Denelezh provides statistics about the gender gap in the content of Wikidata and Wikimedia projects.

You can learn more about Denelezh by reading the documentation and the current state of the project.

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Global Gender Gap

TotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
4,119,7273,602,413637,93717.7 %
2,964,09382.3 %3830.0 %

[arwiki] Gender Gap

TotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
135,092131,93521,25216.1 %
110,66883.9 %150.0 %

[arwiki] Gender Gap by year of birth

Years of birthTotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
1800 → 1809603603427.0 %total under the threshold of 2000 people56193.0 %00.0 %
1810 → 1819661661517.7 %total under the threshold of 2000 people61092.3 %00.0 %
1820 → 1829662661598.9 %total under the threshold of 2000 people60291.1 %00.0 %
1830 → 1839740740648.6 %total under the threshold of 2000 people67691.4 %00.0 %
1840 → 18498218219811.9 %total under the threshold of 2000 people72388.1 %00.0 %
1850 → 18591,0391,038797.6 %total under the threshold of 2000 people95992.4 %00.0 %
1860 → 18691,3331,33215411.6 %total under the threshold of 2000 people1,17888.4 %00.0 %
1870 → 18791,6221,6171529.4 %total under the threshold of 2000 people1,46590.6 %00.0 %
1880 → 18892,2212,2042029.2 %
2,00190.8 %10.0 %
1890 → 18992,3282,31728712.4 %
2,03087.6 %00.0 %
1900 → 19093,2873,26336811.3 %
2,89588.7 %00.0 %
1910 → 19193,7373,71143411.7 %
3,27788.3 %00.0 %
1920 → 19295,1145,07958611.5 %
4,49388.5 %00.0 %
1930 → 19396,1116,06373812.2 %
5,32487.8 %10.0 %
1940 → 19497,9177,8851,06513.5 %
6,81886.5 %20.0 %
1950 → 19598,8848,8231,33115.1 %
7,49084.9 %20.0 %
1960 → 196910,68810,6071,99918.8 %
8,60681.1 %20.0 %
1970 → 197914,15114,0243,02621.6 %
10,99678.4 %20.0 %
1980 → 198920,74120,6494,51321.9 %
16,13278.1 %40.0 %
1990 → 199910,0439,8832,32023.5 %
7,56376.5 %00.0 %
2000 → 200926626312647.9 %total under the threshold of 2000 people13752.1 %00.0 %
2010 → 20191818738.9 %total under the threshold of 2000 people1161.1 %00.0 %

[arwiki] Gender Gap by country of citizenship

Country ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
United States of America23,29423,2944,66820.0 %
18,61879.9 %80.0 %
Japan6,3806,28476912.2 %
5,51487.7 %10.0 %
United Kingdom6,0696,0691,05217.3 %
5,01382.6 %40.1 %
France5,7625,76284114.6 %
4,92185.4 %00.0 %
Germany4,8584,85769114.2 %
4,16685.8 %00.0 %
Egypt3,5143,4611,02329.6 %
2,43870.4 %00.0 %
Spain3,0643,06439312.8 %
2,67187.2 %00.0 %
Saudi Arabia2,4882,4881696.8 %
2,31993.2 %00.0 %
Italy2,4682,46828111.4 %
2,18788.6 %00.0 %
Brazil2,0242,0241808.9 %
1,84491.1 %00.0 %

