Figures & data
Every figure in the study
All 23 figures — the five in the main text, the nine in the online appendix, and the nine the paper defers here — each with the caption it carries in the manuscript, the page it appears on, and the counts behind it. The artwork is the same vector file the paper prints.
Figure numbers, pages and captions on this page are generated from the manuscript's own cross-reference table, so they cannot drift from the paper. Where a figure has underlying counts, they are printed below it and offered as CSV.
Main text (5)
The five figures in the body of the Short Communication, with the page each appears on in the manuscript PDF.
Women as a Share of STEM Applicants, All Applicants and Top 10%
The Pipeline Gap and the Choice Gap among Top 10% Students
Pipeline and Choice Components of the STEM Gender Gap
Female Representation among High Achievers, STEM Applicants, and STEM Assignees, Top Decile
Academic Pipeline and STEM Choice Gaps across Levels of Wage Parity
Online appendix (9)
The nine figures of the online appendix (pp. 23–42 of the same PDF), reproduced here in full so they can be read without opening the paper.
The STEM Choice Gap at the Top 1%, 5%, and 10%
Gender Shares among STEM Applicants at Alternative Performance Thresholds
Gender Shares among Top Students at Alternative Performance Thresholds
The Pipeline Gap at Alternative Performance Thresholds
STEM First-Choice Probabilities by Sex at Alternative Performance Thresholds
The STEM First-Choice Gender Gap at Alternative Performance Thresholds
Any-STEM Application Probabilities by Sex at Alternative Performance Thresholds
The Any-STEM Gender Gap at Alternative Performance Thresholds
Top-10% Pipeline and Choice Gaps in Cohorts Closest to 2018
Deferred to these online materials (9)
Nine figures the Short Communication has no room for and points here for instead: the three by-score-bin figures promised in the Appendix B.7 footnote, and the six cross-field figures for business/law and health, which Appendix C reports as gaps by setting and threshold. Each carries the underlying counts.
Female shares by score bin
Underlying counts (60 rows)
| country | score_bin | n_male | n_female | prob_male_pct | prob_female_pct | gap_pp |
|---|---|---|---|---|---|---|
| Taiwan | 1-5 | 17336 | 18806 | NA | NA | NA |
| Taiwan | 6 | 3682 | 3801 | NA | NA | NA |
| Taiwan | 7 | 3328 | 3542 | NA | NA | NA |
| Taiwan | 8 | 3967 | 4294 | NA | NA | NA |
| Taiwan | 9 | 3632 | 2681 | NA | NA | NA |
| Taiwan | 10 | 4232 | 2766 | NA | NA | NA |
| Chile | 1-5 | 390308 | 487488 | NA | NA | NA |
| Chile | 6 | 79007 | 93466 | NA | NA | NA |
| Chile | 7 | 82367 | 93485 | NA | NA | NA |
| Chile | 8 | 84325 | 89161 | NA | NA | NA |
| Chile | 9 | 88202 | 86096 | NA | NA | NA |
| Chile | 10 | 97486 | 76534 | NA | NA | NA |
| Brazil | 1-5 | 516477 | 839128 | NA | NA | NA |
| Brazil | 6 | 116752 | 154418 | NA | NA | NA |
| Brazil | 7 | 124021 | 147029 | NA | NA | NA |
| Brazil | 8 | 131351 | 139685 | NA | NA | NA |
| Brazil | 9 | 136829 | 134310 | NA | NA | NA |
