Figures & data
Every exhibit in the study
All 23 exhibits — the four in the main text, the fourteen in the online appendix, and the five 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.
Exhibit numbers, pages and captions on this page are generated from the manuscript's own cross-reference table, so they cannot drift from the published paper. Where a figure has underlying counts, they are printed below it and offered as CSV.
Main text (4)
The four exhibits 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 component against choice component
Female share at each stage of the STEM funnel, top decile
Online appendix (14)
The fourteen figures of the online appendix (pp. 24–48 of the same PDF), reproduced here in full so they can be read without opening the paper.
The choice gap at the top 1%, 5% and 10%
Gender shares among STEM applicants at alternative thresholds
Gender shares among top students at alternative thresholds
The pipeline gap at alternative thresholds
STEM first-choice probabilities by sex at alternative thresholds
The STEM first-choice gap at alternative thresholds
Any-STEM probabilities by sex at alternative thresholds
The any-STEM gap at alternative thresholds
Business/law first-choice probabilities by sex
The business/law first-choice gap
Health first-choice probabilities by sex
The health first-choice gap
Pipeline and choice gaps in cohorts closest to 2018
Pipeline and choice gaps against the wage parity index
Deferred to these online materials (5)
Five figures the Short Communication has no room for and points here for instead: the three by-score-bin figures promised in the Appendix B.8 footnote, and the two any-choice cross-field figures promised in the Appendix C footnote. 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 |
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.