Figures and data in Gendered hiring and attrition on the path to parity for academic faculty

Figures
Tables
Additional files

11 figures, 3 tables and 1 additional file

Figures

Figure 1

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Change in women’s overall faculty representation for 111 academic fields between 2011 and 2020, decomposed into change due to hiring (horizontal axis) and change due to attrition (vertical axis, see Appendix 1 section, Decomposition of change in gender diversity), showing that hiring increased women’s representation for a large majority (87.4%) of fields, while it decreased women’s representation for five fields.

Point size represents the relative size of each field by number of faculty in 2020, and points are colored by Science, Technology, Engineering, and Mathematics (STEM) (black) or non-STEM (gray).

Figure 2

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Gendered faculty attrition has caused a differential loss of women faculty in both Science, Technology, Engineering, and Mathematics (STEM) and non-STEM fields.

(A) Gendered attrition in psychology has caused a loss of $- 1.83 p p$ ( $p < 0.01$ ) of women’s representation between 2011 and 2020, relative to a counterfactual model with gender-neutral attrition (see Methods section, Model of faculty hiring an attrition). In contrast, (B) gendered attrition in Ecology has not caused a statistically significant loss ( $+ 1.42 p p$ , $p = 0.24$ ). Relative to their field-specific counterfactual simulations, 15 academic fields and the STEM and non-STEM aggregations exhibit significant losses of women faculty due to gendered attrition (circles on C; two-sided test for significance relative to the gender-neutral null distribution derived from simulation, $α = 0.1$ ). The differences in the remaining 95 fields were not statistically significant (crosses on C), but we note that their lack of significance is likely partly attributable to their smaller sample sizes at the field-level compared to the all STEM and all non-STEM aggregations, which exhibited large and significant differences. Error bars for the non-STEM and STEM aggregations contain 95% of $n = 500$ stochastic simulations. No bars are included for field-level points to preserve readability.

Figure 3

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Projecting women’s representation under five policy scenarios.

(A) Observed (dotted line, 2011–2020) and projected (solid lines, 2021–2060) faculty gender diversity for Natural Sciences over time and (B) projections for 11 academic domains over 40 years under five policy scenarios. Line widths span the middle 95% of $N = 500$ simulations and ${\bar{Δ}}_{40}$ gives the mean change in women’s representation across domains over the 40-year period. Educ.=Education, J,M,C=Journalism, Media and Communications, Hum.=Humanities, Soc. Sci.=Social Sciences, and PA&P=Public Administration and Policy., Med.=Medicine, Nat. Sci.=Natural Sciences, Bus.=Business, Eng.=Engineering. See text for scenario explanations. OA = observed attrition, GNA = gender-neutral attrition, IR = increasing representation of women among hires ( $+ 0.5 p p$ each year), ER = equal representation of women and men among hires.

Appendix 1—figure 1

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The change in gender diversity between 2011 and 2020 can be approximately decomposed into parts due to hiring and attrition for each academic field, but there is a leftover residual term.

In practice, we find that the residual term tends to be very small, such that the decomposition is nearly ideal. The dotted line represents an ideal decomposition, where the change in women’s representation among faculty due to hiring and attrition perfectly matches the total observed change.

Appendix 1—figure 2

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Model validation: Differences between observed gender diversity outcomes and model-based outcomes.

(A) The mean outcomes of model-based simulations in psychology differ from the observed outcomes by $- 0.04 p p$ , and (B) in Ecology by $+ 0.11 p p$ , but these differences are not statistically significant. (C) Gender diversity outcomes from model-based simulations of hiring and attrition are statistically indistinguishable from observed gender diversity outcomes for all 111 fields, and for Science, Technology, Engineering, and Mathematics (STEM) and non-STEM aggregations, based on a two-sided test for significance relative to the model-based null distribution derived from simulation, $α = 0.1$ . Error bars for the non-STEM and STEM aggregations contain 95% of stochastic simulations. No bars are included for field-level points to preserve readability.

Appendix 1—figure 3

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Model validation: Projected 2060 faculty career age distributions for Natural Sciences from Figure 3 are similar to the observed career age distribution for Natural Sciences in 2020, for each projection scenario.