| Brazil | 10 | 137150 | 133899 | NA | NA | NA |
| China | 1-5 | 12636 | 13595 | NA | NA | NA |
| China | 6 | 2162 | 3139 | NA | NA | NA |
| China | 7 | 2123 | 3166 | NA | NA | NA |
| China | 8 | 2062 | 3107 | NA | NA | NA |
| China | 9 | 2014 | 3220 | NA | NA | NA |
| China | 10 | 2324 | 2879 | NA | NA | NA |
| Uganda | 1-5 | 11524 | 9915 | NA | NA | NA |
| Uganda | 6 | 2112 | 1485 | NA | NA | NA |
| Uganda | 7 | 1885 | 1319 | NA | NA | NA |
| Uganda | 8 | 1597 | 1083 | NA | NA | NA |
| Uganda | 9 | 1250 | 890 | NA | NA | NA |
| Uganda | 10 | 1956 | 1231 | NA | NA | NA |
| Finland | 1-5 | 65594 | 108684 | NA | NA | NA |
| Finland | 6 | 13806 | 20811 | NA | NA | NA |
| Finland | 7 | 14351 | 20546 | NA | NA | NA |
| Finland | 8 | 13560 | 21081 | NA | NA | NA |
| Finland | 9 | 14767 | 20119 | NA | NA | NA |
| Finland | 10 | 16726 | 17859 | NA | NA | NA |
| Spain | 1-5 | 204517 | 224561 | NA | NA | NA |
| Spain | 6 | 35830 | 49897 | NA | NA | NA |
| Spain | 7 | 34165 | 51632 | NA | NA | NA |
| Spain | 8 | 32799 | 53057 | NA | NA | NA |
| Spain | 9 | 31355 | 54366 | NA | NA | NA |
| Spain | 10 | 31908 | 53783 | NA | NA | NA |
| Australia | 1-5 | 17453 | 21456 | NA | NA | NA |
| Australia | 6 | 3314 | 4387 | NA | NA | NA |
| Australia | 7 | 3368 | 4379 | NA | NA | NA |
| Australia | 8 | 3321 | 4494 | NA | NA | NA |
| Australia | 9 | 3237 | 4491 | NA | NA | NA |
| Australia | 10 | 3590 | 4158 | NA | NA | NA |
| Greece | 1-5 | 161632 | 178384 | NA | NA | NA |
| Greece | 6 | 28395 | 39607 | NA | NA | NA |
| Greece | 7 | 28321 | 39682 | NA | NA | NA |
| Greece | 8 | 28215 | 39790 | NA | NA | NA |
| Greece | 9 | 27669 | 40333 | NA | NA | NA |
| Greece | 10 | 26484 | 41523 | NA | NA | NA |
| Sweden | 1-5 | 26483 | 27649 | NA | NA | NA |
| Sweden | 6 | 4349 | 6569 | NA | NA | NA |
| Sweden | 7 | 4103 | 6647 | NA | NA | NA |
| Sweden | 8 | 3874 | 6923 | NA | NA | NA |
| Sweden | 9 | 3622 | 7260 | NA | NA | NA |
| Sweden | 10 | 3673 | 7085 | NA | NA | NA |
STEM first-choice gap by score bin
Underlying counts (60 rows)
| country | score_bin | n_male | n_female | prob_male_pct | prob_female_pct | gap_pp |
|---|---|---|---|---|---|---|
| Taiwan | 1-5 | 17336 | 18806 | 41.21481310567605 | 15.319578857811337 | -25.895234247864714 |
| Taiwan | 6 | 3682 | 3801 | 51.41227593699077 | 19.60010523546435 | -31.812170701526416 |
| Taiwan | 7 | 3328 | 3542 | 54.176682692307686 | 23.517786561264824 | -30.658896131042862 |
| Taiwan | 8 | 3967 | 4294 | 58.10436097806907 | 26.292501164415466 | -31.8118598136536 |
| Taiwan | 9 | 3632 | 2681 | 69.7136563876652 | 37.33681462140992 | -32.376841766255275 |
| Taiwan | 10 | 4232 | 2766 | 80.08034026465029 | 55.35068691250904 | -24.72965335214125 |
| Chile | 1-5 | 69683 | 121852 | 33.83178106568317 | 8.28381971572071 | -25.547961349962456 |
| Chile | 6 | 44913 | 62601 | 36.80003562442945 | 10.450312295330745 | -26.3497233290987 |
| Chile | 7 | 56820 | 71645 | 38.87891587469201 | 12.231139646869984 | -26.64777622782203 |
| Chile | 8 | 67086 | 75426 | 41.26494350535134 | 14.712433378410628 | -26.55251012694071 |
