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Repairing the scaffolding: women authors in Paleobiology

Published online by Cambridge University Press:  07 December 2023

Nan Crystal Arens*
Affiliation:
Department of Geoscience, Hobart & William Smith Colleges, Geneva, New York 14456, U.S.A.
Levi Holguin
Affiliation:
Department of Anthropology, Hobart & William Smith Colleges, Geneva, New York 14456, U.S.A.
Natalie Sandoval
Affiliation:
Department of Sociology, Hobart & William Smith Colleges, Geneva, New York 14456, U.S.A.
*
Corresponding author: Nan Crystal Arens; Email: arens@hws.edu

Abstract

Women are underrepresented in paleontology. Despite more women students, representation at senior levels remains low. To advance professionally, scientists must disseminate their research through peer-reviewed publications. We examine gendered authorship patterns in Paleobiology to ask whether the publishing infrastructure supports the Paleontological Society's gender-equity goals. We reviewed all papers published in Paleobiology from its inception in 1975 through 2021. For each paper, we recorded each author, the author's position in the author list, and the total number of authors on each paper. We coded gender based on a combination of personal communication and pronouns used in publicly available information. We compared author demographics with anonymized membership data from the Paleontological Society. Over the journal's run, the number of authors per paper increased due to cultural shifts toward collaborative work and acknowledging student contributions with coauthorship. These trends contribute to proportionally more women authors, beginning in the early 2000s. Despite these increases, women remain chronically underrepresented. In 2018, 2019, and 2021, the proportion of women authors in Paleobiology paralleled membership in the Paleontological Society. However, in 2020, Paleobiology published fewer women authors than expected based on society membership. This echoes declines in women's scholarly productivity in the first year of the COVID-19 pandemic observed across many disciplines. We offer four recommendations: (1) practice double-anonymous peer review; (2) recruit editors from diverse backgrounds who invite reviewers with diverse backgrounds; (3) democratize manuscript review by selecting reviewers from a disaggregated reviewer database; and (4) gather and analyze demographic data for both submissions and publications.

Information

Type
On The Record
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Paleontological Society
Figure 0

Figure 1. Gender (men and women only) of authors in each volume of Paleobiology 1975–2021. (A) Tallies of authors by binary gender overlaid on Paleontological Society membership for 2018–2021, the only years for which complete demographic data were available. Paleontological Society membership included a variety of gender descriptors (see Supplementary Table 1). We grouped transgender members with their authentic gender (e.g., transwomen with women), and all nonbinary markers into the category gender diverse. PNTA denotes those members who preferred not to disclose their gender. (B) Author gender normalized as a proportion. (C) Standardized residuals of a linear model describing the relationship between the number of authors, grouped by gender (M = men, W = women), in each volume across time. Negative residuals represent values below that expected for equal gender representation; positive residuals mean overrepresentation. Least-squares lines of best fit added to each gender group.

Figure 1

Figure 2. (A) Tally of first authors by gender for papers with more than one author. Lines of best fit represent least-squares linear models for each gender. (B) Standardized residuals of a linear model describing the relationship between the first authors in each volume across time. Negative residuals represent values below that expected for equal gender representation; positive residuals mean overrepresentation. Least-squares lines of best fit added to each gender. (C) Tally of single authors on paper in Paleobiology (1975–2021). Lines of best fit represent least-squares linear models for each gender. (D) Standardized residuals of a linear model describing the pattern of first authors in each volume across time. Least-squares line of best fit added to each gender. Negative residuals constitute underrepresentation; positive residuals mean overrepresentation. For all graphs, M = men; W = women.