“Why MANtoring is not the solution. A Rebuttal to ‘The association between early career informal mentorship in academic collaborations and junior author performance.’”

crossref(2020)

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摘要
The findings of AlShebli Makovi & Rahwan1 highlight an endemic problem in science: co-authoring with men is associated with greater numbers of citations for junior scientists than co-authoring with women. The reasons for this likely stem from a long history and culture in science where White, straight, cisgender men are the dominant force. Under the authors’ assumption that authorship is equal to mentorship (a notion we criticize below), the reported citation disparity by coauthor gender for junior scientists may simply reflect that under the current status quo there are more barriers for women to establish strong mentorship programs and secure resources to support their mentees compared to men. In other words, citation disparity is the problem, not the solution as proposed by the authors. We argue that the citation disparity is uncorrelated with mentorship and the quality of the publication. Unfortunately, AlShebli Makovi & Rahwan err in their publication in two ways: they define mentorship as co-authorship (albeit with conditions), and they prescribe the problem as a solution suggesting that junior scientists, especially women, ought to be mentored by men - a proposal we have aptly named “MANtoring”. These faulty interpretations and conclusions reveal a broader problem in scholarship: failure to critically examine structural biases and assumptions when evaluating and interpreting data showing disparity. Much work is needed to improve the culture of science and to provide a more fair and equitable environment for individuals of any background (women in this case, but a similar reasoning would apply to people historically marginalized based on gender, race, sexuality, class, and other dimensions) to thrive2. The AlShebli et al article is a wakeup call to authors in all disciplines to take greater care in interpreting and acting on their disparity data. Failure to do so could have catastrophic effects on science including the irony of exacerbating the very problems researchers are attempting to address.
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