| Chile | 9 | 78122 | 78612 | 42.76644223138169 | 17.370121609932326 | -25.396320621449362 |
| Chile | 10 | 92306 | 73118 | 45.40333239442723 | 20.795153040291037 | -24.608179354136194 |
| Brazil | 1-5 | 516477 | 839128 | 27.88371989459356 | 13.51796150289348 | -14.365758391700082 |
| Brazil | 6 | 116752 | 154418 | 31.201178566534193 | 15.008612985532773 | -16.192565581001418 |
| Brazil | 7 | 124021 | 147029 | 32.55980841954185 | 16.188643056811923 | -16.37116536272993 |
| Brazil | 8 | 131351 | 139685 | 34.96280957130132 | 17.45856749114078 | -17.50424208016054 |
| Brazil | 9 | 136829 | 134310 | 38.52253542743132 | 19.600178691087784 | -18.922356736343538 |
| Brazil | 10 | 137150 | 133899 | 39.95260663507109 | 19.800745337903944 | -20.151861297167148 |
| China | 1-5 | 12636 | 13595 | 50.72807850585629 | 15.027583670467084 | -35.70049483538921 |
| China | 6 | 2162 | 3139 | 61.14708603145236 | 28.41669321439949 | -32.73039281705287 |
| China | 7 | 2123 | 3166 | 62.034856335374464 | 24.76310802274163 | -37.27174831263284 |
| China | 8 | 2062 | 3107 | 63.14258001939864 | 23.624074670099773 | -39.51850534929887 |
| China | 9 | 2014 | 3220 | 60.228401191658385 | 20.217391304347824 | -40.011009887310564 |
| China | 10 | 2324 | 2879 | 55.42168674698795 | 18.930184091698507 | -36.491502655289445 |
| Uganda | 1-5 | 11524 | 9915 | 25.42519958347796 | 11.285930408472012 | -14.139269175005946 |
| Uganda | 6 | 2112 | 1485 | 37.97348484848485 | 19.5959595959596 | -18.377525252525253 |
| Uganda | 7 | 1885 | 1319 | 43.342175066313 | 21.152388172858224 | -22.189786893454773 |
| Uganda | 8 | 1597 | 1083 | 45.77332498434565 | 24.930747922437675 | -20.842577061907974 |
| Uganda | 9 | 1250 | 890 | 47.199999999999996 | 25.842696629213485 | -21.35730337078651 |
| Uganda | 10 | 1956 | 1231 | 46.012269938650306 | 34.52477660438667 | -11.487493334263633 |
| Finland | 1-5 | 65594 | 108684 | 25.679177973595145 | 5.833425343196791 | -19.845752630398355 |
| Finland | 6 | 13806 | 20811 | 27.850210053599884 | 7.947719955792609 | -19.902490097807274 |
| Finland | 7 | 14351 | 20546 | 30.555361995679743 | 10.147960673610436 | -20.407401322069305 |
| Finland | 8 | 13560 | 21081 | 32.868731563421825 | 12.281201081542621 | -20.587530481879206 |
| Finland | 9 | 14767 | 20119 | 39.669533419110174 | 15.164769620756498 | -24.504763798353675 |
| Finland | 10 | 16726 | 17859 | 48.439555183546574 | 22.263284618399688 | -26.176270565146886 |
| Spain | 1-5 | 204517 | 224561 | 38.2256731714234 | 13.586508788257978 | -24.639164383165422 |
| Spain | 6 | 35830 | 49897 | 42.71839240859615 | 15.796540874200854 | -26.921851534395298 |
| Spain | 7 | 34165 | 51632 | 44.41972779159959 | 17.064998450573288 | -27.354729341026303 |
| Spain | 8 | 32799 | 53057 | 47.04411719869508 | 18.798650507944288 | -28.245466690750796 |
| Spain | 9 | 31355 | 54366 | 50.916919151650454 | 21.34422249199868 | -29.572696659651776 |
| Spain | 10 | 31908 | 53783 | 53.544565626175256 | 23.821653682390345 | -29.72291194378491 |
| Australia | 1-5 | 17453 | 21456 | 21.824328195725663 | 6.566927665920955 | -15.257400529804709 |
