Jason P. Nance and Dylan J. Steinberg, “The Law Review Article Selection Process: Results from a National Study”

The abstract:

The student-edited law review has been a much criticized institution. Many commentators have expressed their belief that students are unqualified to determine which articles should be published in which journals, but these discussions have been largely based on anecdotal evidence of how journals make publication decisions. It was against that backdrop that we undertook a national survey of law reviews in an attempt to determine how student editors responsible for making publication decisions went about their task. This article compiles the results of that survey, which received 191 responses from 163 different journals. We analyzed 56 factors that influence the selection process and then grouped similar items together to form 17 constructs using factor analysis. Finally, we disaggregated the results to determine whether the results were significantly different based on the prestige of the journals involved. While many of our results confirm what has been widely assumed to be true, there are also some surprising findings. We found, for example, that Articles Editors seek to publish articles from well-known and widely-respected authors. It appears, however, that editors do not assume that prestigious authors produce the best scholarship, but instead they pursue the work of well-known authors because it can increase their journals’ prestige within the legal academic community. The survey reveals that editors are not nearly as likely to seek out articles dealing with hot or trendy topics as some commentators have assumed, and that author diversity plays almost no role in the article selection process. We hope that our study will provide some structure to the ongoing debate about how best to use students in the law review publication process and will allow a more informed consideration of whether students are sufficiently well-trained to evaluate articles and whether they are using the proper criteria.

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