Line widths for the simulated scenarios span the middle 95% of simulations. OA = observed attrition, GNA = gender-neutral attrition, IR = increasing representation of women among hires (+0.5 pp each year), ER = equal representation of women and men among hires.

Appendix 1—figure 4

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Model selection.

(A) Four logistic regression models fit to observed faculty attrition data. Each model includes career age up to a different power, e.g., the model labeled ‘Career age order 3’ includes career age up to its third power: $l o g i t (p) = β_{0} + β_{1} a + β_{2} a^{2} + β_{3} a^{3} + β_{4} t$ where $a$ represents career age and $t$ represents year (see Methods section, Parameters for counterfactual model of 2011–2020, for details). The pattern in observed attrition risk becomes more noisy at higher career ages, because (B) there are relatively low numbers of faculty at the highest observed career ages.

Appendix 1—figure 5

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Model selection.

(A) Four logistic regression models fit to observed faculty hiring data, where the outcome variable is the gender of the faculty hire (1=woman, 0=man). Each model includes career age up to a different power, e.g., the model labeled ‘Career age order 3’ includes career age up to its third power: $l o g i t (p) = β_{0} + β_{1} a + β_{2} a^{2} + β_{3} a^{3} + β_{6} t$ where $a$ represents career age and $t$ represents year (see Methods section, Parameters for counterfactual model of 2011–2020, for details). The pattern in the gender representation among new faculty hires becomes more noisy at higher career ages, because (B) there are relatively low numbers of faculty hired at higher career ages.

Appendix 1—figure 6

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Sensitivity analysis: Replicating the counterfactual analysis from Results section, Quantifying the impact of gendered attrition using career age up to its third power in the associated logistic regressions model, instead of the fifth power (see Appendix 1 section, Model validation and sensitivity analysis, for details).

Findings under this parameterization are qualitatively very similar to those presented in Figure 2, indicating that the results are robust to modest changes to model parameterization.

Appendix 1—figure 7

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Fraction of women among tenure-track faculty hires over time at U.S. PhD-granting institutions.

Women’s share of new hires is observed to increase at around $0.91 p p$ annually (t-test, $p < 0.001$ ), measured by an ordinary least squares regression fit (shown in purple).

Appendix 1—figure 8

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Career age distribution of women (red) and men (blue) tenured and tenure-track faculty across all academic fields.

Career age is measured as the number of years since earning a PhD. There are substantially more men faculty with high career ages than women faculty.

Tables

Appendix 1—table 1

Trends in women’s representation among new hires from 2012 to 2020 for 11 academic domains, along with academia overall.

We use linear regression to measure the expected change in women’s concentration among new hires each year, and find that women’s representation has been increasing in 6 of the 11 domains over time, at rates ranging from 0.58 pp to 1.30 pp per year. The remaining 5 domains have not exhibited significant linear trends. Overall, the fraction of women among hires has been increasing in academia over time (Appendix 1—figure 7). These findings are qualitatively replicated using logistic regression, so we present the linear regression results here for enhanced interpretability.

Academic domain	Estimated annual change (pp)	p
Mathematics and Computing	0.25	0.095
Social Sciences	1.18^†	0.006
Natural Sciences	1.30^‡	0.000
Engineering	0.95^‡	0.000
Health	0.58*	0.020
Humanities	1.18^†	0.002
Public Administration and Policy	0.22	0.717
Business	0.38	0.089
Medicine	0.98^†	0.009
Journalism, Media and Communication	0.49	0.173
Education	0.34	0.057
Academia Overall	0.91^‡	0.000

*

p<0.05.
†

p<0.01.
‡

p<0.001.

Appendix 1—table 2

Changes in women’s representation through Hiring, Attrition, and Gendered Attrition in Academic Fields (2011–2020).

Observed changes in women’s representation resulting from hiring and attrition, expressed in percentage points (pp), based on data from Figure 1, and the estimated average change in women’s representation due to gendered attrition as depicted in Figure 2, accompanied by the 2.5 percentile and 97.5 percentiles of simulations in parentheses. The analysis covers 111 academic fields.