[arwiki] Gender Gap by occupation

Occupation ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
research subject96,47996,15716,35417.0 %
79,78883.0 %150.0 %
athlete48,53048,3514,95810.3 %
43,39089.7 %30.0 %
creator42,91742,77610,83225.3 %
31,93174.6 %130.0 %
competitive player39,56239,3833,7209.4 %
35,66290.6 %10.0 %
association football player24,55424,3751630.7 %
24,21299.3 %00.0 %
artist23,94623,8408,26834.7 %
15,56265.3 %100.0 %
author17,62117,5843,51520.0 %
14,06680.0 %30.0 %
writer16,22016,1853,37520.9 %
12,80779.1 %30.0 %
actor16,06215,9636,55141.0 %
9,40358.9 %90.1 %
occupation12,94812,9461,96715.2 %
10,97484.8 %50.0 %
politician12,87912,8701,50711.7 %
11,36088.3 %30.0 %
researcher12,62612,6259837.8 %
11,64192.2 %10.0 %
erudite12,22912,2289567.8 %
11,27192.2 %10.0 %
scientist12,22212,2219567.8 %
11,26492.2 %10.0 %
basketball player8,2538,2537308.8 %
7,52391.2 %00.0 %
film actor7,6187,6183,15241.4 %
4,46158.6 %50.1 %
non-fiction writer6,7926,7921,34319.8 %
5,44680.2 %30.0 %
musician6,3166,3112,27336.0 %
4,03664.0 %20.0 %
worker5,8445,8444728.1 %
5,37091.9 %20.0 %
performer5,3945,3941,97536.6 %
3,41563.3 %40.1 %
educator5,1985,1984498.6 %
4,74991.4 %00.0 %
teacher5,1245,1244248.3 %
4,70091.7 %00.0 %
television actor5,1145,1141,93837.9 %
3,17162.0 %50.1 %
coach4,9204,9201132.3 %
4,80697.7 %10.0 %
academic4,9024,9023417.0 %
4,56093.0 %10.0 %
employee4,8774,8772394.9 %
4,63795.1 %10.0 %
faculty member4,7604,7603246.8 %
4,43693.2 %00.0 %
university teacher4,7374,7373216.8 %
4,41693.2 %00.0 %
administrator4,7354,7352314.9 %
4,50395.1 %10.0 %
Middle management4,7354,7352314.9 %
4,50395.1 %10.0 %
bureaucrat4,7334,7332314.9 %
4,50195.1 %10.0 %
civil servant4,7324,7322314.9 %
4,50095.1 %10.0 %
humanities scholar4,6374,6362856.1 %
4,35193.9 %00.0 %
poet4,5024,47193620.9 %
3,53579.1 %00.0 %
vocalist4,3784,3732,09447.9 %
2,27852.1 %10.0 %
singer4,3764,3712,09447.9 %
2,27652.1 %10.0 %
journalist3,8913,89196824.9 %
2,92175.1 %20.1 %
tennis player3,7913,7911,60742.4 %
2,18357.6 %10.0 %
manager3,7523,74946712.5 %
3,28287.5 %00.0 %
head coach3,5993,59940.1 %
3,59599.9 %00.0 %
association football manager3,5963,59640.1 %
3,59299.9 %00.0 %
jurist3,2263,2262567.9 %
2,97092.1 %00.0 %
screenwriter3,0853,08349316.0 %
2,59084.0 %00.0 %
composer3,0423,04067622.2 %
2,36477.8 %00.0 %
theatrical occupation3,0033,0031,11937.3 %
1,88262.7 %20.1 %
stage actor2,8602,8601,10538.6 %
1,75361.3 %20.1 %
official2,7202,720963.5 %
2,62396.4 %10.0 %
combatant2,7092,707632.3 %
2,64197.6 %30.1 %
warrior2,6932,691622.3 %
2,62697.6 %30.1 %
martial artist2,6672,667833.1 %
2,58496.9 %00.0 %
military personnel2,6212,619582.2 %
2,55897.7 %30.1 %
voice actor2,5512,55199439.0 %
1,55761.0 %00.0 %
director2,5202,51733813.4 %
2,17986.6 %00.0 %
lawyer2,4942,4942168.7 %
2,27891.3 %00.0 %
boxer2,4072,407271.1 %
2,38098.9 %00.0 %
model2,3592,3581,98384.1 %
37015.7 %50.2 %
cyclist2,3432,3432078.8 %
2,13591.1 %10.0 %
sport cyclist2,3432,3432078.8 %
2,13591.1 %10.0 %
film director2,2962,29330713.4 %
1,98686.6 %00.0 %
naturalist2,2812,2811717.5 %
2,11092.5 %00.0 %
businessperson2,2752,27531814.0 %
1,95686.0 %10.0 %
biologist2,2452,2451687.5 %
2,07792.5 %00.0 %
visual artist2,1432,14337117.3 %
1,77182.6 %10.0 %
diplomat2,1202,1201286.0 %
1,99294.0 %00.0 %