and reproduction are still in a development stage in Brazilian Political Science
We analyzed every paper published in the leading Brazilian Political Science journals, and coded each one according to its methodological approach, response to the data request, and research replicability7
Summary
Scientific disciplines are facing a credibility crisis. In social sciences, significant published findings often cannot be replicated (Goodman, Fanelli and Ioannidis, 2016; Key, 2016; Christensen et al, 2019). The session presents the research design that includes the explanation of our hypotheses, criteria for classification of papers into fields (established or emerging) and methodology (quantitative or non-quantitative), details about the request for replication data and coding methodology for our dependent variables. We analyzed every paper published in the leading Brazilian Political Science journals, and coded each one according to its methodological approach, response to the data request, and research replicability. We coded Replicability as “1” for articles in which data that the author(s) provided produced the same results in terms of values, signs, and statistical significance From those 28 papers with complete data, we were able to fully replicate only 10 (35.7%), seven of which were from established fields. Shared complete data but and all reported results were replicable at same statistical significance, value, and sign
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