Field	Observed $Δ_{hiring}$	Observed $Δ_{attrition}$	Est. $Δ_{gendered attrition}$
Health
Environmental Health Sciences	+6.65	+3.46	+2.40 (–1.03, +5.60)
Nursing	–4.34	+0.48	+0.55 (–0.59, +1.65)
Public Health	+4.48	+0.71	–0.11 (–1.89, +1.60)
Human Development and Family Sciences	+3.19	–0.48	–2.81 (–5.44, –0.25)
Speech and Hearing Sciences	+3.30	+2.84	+2.67 (–0.81, +6.31)
Exercise Science, Kinesiology, Rehab, Health	+6.26	–1.96	–2.05 (–3.63, –0.27)
Nutrition Sciences	+0.31	+0.12	–1.18 (–3.62, +1.37)
Communication Disorders and Sciences	+6.11	+1.32	+1.26 (–1.77, +4.99)
Health, Physical Education, Recreation	+2.40	–0.35	–0.78 (–4.34, +2.52)
Social Work	+4.73	–0.04	–1.23 (3.21, +0.60)
Education
Education	+1.55	+1.07	–0.28 (–2.21, +1.62)
Special Education	+3.64	–2.24	–3.41 (–3.41, –0.28)
Education Administration	+0.91	+2.34	–0.74 (–2.84, +1.51)
Counselor Education	+5.08	+0.86	–0.49 (–3.36, +2.49)
Curriculum and Instruction	+0.97	+1.26	–1.61 (–3.70, +0.22)
Journalism, Media and Communication
Communication	+3.43	+0.20	–1.16 (–3.01, +0.80)
Mass Communications and Media Studies	+4.30	+1.22	+0.63 (–1.61, +2.73)
Humanities
Theological Studies	+0.51	+0.71	–0.91 (–3.07, +1.02)
Asian Languages	–0.54	+2.43	+1.78 (–1.91, +5.32)
Slavic Languages and Literatures	+3.34	+3.60	+0.93 (–3.00, +5.18)
Classics and Classical Languages	+3.33	+2.25	+0.20 (–2.14, +2.69)
French Language and Literature	+0.50	+1.23	–0.38 (–3.69, +3.30)
Germanic Languages and Literatures	+3.72	_3.23	+2.08 (–1.44, +5.76)
Theatre Literature, History and Criticism	+0.79	+2.87	+0.40 (–4.04, +4.58)
Art History and Criticism	+2.18	+2.67	+0.44 (–1.85, +2.86)
Asian Studies	–1.17	+1.04	+0.72 (–2.84, +3.90)
History	+2.84	+2.11	–0.64 (–1.69, +0.44)
Urban and Regional Planning	+5.71	+1.74	–1.01 (–4.53, +2.34)
Linguistics	–0.15	+2.19	+0.44 (–2.12, +3.29)
English Language and Literature	+2.17	+0.63	–1.80 (–2.80, –0.80)
Near and Middle Eastern Languages and Cultures	+5.80	–0.22	–0.87 (–4.87, +3.41)
Music	+3.72	–0.99	–1.10 (–2.54, +2.54)
Philosophy	+5.03	+0.04	–1.84 (–3.37, –0.24)
Religious Studies	+2.68	–0.22	–1.97 (–4.28, +0.08)
Comparative Literature	+1.78	+1.17	–0.58 (–4.04, +2.40)
Spanish Language and Literature	+2.39	+1.94	–0.55 (–3.09, +1.98)
Architecture	+4.53	+2.64	+0.77 (–2.31, +3.72)
Public Administration and Policy
Public Policy	+5.16	–0.88	–1.88 (–3.85, +0.23)
Public Administration	+6.49	+0.82	–1.11 (–3.71, +1.62)
Social Sciences
Sociology	+3.99	+1.51	–1.43 (–2.92, +0.03)
Gender Studies	–2.71	+1.40	+2.28 (–0.56, +5.25)
Anthropology	+3.68	+2.30	–0.42 (–1.94, +1.31)
Political Science	+4.35	+1.00	–0.15 (–1.41, +0.98)
International Affairs	+6.99	–1.58	–2.74 (–5.31, –0.33)
Geography	+6.65	+0.80	–0.51 (–2.26, +1.82)
Psychology	+5.81	–0.04	–1.83 (–2.82, –0.74)
Agricultural Economics	+6.46	+0.43	–0.87 (–4.10, +1.76)
Educational Psychology	+3.51	–0.73	–0.84 (–3.75, +2.13)
Economics	+2.93	+0.45	–0.61 (–1.66, +0.50)
Criminal Justice and Criminology	+6.26	+1.12	–0.63 (–3.47, +2.28)
Business
Accounting	+3.02	+0.47	–1.35 (–3.37, +0.61)
