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Downloaded by guest on September 26, 2021 a Huang disciplines Junming and countries scientific across in careers inequality gender of comparison Historical eeaietefidn oalo cec.Afrhrcomplication further www.pnas.org/cgi/doi/10.1073/pnas.1914221117 A and . compare of countries, to all specific difficult to in finding it scientists the making generalize active institutions, stud- of or case subsets on the disciplines, to based of is limited differences much ies gender Consequently, on evidence population. available across academic genders both diverse of scientists the for careers full struct puzzle, productivity effective it. enact address the to to of policies ability community’s consequences scientific differentiate the the to complicating ability from our causes limited interre- has the deep factors the these systemic Indeed, of that academic. latedness evidence female increasing the impede dismisses simplistic barriers data female such the However, of equivalent. of programs not reading are perpetuate (28). scientists the could male climate that and differences work interpretation gender naive and these the aca- (27), of (25), specialization persistence stereotypes The (26), role peer of 24), rank role (23, demic the collaboration (21), to (22), allocation (17–19), their review explanations resource responsibilities of (20), possible family absences course of in career plethora the differences a over from inspired women (14–16), has than which more career, publish men evidence persistent that (9–13)—the differ- puzzle” gender “productivity of the epitome is The ence (1–8). countries across and documented disciplines well all are salary, and recognition, , ity, G inequality gender and institutions for careers consequences women’s makers. important policy of rephrase with sustainability help academia, can the in academia around in conversation comprehen- inequality the gender This of remain. picture still impact, sive and differences productivity productivity in although of pub- differences portion career-wise in large a reported differences size explain the rates that same dropout demonstrate and the annual lengths we career for comparable Finally, lishing impact a work. career-wise of at equivalent body publish invariants, have women and gender and rate two men impact. uncover that and we finding productivity though, both an surprisingly, by in accompanied Most differences was years gender 60 of past increase the over of science participation of in increase women the disci- paradoxically, career 13 that, and find countries publishing We 83 plines. covering whose 2010, and 1955 authors between ended gender-identified over million of 1.5 publication publishing complete academic the reconstructing of by analysis careers per- bibliometric in a differences through a gender offer formance we longitudinal Here, of citations. picture fewer comprehensive acquires work their throughout and articles career, differ- fewer a publish underrepresented and gender disciplines are scientific of women most that in 2019) evidence 15, suggesting August fragmented, academia review in for yet (received ences 2020 extensive, 22, January is approved and There NJ, Princeton, University, Princeton Fiske, T. Susan by Edited and 02115; MA Boston, Hungary School, Budapest, Medical 1051 Harvard University, Hospital, Women’s and Brigham Medicine, China; Italy; 611731, Turin, Chengdu 10126 08540; China, NJ of Princeton, University, and Princeton Science Electronic of University Engineering, ewr cec nttt n eateto hsc,Nrhatr nvriy otn A02115; MA Boston, University, Northeastern Physics, of Department and Institute Science Network e ehdlgclosal a entedfclyt recon- to difficulty the been has obstacle methodological key A h ubro eaeadml uhr,terproductiv- their authors, male in and disparities female by of captured number academia, the in differences ender f | hnigDvso fNtokMdcn,BihmadWmnsHsia,HradMdclSho,Bso,M 02115; MA Boston, School, Medical Harvard Hospital, Women’s and Brigham Medicine, Network of Division Channing cec fscience of science a,b,c,1 lxne .Gates J. Alexander , | STEM d eateto optrSine TUiest fCpnae,20 oehgn Denmark; Copenhagen, 2300 Copenhagen, of University IT Science, Computer of Department | cetfi careers scientific a,1 oet Sinatra Roberta , d,e doi:10.1073/pnas.1914221117/-/DCSupplemental. at online information supporting contains article This 2 1 under distributed BY).y is (CC article authors access open other This Submission.y All Direct Scipher health. PNAS a in and is article networks Foodome, This of Nomix, role interest. y of the competing no founder explore declare that is companies A.-L.B. wrote Medicine, statement: A.-L.B. and interest R.S., Competing A.J.G., J.H., and data; per- analyzed paper. A.J.G. y A.J.G. the and J.H. and research; J.H. designed research; A.