Jeremy Freese Overcoming Objections to Open-Source Social Science Sociological Methods & Research 2007 36: 220-226.

February 7, 2010

Commentators appreciate the benefits of developing improved standards for replicating quantitative results in sociology. Nonetheless, reservations remain, and the author addresses several of them and explains why improved replication standards do not endanger participant confidentiality, do not undermine incentives for collecting data, do not need to wait for greater standardization of data formats, need not require that editors assign a reviewer to actually replicate results, and do not diminish methodological diversity in any positive sense. The author concludes by encouraging sociologists to find a way of moving beyond intermittent discussions of replication standards to collective action.

Key Words: replication • data sharing • data archiving • transparency

Andrew Abbott Notes on Replication Sociological Methods & Research 2007 36: 210-219.

February 7, 2010

This comment argues that although replication will and should gain ground in sociology, that process will be complicated by issues of ownership, mechanics, and security. Replicationism will also change the economy of peer review. Ironically, it could also reveal that sociologists have less agreement on methodological issues than we think.

Key Words: replication • data ownership • security • journals • peer review

Glenn Firebaugh Replication Data Sets and Favored-Hypothesis Bias: Comment on Jeremy Freese (2007) and Gary King (2007) Sociological Methods & Research 2007 36: 200-209.

February 7, 2010

Jeremy Freese makes the case for data sharing as a condition of publication for quantitative research in sociology, and Gary King tells us of a Dataverse Network under construction that is designed to routinize the process of posting and storing such data sets. No matter how user-friendly that network turns out to be, it is clear that no system is entirely cost-free, either for researchers or for journal editors. It is important, then, to determine whether the benefits of mandatory data sharing(or “data relinquishment,” as Herrnson calls it) would outweigh the costs. In this comment, the author discusses the issue from his vantage point as a former editor and concludes that the benefits of such a requirement most likely would exceed the costs.

Key Words: data dredging • data sharing • peer review • replication • transparency in science • verification

Replication Standards for Quantitative Social Science: Why Not Sociology?

February 7, 2010

Jeremy Freese Replication Standards for Quantitative Social Science: Why Not Sociology? Sociological Methods & Research 2007 36: 153-172. SMR 36:2 was a special issue on Replication and Data Analysis.

Jeremy FreeseThe credibility of quantitative social science benefits from policies that increase confidence that results reported by one researcher can be verified by others. Concerns about replicability have increased Read the rest of this entry »

Christopher Winship Introduction to the Special Section on Replication and Data Access Sociological Methods & Research 2007 36: 151-152.

February 7, 2010

Introduction to the Special Section on Replication and Data Analysis.