| Australia | 6 | 3314 | 4387 | 36.90404345202173 | 11.944381126054251 | -24.95966232596748 |
| Australia | 7 | 3368 | 4379 | 39.934679334916865 | 14.638045215802695 | -25.29663411911417 |
| Australia | 8 | 3321 | 4494 | 44.233664558867815 | 18.82510013351135 | -25.408564425356467 |
| Australia | 9 | 3237 | 4491 | 45.35063330244053 | 23.602761077710976 | -21.74787222472955 |
| Australia | 10 | 3590 | 4158 | 41.949860724233986 | 25.82972582972583 | -16.120134894508155 |
| Greece | 1-5 | 161632 | 178384 | 42.845476143337955 | 16.49419230424253 | -26.351283839095423 |
| Greece | 6 | 28395 | 39607 | 35.601338263778835 | 15.179135001388644 | -20.42220326239019 |
| Greece | 7 | 28321 | 39682 | 38.021256311570916 | 16.39786301093695 | -21.623393300633968 |
| Greece | 8 | 28215 | 39790 | 41.34325713273081 | 17.162603669263635 | -24.180653463467177 |
| Greece | 9 | 27669 | 40333 | 44.363728360258776 | 17.660476532863907 | -26.70325182739487 |
| Greece | 10 | 26484 | 41523 | 47.84398127171122 | 25.313681574067388 | -22.530299697643834 |
| Sweden | 1-5 | 26483 | 27649 | 29.78514518747876 | 6.459546457376398 | -23.325598730102364 |
| Sweden | 6 | 4349 | 6569 | 33.22602897217751 | 9.362155579235806 | -23.863873392941706 |
| Sweden | 7 | 4103 | 6647 | 35.9736777967341 | 11.012486836166692 | -24.961190960567407 |
| Sweden | 8 | 3874 | 6923 | 36.91275167785235 | 12.046800520005778 | -24.86595115784657 |
| Sweden | 9 | 3622 | 7260 | 39.12203202650469 | 13.484848484848486 | -25.637183541656206 |
| Sweden | 10 | 3673 | 7085 | 44.07841001905799 | 17.79816513761468 | -26.28024488144331 |
Any-STEM gap by score bin
Underlying counts (60 rows)
| country | score_bin | n_male | n_female | prob_male_pct | prob_female_pct | gap_pp |
|---|---|---|---|---|---|---|
| Taiwan | 1-5 | 17336 | 18806 | 87.64997692662668 | 74.0508348399447 | -13.59914208668198 |
| Taiwan | 6 | 3682 | 3801 | 88.67463335143944 | 70.00789265982637 | -18.66674069161307 |
| Taiwan | 7 | 3328 | 3542 | 87.6201923076923 | 70.52512704686617 | -17.095065260826132 |
| Taiwan | 8 | 3967 | 4294 | 89.36223846735568 | 72.98556124825338 | -16.376677219102305 |
| Taiwan | 9 | 3632 | 2681 | 93.14427312775331 | 79.89556135770235 | -13.24871177005096 |
| Taiwan | 10 | 4232 | 2766 | 94.91965973534971 | 86.22559652928416 | -8.69406320606555 |
| Chile | 1-5 | 69683 | 121852 | 49.333409870413156 | 20.155598595016905 | -29.17781127539625 |
| Chile | 6 | 44913 | 62601 | 52.99579186427093 | 23.456494305202792 | -29.539297559068135 |
| Chile | 7 | 56820 | 71645 | 54.58465329109469 | 26.366110684625582 | -28.218542606469107 |
| Chile | 8 | 67086 | 75426 | 56.7003547685061 | 29.395699095802506 | -27.304655672703596 |
| Chile | 9 | 78122 | 78612 | 58.11295153733903 | 31.86281992571109 | -26.25013161162794 |
| Chile | 10 | 92306 | 73118 | 59.15541784932724 | 34.86966273694576 | -24.28575511238148 |
| Brazil | 1-5 | 516477 | 839128 | 40.37759667903895 | 22.71739234062026 | -17.66020433841869 |
| Brazil | 6 | 116752 | 154418 | 42.919179114704676 | 23.982955354945666 | -18.93622375975901 |