-L.B. formed and R.S., A.J.G., J.H., contributions: Author and 1955 lacks systematically between limitations, published methodological papers to due all but of 2010 extensive 33% This careers. covers female sample and S2.H male 2010 complete and and compare S1 1955 cally 1,110,194 sections between Appendix , and ended (SI careers female publishing countries (412,808 whose Appendix scientists 83 male) 1,523,002 (SI spanning on disciplines male) focused major 2,146,926 authors 13 million and and 3 Sci- over female of a gender of Appendix , (856,889 the deploying (SI identified Web By we identification S2.E), 2016. the gender section and for in 1900 method record between state-of-the-art database publication (WoS) their ence from scientists boundaries. national careers and publishing disciplinary complete across capture scientists we all if for only possible landscape, is survey geographical to which truly and need disciplinary, To we longitudinal, inequality, (30). whole gender sizes (29), the the sample citations of small roots the in of the exacerbated of understand fraction is majority large that the effect a receive dispropor- an produce and a authors publications academia: of the of number nature small heavy-tailed tionately the from arises ..adAJG otiue qal oti work. this to equally contributed A.J.G. and J.H. owo orsodnemyb drse.Eal [email protected] Email: addressed. be may correspondence whom To n Albert-L and , esto rudtessanblt fwmnscresin and careers institutions for women’s makers. policy consequences of important sustainability gender with con- academia, the the of rephrase around help picture can versation comprehensive lengths publishing academic career This in publishing inequality rates. differ- different gender dropout by of and explained impact and are productivity ences publications. the of equivalent suggests number have total This same and a the year publish for gen- per impact women career-wise these papers and increased of men that number has find comparable women years we Yet, of 60 differences. number past der the the in over (STEM) increase academics mathematics the across Paradoxically, and careers fields. engineering, academic of technology, impact science, and in productivity differences total gender the significant suggests evidence Empirical Significance ee ercntutdtefl ulsigcre f7,863,861 of career publishing full the reconstructed we Here, h eateto ewr n aaSine eta European Central Science, Data and Network of Department c aladMri yhsCne nCneprr China, Contemporary on Center Wythes Marcia and Paul aszl b ´ ope a,Sho fCmue cec and Science Computer of School Lab, CompleX Barab o ´ asi ´ a,f,g,h,2 raieCmosAtiuinLcne4.0 License Attribution Commons Creative y y ,alwn st systemati- to us allowing ), https://www.pnas.org/lookup/suppl/ .W then We S2). section , NSLts Articles Latest PNAS e g S Foundation, ISI eatetof Department | f8 of 1

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Fig. 1. Gender imbalance since 1955. (A) The number of active female (orange) and male (blue) authors over time and the total proportions of authors (Inset). (B and C) The proportion of female authors in several disciplines (B) and countries (C); for the full list, see SI Appendix, Tables S3 and S4.(D) The career of a scientist is characterized by his or her temporal publication record. For each publication, we identify the date (gold dot) and number of citations after 10 years c10 (gold line, lower). The aggregation by year provides the yearly productivity (light gold bars), while the aggregation over the entire career yields the total productivity (solid yellow bar, right) and total impact (solid yellow bar, right). Career length is calculated as the time between the first and last publication, and the annual productivity (dashed gold line) represents the average yearly productivity. Authors drop out from our data when they published their last article.

authors from China, Japan, Korea, Brazil, Malaysia, and Singa- using different criteria for publication inclusion and methodolo- pore (SI Appendix, section S2). To demonstrate the robustness gies for career reconstruction (SI Appendix, sections S1 and S6). of our findings to database bias and author disambiguation Our focus on bibliometric data limits our analysis to publishing errors, we independently replicated our results in two addi- careers and is unable to capture the career dynamics of teaching, tional datasets: the Graph (MAG) (31) administrative, industrial, or government related research activ- and the Digital Bibliography & Library Project (DBLP), each ities. Nevertheless, our efforts constitute an extensive attempt

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Fig. 3. Controlling for career length. (A and B) The gender gap in career length strongly correlates with the gender gap in productivity across disciplines (Pearson correlation, 0.80) (A) and countries (Pearson correlation, 0.56) (B). A gender gap of 0.0% indicates gender equality, while negative gaps indicate the career length or productivity is greater for male careers, and positive gaps indicate the feature is greater for female careers. (C) In a matching experiment, equal samples are constructed by matching every female author with a male author having an identical discipline, country, and career length. (D) The average productivity provided by the matching experiment for career length compared to the population; the gender gap is reduced from 27.4% in the population to 7.8% in the matched samples. (E) The average impact provided by the matching experiment for career length compared to the original unmatched sample. Where visible, error bars denote 1 SD.