Marketing	+4.43	+0.06	–1.09 (–3.11, +0.99)
Management Information Systems	+3.61	–2.50	–2.44 (–4.61, –0.10)
Finance	+3.13	–0.01	–0.64 (–2.26, +0.88)
Business Administration	+4.21	–0.34	–0.23 (–1.98, +1.67)
Management	+2.76	–0.20	–1.53 (–2.94, +0.17)
Medicine
Genetics	+4.31	+1.04	+0.25 (–2.77, +3.00)
Pharmaceutical Sciences	+6.88	–0.34	–1.42 (–3.78, +0.96)
Epidemiology	+3.95	+0.29	–0.67 (–3.04, +1.59)
Pharmacology	+2.91	+0.61	–0.38 (–2.19, +1.36)
Pharmacy	+10.25	–1.54	–1.36 (–4.17, +1.52)
Physiology	+5.21	+0.26	–1.19 (–3.05, +0.72)
Veterinary Medical Sciences	+10.34	–1.92	–2.52 (–4.31, –0.74)
Immunology	+3.80	+2.23	+0.41 (–1.55, +2.35)
Natural Sciences
Entomology	+6.49	+0.85	–1.42 (–4.55, +1.21)
Soil Science	+4.64	+2.10	+0.52 (–2.46, +3.38)
Anatomy	+6.05	–0.82	–1.61 (–4.11, +0.84)
Natural Resources	+4.70	+1.64	+0.09 (–2.23, +2.49)
Plant Sciences	+4.74	+2.19	+1.01 (–1.61, +3.68)
Plant Pathology	+4.88	+1.51	–1.70 (–4.92, +1.69)
Biophysics	+4.00	–0.41	–0.75 (–3.31, +1.71)
Food Science	+4.16	+0.51	–1.08 (–4.07, +2.03)
Pathology	+5.25	–2.58	–1.50 (–3.14, +0.04)
Horticulture	+2.60	–0.12	–1.66 (–5.07, +1.69)
Biostatistics	+3.58	–0.69	–0.68 (–3.49, +2.02)
Agronomy	+4.82	+1.18	–0.93 (–3.96, +1.68)
Animal Sciences	+7.46	+1.74	–0.51 (–2.68, +1.63)
Forestry and Forest Resources	+6.54	+0.37	–1.82 (–4.83, +0.71)
Geology	+5.93	+1.54	–0.38 (–1.85, +1.03)
Biological Sciences	+5.22	+1.69	–0.04 (–1.07, +0.92)
Physics	+2.32	+1.00	–0.25 (–1.00, +0.50)
Chemistry	+3.96	+0.40	–0.87 (–1.77, +0.02)
Biochemistry	+3.91	+0.25	–0.89 (–2.22, +0.40)
Chemical Engineering	+4.08	+0.21	–0.87 (–2.38, +0.63)
Environmental Sciences	+5.88	+1.56	–0.64 (–2.62, +1.16)
Atmospheric Sciences and Meteorology	+4.59	+2.42	+1.30 (–1.00, +3.30)
Biomedical Engineering	+4.29	+2.08	+0.44 (–1.38, +2.40)
Microbiology	+5.28	+0.32	–0.99 (–2.51, +0.59)
Cell Biology	+4.82	+0.33	–0.48 (2.06, +1.11)
Marine Sciences	+5.20	+1.95	–0.08 (–2.85, +2.44)
Astronomy	+2.89	+1.52	+0.08 (–1.22, +1.35)
Evolutionary Biology	+6.79	+1.88	+0.54 (–2.10, +3.21)
Ecology	+6.23	+3.54	+1.42 (–0.88, +3.92)
Neuroscience	+4.19	–0.07	–0.75 (–2.63, +1.02)
Molecular Biology	+3.40	+0.83	–0.16 (–1.83, +1.53)
Mathematics and Computing
Statistics	+2.89	+1.64	+0.24 (–1.43, +1.72)
Mathematics	+2.86	+0,65	–0.44 (–1.22, +0.41)
Computer Engineering	+2.66	+0.23	–0.18 (–1.08, +0.79)
Computer Science	+2.26	–0.09	–0.55 (–1.51, +0.32)
Information Technology	+0.88	–1.17	–0.29 (–2.68, +2.01)
Information Science	+0.81	–1.00	–1.70 (–4.20, +1.05)
Engineering
Mechanical Engineering	+3.39	+0.60	–0.18 (–1.09, +0.75)
Systems Engineering	+3.29	+0.48	–1.29 (–3.85, +1.15)
Aerospace Engineering	+2.53	+1.18	+0.33 (–1.27, +1.93)
Electrical Engineering	+2.18	+0.46	–0.22 (–1.11, +0.66)
Agricultural Engineering	+4.74	+1.22	–0.16 (–1.96, +1.44)
Operations Research	+2.53	–0.39	–0.99 (–3.44, +1.32)
Environmental Engineering	+4.94	+0.91	–0.91 (–2.30, +0.52)
Civil Engineering	+4.30	+1.54	–0.25 (–1.51, +1.07)
Materials Engineering	+4.68	+0.46	–0.85 (–2.76, +0.80)
Industrial Engineering	+1.86	+1.66	+0.14 (285, –2.25, +2.54)