| Brazil | 7 | 124021 | 147029 | 44.129623208972674 | 24.725734378932046 | -19.40388883004063 |
| Brazil | 8 | 131351 | 139685 | 45.95549329658701 | 25.81809070408419 | -20.137402592502816 |
| Brazil | 9 | 136829 | 134310 | 48.93480183294477 | 27.376219194401013 | -21.558582638543758 |
| Brazil | 10 | 137150 | 133899 | 49.23733138899016 | 26.527457262563576 | -22.70987412642658 |
| China | 1-5 | 12636 | 13595 | 75.87052864830642 | 59.536594336152994 | -16.333934312153424 |
| China | 6 | 2162 | 3139 | 86.91026827012026 | 68.77986619942656 | -18.13040207069369 |
| China | 7 | 2123 | 3166 | 89.7786151672162 | 68.03537586860392 | -21.74323929861228 |
| China | 8 | 2062 | 3107 | 84.23860329776916 | 58.995815899581594 | -25.242787398187566 |
| China | 9 | 2014 | 3220 | 82.17477656405164 | 56.30434782608695 | -25.870428737964687 |
| China | 10 | 2324 | 2879 | 82.01376936316696 | 55.609586662035426 | -26.404182701131532 |
| Uganda | 1-5 | 11524 | 9915 | 65.64560916348489 | 48.66364094805849 | -16.9819682154264 |
| Uganda | 6 | 2112 | 1485 | 78.64583333333334 | 57.03703703703704 | -21.608796296296305 |
| Uganda | 7 | 1885 | 1319 | 82.28116710875332 | 58.15011372251706 | -24.13105338623626 |
| Uganda | 8 | 1597 | 1083 | 85.78584846587351 | 63.342566943674974 | -22.44328152219854 |
| Uganda | 9 | 1250 | 890 | 88.64 | 70.0 | -18.64 |
| Uganda | 10 | 1956 | 1231 | 88.95705521472392 | 79.52883834281073 | -9.428216871913193 |
| Finland | 1-5 | 65594 | 108684 | 37.863219196877765 | 11.354937249273123 | -26.508281947604644 |
| Finland | 6 | 13806 | 20811 | 39.70013037809648 | 15.338042381432896 | -24.362087996663586 |
| Finland | 7 | 14351 | 20546 | 42.72872970524702 | 18.903922904701645 | -23.824806800545375 |
| Finland | 8 | 13560 | 21081 | 45.77433628318584 | 23.58521891750866 | -22.18911736567718 |
| Finland | 9 | 14767 | 20119 | 53.97846549739283 | 29.74302897758338 | -24.235436519809454 |
| Finland | 10 | 16726 | 17859 | 64.27119454741121 | 42.337196931519124 | -21.93399761589209 |
| Spain | 1-5 | 204517 | 224561 | 37.91420762088237 | 14.032712715030659 | -23.881494905851714 |
| Spain | 6 | 35830 | 49897 | 42.95004186435947 | 16.62224181814538 | -26.32780004621409 |
| Spain | 7 | 34165 | 51632 | 44.70657105224645 | 17.901688875116207 | -26.804882177130246 |
| Spain | 8 | 32799 | 53057 | 47.28802707399616 | 19.80511525340671 | -27.48291182058945 |
| Spain | 9 | 31355 | 54366 | 50.920108435656196 | 22.309899569583933 | -28.610208866072263 |
| Spain | 10 | 31908 | 53783 | 53.73260624294848 | 24.769908707212316 | -28.96269753573616 |
| Australia | 1-5 | 17453 | 21456 | 42.78347562023721 | 21.075689783743474 | -21.707785836493738 |
| Australia | 6 | 3314 | 4387 | 59.95775497887749 | 31.958057898335994 | -27.999697080541495 |
| Australia | 7 | 3368 | 4379 | 62.47030878859857 | 35.5560630280886 | -26.91424576050997 |
| Australia | 8 | 3321 | 4494 | 63.956639566395665 | 39.56386292834891 | -24.392776638046755 |
| Australia | 9 | 3237 | 4491 | 67.80970033982082 | 47.45045646849254 | -20.35924387132828 |