4 of 8 | www.pnas.org/cgi/doi/10.1073/pnas.1914221117 Huang et al. 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(Fig. also is (Fig. 7.8% impact total to the in 31.0 gap produc- gender the total from in from reduces gap these scientist gender tivity In the length. male samples, career which a same length-matched in the career to exactly first, with matched the and discipline of is same discipline subset scientist a same female as the each population, matched from female second each scientist a for male population, 3C a first (Fig. select the gender In we the length. eliminate per- scientist, we career to this, designed in For experiment gaps length. the matching career and in a variation productivity form the 2 total by (Fig. the explained above of observed be gaps much gender how impact ask total that next gap we gender terns, productivity con- total In (7.8%). a careers longer productivity in 35.1%. 19.2% exceeds total resulting have in (2.6%), men average, chemistry, physics gap on and applied gender biology in in the smallest trast, gen- is is the so length example, small career as For a in have productivity. gap also with total der length difference countries in career gender difference or the large gender disciplines in a differences those gender have while small also differ- productivity, gender length total correlation large career in a strong the with this in countries words, ence or disciplines other Pear- that In B; 3 implies (Fig. 0.58). country correlation, and discipline 0.80) son by correlation, scientists Pearson subdivide 3A; we (Fig. when career- gap the a productivity and by rooted gap wise supported career-length is is the conclusion between productivity correlation This total strong lengths. career in in variation variations the in of fraction 2 nificant (Fig. affiliation 2T or (Fig. country, 2P discipline, pub- either (Fig. Q, to by ceasing years grouped authors before female 9.3 are of years authors age only academic 11.0 male terminal is average average, of sci- the on age while each lish, that, of academic is 1D) finding an this (Fig. database, if reach length the test career To in the length. entist measured career we in case, differences the productivity by career total determined in gap is gender large the that suggests tists of roots possible the gaps. probe gender us observed next, helps the show result, we key As our invariant, metrics. this performance in quantity invariant der oadestefcosgvrigteedo publishing a of end the governing factors the address To pat- productivity annual indistinguishable largely the Given scien- female and male of productivity annual comparable The and R, .Tkntgte,Fg 2 Fig. together, Taken ). and n a enicesn vrteps 0years 60 past the over increasing been has and S) .W hnconstructed then We ). 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Fig. 4. Author’s age-dependent dropout rate. (A) Dropout rate for male (blue) and female (orange) authors over their academic ages. (B) The cumulative survival rate for male and female authors over their academic ages. (C and D) The effect of controlling for the age-dependent dropout rate on the gender gaps in total productivity (C) and impact (D). (E) The total impact gap is eliminated in the matched sample based on total productivity. (F) The gender gap in the total number of collaborators is eliminated in the matched sample based on total productivity.

The average causal effect of this differential attrition is accounting for about 67% of the productivity and impact gaps. demonstrated through a counterfactual experiment in which we Yet, the differential dropout rates do not account for the whole shorten the careers of male authors to simulate dropout rates effect, suggesting that auxiliary disruptive effects, from percep- matching their female counterparts at the same career stage tion of talent to resource allocation (15, 21), may also play a (Fig. 4 C and D and SI Appendix, section S4.F). We find that potential role. under similar dropout rates, the differences in total productiv- The reduction of the gender gaps in both total productiv- ity and total impact reduce by roughly two-thirds, namely from ity and total impact by similar amounts suggests that total 27.4 to 9.0% and from 30.5 to 12.1%, respectively. This result, impact, being the summation over individual articles, may be combined with our previous matching experiment (Fig. 3 D and primarily dependent on productivity (15). To test this hypoth- E), suggests that the difference in dropout rates is a key fac- esis, we conducted another matching experiment in which we tor in the observed total productivity and impact differences, selected a male author from the same discipline and with exactly