Appendix 1—table 3

Number of faculty by field and gender, 2020.

Estimated counts of women and men faculty based on 2020 faculty rosters and name-based gender inference (Van Buskirk et al., 2023).

Field	Women	Men	Pct. women
Health
Environmental Health Sciences	285	430	39.9
Nursing	3531	515	87.3
Public Health	1813	1555	53.3
Human Development and Family Sciences	765	486	61.2
Speech and Hearing Sciences	352	184	65.7
Exercise Science, Kinesiology, Rehab, Health	1612	1555	50.9
Nutrition Sciences	722	604	54.4
Communication Disorders and Sciences	450	215	67.7
Health, Physical Education, Recreation	356	427	45.5
Social Work	1308	696	65.3
Education
Education	1301	857	60.3
Special Education	452	277	62.0
Education Administration	986	840	54.0
Counselor Education	566	405	58.3
Curriculum and Instruction	1204	654	64.3
Journalism, Media and Communication
Communication	1054	1208	46.6
Mass Communications and Media Studies	947	1093	46.4
Humanities
Theological Studies	324	958	25.3
Asian Languages	189	257	42.4
Slavic Languages and Literatures	198	186	51.6
Classics and Classical Languages	513	596	46.3
French Language and Literature	291	253	53.5
Germanic Languages and Literatures	244	264	48.0
Theatre Literature, History and Criticism	574	615	48.3
Art History and Criticism	1006	912	52.5
Asian Studies	237	344	40.8
History	2071	3008	40.8
Urban and Regional Planning	335	506	39.8
Linguistics	404	467	46.4
English Language and Literature	2968	2018	50.4
Near and Middle Eastern Languages and Cultures	160	268	37.4
Music	1239	2747	31.1
Philosophy	788	1773	30.8
Religious Studies	446	900	33.1
Comparative Literature	354	364	49.3
Spanish Language and Literature	438	409	51.7
Architecture	606	1205	33.5
Public Administration and Policy
Public Policy	687	1146	37.5
Public Administration	446	645	40.9
Social Sciences
Sociology	1501	1483	50.3
Gender Studies	474	82	85.3
Anthropology	1305	1291	50.3
Political Science	1345	2702	33.2
International Affairs	426	851	33.4
Geography	482	933	34.1
Psychology	2826	3215	46.8
Agricultural Economics	171	532	24.3
Educational Psychology	555	463	54.5
Economics	804	3039	20.9
Criminal Justice and Criminology	466	588	44.2
Business
Accounting	536	1186	31.1
Marketing	516	1069	32.6
Management Information Systems	231	867	21.0
Finance	377	1503	20.1
Business Administration	546	1473	27.0
Management	880	2136	29.2
Medicine
Genetics	324	612	34.6
Pharmaceutical Sciences	444	912	32.7
Epidemiology	778	747	51.0
Pharmacology	512	1268	28.8
Pharmacy	567	639	47.0
Physiology	620	1446	30.0
Veterinary Medical Sciences	956	1281	42.7
Immunology	677	1303	34.2
Natural Sciences
Entomology	191	494	27.9
Soil Science	163	506	24.4
Anatomy	387	763	33.7
Natural Resources	340	877	27.9
Plant Sciences	250	656	27.6
Plant Pathology	166	446	27.1
Biophysics	223	689	24.5
Food Science	353	474	42.7
Pathology	1199	1868	39.1
Horticulture	117	394	22.9