| Australia | 10 | 3590 | 4158 | 74.59610027855153 | 57.11880711880711 | -17.47729315974442 |
| Greece | 1-5 | 161632 | 178384 | 91.02529202138192 | 82.27083146470535 | -8.754460556676563 |
| Greece | 6 | 28395 | 39607 | 84.51840112695898 | 63.710960183805895 | -20.807440943153082 |
| Greece | 7 | 28321 | 39682 | 82.69128914939444 | 58.85288039917342 | -23.838408750221014 |
| Greece | 8 | 28215 | 39790 | 82.40652135388977 | 56.70017592359889 | -25.70634543029088 |
| Greece | 9 | 27669 | 40333 | 83.08576385124145 | 56.52939280489922 | -26.556371046342235 |
| Greece | 10 | 26484 | 41523 | 85.05135175955294 | 60.07273077571467 | -24.978620983838276 |
| Sweden | 1-5 | 26483 | 27649 | 43.38632330174074 | 14.362183080762414 | -29.024140220978325 |
| Sweden | 6 | 4349 | 6569 | 44.653943435272474 | 17.32379357588674 | -27.330149859385735 |
| Sweden | 7 | 4103 | 6647 | 45.69826955885937 | 18.474499774334284 | -27.22376978452509 |
| Sweden | 8 | 3874 | 6923 | 46.61848218895199 | 19.38465982955366 | -27.233822359398328 |
| Sweden | 9 | 3622 | 7260 | 47.183876311430154 | 21.06060606060606 | -26.123270250824095 |
| Sweden | 10 | 3673 | 7085 | 53.090117070514566 | 25.772759350741005 | -27.31735771977356 |
Business/law first-choice probabilities by sex
The business/law first-choice gap
Health first-choice probabilities by sex
The health first-choice gap
Any-business/law probabilities and gap
Underlying counts (28 rows)
| country | threshold | n_male | n_female | prob_male_pct | prob_female_pct | gap_pp |
|---|---|---|---|---|---|---|
| Taiwan | Top 5% | 2148.0 | 1306.0 | 35.754 | 54.977 | 19.223 |
| Chile | Top 5% | 50745.0 | 36010.0 | 27.008 | 23.58 | -3.428 |
| Brazil | Top 5% | 68293.0 | 67283.0 | 18.207 | 16.74 | -1.467 |
| China | Top 5% | 1242.0 | 1379.0 | 51.852 | 83.684 | 31.832 |
| Uganda | Top 5% | 1001.0 | 605.0 | 15.485 | 22.149 | 6.664 |
| Finland | Top 5% | 8537.0 | 8437.0 | 18.73 | 13.216 | -5.515 |
| Spain | Top 5% | 19479.0 | 31949.0 | 10.832 | 15.481 | 4.649 |
| Australia | Top 5% | 1879.0 | 2073.0 | 54.497 | 38.736 | -15.761 |
| Greece | Top 5% | 12382.0 | 21623.0 | 62.227 | 54.715 | -7.513 |
| Sweden | Top 5% | 1854.0 | 3497.0 | 31.23 | 31.827 | 0.598 |
| Taiwan | Top 10% | 4232.0 | 2766.0 | 43.195 | 63.847 | 20.652 |
| Chile | Top 10% | 97486.0 | 76534.0 | 27.685 | 23.707 | -3.978 |
| Brazil | Top 10% | 137150.0 | 133899.0 | 19.958 | 18.34 | -1.618 |
| China | Top 10% | 2324.0 | 2879.0 | 57.788 | 86.106 | 28.318 |
| Uganda | Top 10% | 1956.0 | 1231.0 | 18.047 | 30.138 | 12.091 |
| Finland | Top 10% | 16726.0 | 17859.0 | 19.347 | 14.223 | -5.125 |
| Spain | Top 10% | 31908.0 | 53783.0 | 11.878 | 16.202 | 4.324 |
| Australia | Top 10% | 3590.0 | 4158.0 | 55.404 | 37.278 | -18.126 |
| Sweden | Top 10% | 3673.0 | 7085.0 | 31.337 | 35.06 | 3.723 |
| Taiwan | Top 20% | 7864.0 | 5447.0 | 48.97 | 70.901 | 21.931 |
| Chile | Top 20% | 185688.0 | 162630.0 | 27.54 | 23.209 | -4.331 |
| Brazil | Top 20% | 273979.0 | 268209.0 | 21.31 | 20.114 | -1.197 |
| China | Top 20% | 4338.0 | 6099.0 | 64.408 | 85.801 | 21.393 |
| Uganda | Top 20% | 3206.0 | 2121.0 | 21.21 | 37.388 | 16.178 |
