Abstract
Alessandro Strumia recently published a survey of gender differences in publications and citations in high-energy physics (HEP). In addition to providing full access to the data, code, and methodology, Strumia (2021) systematically describes and accounts for gender differences in HEP citation networks. His analysis points both to ongoing difficulties in attracting women to HEP and an encouraging—though slow—trend in improvement.
Unfortunately, however, the time and effort that Strumia (2021) devoted to collating and quantifying the data are not matched by a similar rigor in interpreting the results. To support his conclusions, he selectively cites available literature and fails to adequately adjust for a range of confounding factors. For example, his analyses do not consider how unobserved factors—for example, a tendency to overcite well-known authors—drive a wedge between quality and citations and correlate with author gender. He also fails to take into account many structural and nonstructural factors—including, but not limited to, direct discrimination and the expectations that women form (and actions they take) in response to it—that undoubtedly lead to gender differences in productivity.
We therefore believe that a number of Strumia’s conclusions are not supported by his analysis. Indeed, we reanalyze a subsample of solo-authored papers from his data, adjusting for year and journal of publication, authors’ research age and their lifetime “fame.” Our reanalysis suggests that female-authored papers are actually cited more than male-authored papers. This finding is inconsistent with the “greater male variability” hypothesis that Strumia (2021) proposes to explain many of his results.
In the conclusion to his paper, Strumia states that “… dealing with complex systems, any simple interpretation can easily be incomplete …”. We agree entirely. Strumia’s simple—and, more importantly, simplistic—analysis and interpretation are far from complete.
Unfortunately, however, the time and effort that Strumia (2021) devoted to collating and quantifying the data are not matched by a similar rigor in interpreting the results. To support his conclusions, he selectively cites available literature and fails to adequately adjust for a range of confounding factors. For example, his analyses do not consider how unobserved factors—for example, a tendency to overcite well-known authors—drive a wedge between quality and citations and correlate with author gender. He also fails to take into account many structural and nonstructural factors—including, but not limited to, direct discrimination and the expectations that women form (and actions they take) in response to it—that undoubtedly lead to gender differences in productivity.
We therefore believe that a number of Strumia’s conclusions are not supported by his analysis. Indeed, we reanalyze a subsample of solo-authored papers from his data, adjusting for year and journal of publication, authors’ research age and their lifetime “fame.” Our reanalysis suggests that female-authored papers are actually cited more than male-authored papers. This finding is inconsistent with the “greater male variability” hypothesis that Strumia (2021) proposes to explain many of his results.
In the conclusion to his paper, Strumia states that “… dealing with complex systems, any simple interpretation can easily be incomplete …”. We agree entirely. Strumia’s simple—and, more importantly, simplistic—analysis and interpretation are far from complete.
Original language | English |
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Pages (from-to) | 263-272 |
Number of pages | 10 |
Journal | Quantitative Science Studies |
Volume | 2 |
Issue number | 1 |
DOIs | |
Publication status | Published - 8 Apr 2021 |