Biostatistics	457	676	40.3
Agronomy	149	526	22.1
Animal Sciences	337	749	31.0
Forestry and Forest Resources	229	655	25.9
Geology	770	2098	26.8
Biological Sciences	1895	3656	34.1
Physics	800	4364	15.5
Chemistry	1024	3691	21.8
Biochemistry	1001	2884	25.8
Chemical Engineering	405	1692	19.3
Environmental Sciences	624	1416	30.6
Atmospheric Sciences and Meteorology	267	757	26.1
Biomedical Engineering	426	1284	24.9
Microbiology	884	1815	32.8
Cell Biology	844	1699	33.2
Marine Sciences	279	722	27.9
Astronomy	416	1937	17.7
Evolutionary Biology	293	521	36.0
Ecology	370	662	35.9
Neuroscience	721	1443	33.3
Molecular Biology	732	1669	30.5
Mathematics and Computing
Statistics	474	1598	22.9
Mathematics	1072	4688	18.6
Computer Engineering	584	3581	14.0
Computer Science	885	4291	17.1
Information Technology	211	759	21.8
Information Science	404	723	35.8
Engineering
Mechanical Engineering	562	3428	14.1
Systems Engineering	152	654	18.9
Aerospace Engineering	209	1364	13.3
Electrical Engineering	613	3914	13.5
Agricultural Engineering	378	1386	21.4
Operations Research	149	632	19.1
Environmental Engineering	517	1854	21.8
Civil Engineering	585	2217	20.9
Materials Engineering	340	1439	19.1
Industrial Engineering	212	838	20.2

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Nicholas LaBerge
Kenneth Hunter Wapman
Aaron Clauset
Daniel B Larremore

(2024)

Gendered hiring and attrition on the path to parity for academic faculty

eLife 13:RP93755.

https://doi.org/10.7554/eLife.93755.3

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Gendered faculty attrition has caused a differential loss of women faculty in both Science, Technology, Engineering, and Mathematics (STEM) and non-STEM fields.

Projecting women’s representation under five policy scenarios.

The change in gender diversity between 2011 and 2020 can be approximately decomposed into parts due to hiring and attrition for each academic field, but there is a leftover residual term.

Model validation: Differences between observed gender diversity outcomes and model-based outcomes.

Model validation: Projected 2060 faculty career age distributions for Natural Sciences from Figure 3 are similar to the observed career age distribution for Natural Sciences in 2020, for each projection scenario.

Model selection.

Model selection.

Fraction of women among tenure-track faculty hires over time at U.S. PhD-granting institutions.

Career age distribution of women (red) and men (blue) tenured and tenure-track faculty across all academic fields.

Trends in women’s representation among new hires from 2012 to 2020 for 11 academic domains, along with academia overall.

Changes in women’s representation through Hiring, Attrition, and Gendered Attrition in Academic Fields (2011–2020).

Number of faculty by field and gender, 2020.

MDAR checklist

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