| Finland | Top 20% | 31493.0 | 37978.0 | 22.961 | 16.391 | -6.57 |
| Spain | Top 20% | 63263.0 | 108149.0 | 14.185 | 17.813 | 3.628 |
| Australia | Top 20% | 6827.0 | 8649.0 | 53.479 | 35.946 | -17.532 |
| Sweden | Top 20% | 7295.0 | 14345.0 | 33.722 | 37.4 | 3.678 |
Any-health probabilities and gap
Underlying counts (30 rows)
| country | threshold | n_male | n_female | prob_male_pct | prob_female_pct | gap_pp |
|---|---|---|---|---|---|---|
| Taiwan | Top 5% | 2148.0 | 1306.0 | 60.521 | 57.963 | -2.558 |
| Chile | Top 5% | 50745.0 | 36010.0 | 29.272 | 48.431 | 19.159 |
| Brazil | Top 5% | 68293.0 | 67283.0 | 34.56 | 55.191 | 20.631 |
| China | Top 5% | 1242.0 | 1379.0 | 19.807 | 23.568 | 3.761 |
| Uganda | Top 5% | 1001.0 | 605.0 | 49.65 | 59.504 | 9.854 |
| Finland | Top 5% | 8537.0 | 8437.0 | 28.371 | 46.592 | 18.222 |
| Spain | Top 5% | 19479.0 | 31949.0 | 22.912 | 36.214 | 13.302 |
| Australia | Top 5% | 1879.0 | 2073.0 | 37.36 | 42.016 | 4.656 |
| Greece | Top 5% | 12382.0 | 21623.0 | 35.64 | 38.325 | 2.684 |
| Sweden | Top 5% | 1854.0 | 3497.0 | 26.052 | 36.374 | 10.322 |
| Taiwan | Top 10% | 4232.0 | 2766.0 | 49.22 | 49.385 | 0.165 |
| Chile | Top 10% | 97486.0 | 76534.0 | 25.705 | 45.546 | 19.841 |
| Brazil | Top 10% | 137150.0 | 133899.0 | 27.223 | 47.875 | 20.651 |
| China | Top 10% | 2324.0 | 2879.0 | 20.74 | 26.051 | 5.311 |
| Uganda | Top 10% | 1956.0 | 1231.0 | 48.364 | 52.478 | 4.114 |
| Finland | Top 10% | 16726.0 | 17859.0 | 26.551 | 44.818 | 18.266 |
| Spain | Top 10% | 31908.0 | 53783.0 | 22.853 | 36.536 | 13.683 |
| Australia | Top 10% | 3590.0 | 4158.0 | 31.532 | 40.212 | 8.68 |
| Greece | Top 10% | 26484.0 | 41523.0 | 32.204 | 39.978 | 7.773 |
| Sweden | Top 10% | 3673.0 | 7085.0 | 23.278 | 34.933 | 11.655 |
| Taiwan | Top 20% | 7864.0 | 5447.0 | 40.463 | 40.352 | -0.11 |
| Chile | Top 20% | 185688.0 | 162630.0 | 23.242 | 43.973 | 20.731 |
| Brazil | Top 20% | 273979.0 | 268209.0 | 21.37 | 40.39 | 19.02 |
| China | Top 20% | 4338.0 | 6099.0 | 24.666 | 29.447 | 4.782 |
| Uganda | Top 20% | 3206.0 | 2121.0 | 46.257 | 48.185 | 1.928 |
| Finland | Top 20% | 31493.0 | 37978.0 | 23.97 | 40.913 | 16.943 |
| Spain | Top 20% | 63263.0 | 108149.0 | 19.833 | 33.687 | 13.854 |
| Australia | Top 20% | 6827.0 | 8649.0 | 27.948 | 39.299 | 11.351 |
| Greece | Top 20% | 54153.0 | 81856.0 | 25.696 | 38.742 | 13.047 |
| Sweden | Top 20% | 7295.0 | 14345.0 | 20.891 | 35.699 | 14.808 |
Underlying data
Two files carry every number on this site. Both are derived from the same harmonized counts that produce the paper's figures.
Full results grid
321 rows — one per country × field × stage × threshold, with counts, rates and gaps.
Rates and counts by score bin
180 rows — male and female rates and numerators by decile bin, for the pipeline, first-choice and any-choice measures.
Table A.I — institutional characteristics
Setting, university-system and admission-system characteristics for the ten settings.
Table A.II — sample provenance
Administrative source, cohorts, sample size and top-decile composition per setting.