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Hauser, Matilda 6. E. C. The Stuart-Fox, Leboy, D. Holman, S. P. L. Koster, 5. B. J. Pincus, S. gap. Lincoln, gender E. the A. Mind 4. in quantified: disparities Inequality gender Global Shen, Sugimoto, R. H. C. Cronin, 3. B. Gingras, Y. Ni, C. Lariviere, applications. V. grant NIH in 2. gap gender The Hamilton, H. B. Ley, J. T. 1. u ou ncoe aer iie u td ocresthat careers to study our limited careers closed on focus Our the gap, gender the reduce to order in that argued often is It ei cec n Engineering 2007). and Science demic Medicine, of elsevier.com/research-intelligence/campaigns/gender-17). Collaboration International 2000s. and represented? equally are 1990s women US, the in prizes (2012). and Awards (2013). science. (2008). 1474 Nature oe nGoa cec:AvnigAaei aer Through Careers Academic Advancing Science: Global in Women eodBa n ares ufiln h oeta fWmni Aca- in Women of Potential the Fulfilling Barriers: and Bias Beyond 1–1 (2013). 211–213 504, Safr nvriyPes tnod A 2017). CA, Stanford, Press, University (Stanford LSBiol. PLoS TeNtoa cdme rs,Wsigo,DC, Washington, Press, Academies National (The 2096(2018). e2004956 16, o.Su.Sci. Stud. Soc. aueNews Nature and Science IAppendix, SI 307–320 42, 22–24 495, 1472– 322, 1 .S og esrso e ifrne nsinicproductivity. scientific in differences sex of science. Measures in differences Long, sex S. of J. origins The 11. Long, S. J. 10. 6 .Xe .A Shauman, A. K. Xie, differences Y. Sex 16. Gingras, Y. Gelinas, P. Villeneuve, C. Vignola-Gagne, E. Lariviere, V. 15. productiv- research in differences Gender Caprasecca, A. D’Angelo, A. C. Abramo, work- G. scientific the 14. and equity, “Gender,(in) Linkova, M. Whittington, about K. evidence Fox, New F. productivity: M. research in 13. differences Sex Shauman, A. K. Xie, Y. 12. ..akolde upr rmArFreOfieo cetfi Research Scientific of by Office part Force in Air FA9550-15-1-0364. from and supported DARPA-BAA-15-39. FA9550-15-1-0077 Grants Contract support were Agency acknowledges A.-L.B. Projects Research R.S. Scientific Research and of Advanced Office J.H. Defense Force Temple- Air by FA9550-19-1-0354. for part and University in Award 61066 supported Contract Northeastern were Foundation at A.-L.B. ton Zippel and A.J.G. Khorramzadeh, Kathrin Yasamin suggestions. and valuable particular discussions, Center in the helpful and at for Research, community Network research wonderful Complex the for thank also We alizations. ACKNOWLEDGMENTS. corresponding the from request. available upon are author code and related data Other relevant Appendix). and (SI academic websites source their entire from Availability. available an Code of and Data course the gender- over in effort sustain- gender-specific rooted career. that gaps the research of be by gender conduct but ability the not academics publications of contribute may which and component through impact processes key and specific a productivity that in find departments. consequences academic we important within Namely, structures suggest (13, organizational do researchers the organizational results individual for the our to in However, available variation 58). resources potential and test context can- and we observe yet and our not differences, large-scale gender Furthermore, the reflecting DBLP) into patterns analysis. insight and statistical deep our draw MAG, can biasing approach (WoS, bibliometric possibly publications sources language thereby English data and (57), our STEM overrepresent some of important, to tend in equally three are outputs; all academic and and possible the disciplines, publications of academic Scientific one only or publications. represent industry research their in through communicate career; to research findings pressure academic less productive with an conduct positions, admin- governmental of or or end teaching duties retain an often istrative publishing imply stopped always who authors not in does inequality career gender particular, study- in for controls and, academia. temporal careers of academic gen- importance accurate ing the our more limitations, suggests develop these a work to Despite is methodologies. work there identification future discourse, der for scientific need global the pressing to contributions increased sci- significantly their in countries these differences from scientists gender Since of ence. more perspective a Brazil, provide global also Korea, would future. comprehensive were inclusion Japan, whose China, the we Singapore, for and disambiguation, in gender Malaysia, gender author studies assess of to experimental reliability could unable of such gap the gender analysis to for the Due Our baseline dominate 56). that a factors (41, offer the minorities and careers and all women of ticipation .J .Cl,H ukra,Tepoutvt uze essec n hne npat- in changes and Persistence puzzle: productivity The Zuckerman, H. 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