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
4,255,7323,687,078658,38417.9 %
3,028,22982.1 %4650.0 %

[kowiki] Gender Gap

TotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
94,34583,19319,42823.4 %
63,73576.6 %300.0 %

[kowiki] Gender Gap by year of birth

Years of birthTotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
1800 → 18092662612710.3 %total under the threshold of 2000 people23489.7 %00.0 %
1810 → 18193163143812.1 %total under the threshold of 2000 people27687.9 %00.0 %
1820 → 1829331327329.8 %total under the threshold of 2000 people29590.2 %00.0 %
1830 → 1839403396348.6 %total under the threshold of 2000 people36291.4 %00.0 %
1840 → 1849466454419.0 %total under the threshold of 2000 people41391.0 %00.0 %
1850 → 1859670598427.0 %total under the threshold of 2000 people55693.0 %00.0 %
1860 → 1869845724709.7 %total under the threshold of 2000 people65490.3 %00.0 %
1870 → 18791,144900788.7 %total under the threshold of 2000 people82291.3 %00.0 %
1880 → 18891,5721,1791028.7 %total under the threshold of 2000 people1,07791.3 %00.0 %
1890 → 18991,9391,40116011.4 %total under the threshold of 2000 people1,24188.6 %00.0 %
1900 → 19092,2721,73821612.4 %total under the threshold of 2000 people1,52287.6 %00.0 %
1910 → 19192,2791,77425714.5 %total under the threshold of 2000 people1,51785.5 %00.0 %
1920 → 19292,9502,35039216.7 %
1,95783.3 %10.0 %
1930 → 19393,5162,98047415.9 %
2,50584.1 %10.0 %
1940 → 19495,3394,69485218.2 %
3,84081.8 %20.0 %
1950 → 19597,0046,0591,24620.6 %
4,81379.4 %00.0 %
1960 → 19698,6517,8282,00725.6 %
5,81474.3 %70.1 %
1970 → 197911,45710,6153,24930.6 %
7,36269.4 %40.0 %
1980 → 198916,51315,2835,13533.6 %
10,14066.3 %80.1 %
1990 → 19998,1967,6382,72735.7 %
4,90664.2 %50.1 %
2000 → 200935432420162.0 %total under the threshold of 2000 people12338.0 %00.0 %
2010 → 20191413861.5 %total under the threshold of 2000 people538.5 %00.0 %

[kowiki] Gender Gap by country of citizenship

Country ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
South Korea12,86011,1983,54131.6 %
7,65768.4 %00.0 %
United States of America13,86613,8603,91328.2 %
9,93271.7 %150.1 %
United Kingdom4,2534,2511,04824.7 %
3,20075.3 %30.1 %
France2,6392,63962923.8 %
2,00976.1 %10.0 %
Japan9,7969,7402,01520.7 %
7,72179.3 %40.0 %
Germany2,4312,42941217.0 %
2,01583.0 %20.1 %

[kowiki] Gender Gap by occupation

Occupation ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
model3,1943,1862,58381.1 %
59518.7 %80.3 %
singer8,2067,9864,27053.5 %
3,70946.4 %70.1 %
vocalist8,3158,0954,28252.9 %
3,80647.0 %70.1 %
actor17,98717,7648,81249.6 %
8,93950.3 %130.1 %
stage actor2,9082,9081,44149.6 %
1,46750.4 %00.0 %
theatrical occupation3,0253,0251,45648.1 %
1,56951.9 %00.0 %
film actor9,5929,5334,47246.9 %
5,05353.0 %80.1 %
television actor5,1295,1282,38146.4 %
2,74153.5 %60.1 %
voice actor3,4143,4131,58046.3 %
1,83353.7 %00.0 %
musician10,72810,4554,50243.1 %
5,94356.8 %100.1 %
artist28,98628,39412,01742.3 %
16,35657.6 %210.1 %
songwriter2,6452,6331,04439.7 %
1,58860.3 %10.0 %
lyricist2,7542,7351,08039.5 %
1,65360.4 %20.1 %
performer6,9746,8822,57337.4 %
4,30562.6 %40.1 %
creator39,01338,14613,59435.6 %
24,52964.3 %230.1 %
poet4,1664,1321,26930.7 %
2,86169.2 %20.0 %
composer4,1474,1121,19429.0 %
2,91670.9 %20.0 %
research subject62,96761,65215,94325.9 %
45,68274.1 %270.0 %
writer12,06011,7732,92224.8 %
8,84275.1 %90.1 %
journalist2,6972,48760424.3 %
1,87975.6 %40.2 %
author13,79613,4663,18423.6 %
10,27376.3 %90.1 %
non-fiction writer4,0773,86384922.0 %
3,00977.9 %50.1 %
producer2,3792,37249120.7 %
1,87979.2 %20.1 %
entrepreneur2,9192,90856319.4 %
2,34380.6 %20.1 %
businessperson3,5973,57865718.4 %
2,91981.6 %20.1 %
screenwriter2,9122,90653018.2 %
2,37581.7 %10.0 %
director2,5302,47039315.9 %
2,07784.1 %00.0 %
film director2,2862,22734815.6 %
1,87984.4 %00.0 %
manager3,8483,77954414.4 %
3,23585.6 %00.0 %
politician9,6448,7171,13013.0 %
7,58387.0 %40.0 %
worker11,61311,5491,21610.5 %
10,32889.4 %50.0 %
athlete19,96119,9062,08510.5 %
17,81789.5 %40.0 %
educator3,1963,1902146.7 %
2,97693.3 %00.0 %
teacher3,1583,1522066.5 %
2,94693.5 %00.0 %
researcher6,5616,5514146.3 %
6,13693.7 %10.0 %
erudite6,3736,3634006.3 %
5,96293.7 %10.0 %
scientist6,3696,3594006.3 %
5,95893.7 %10.0 %
employee2,6982,6811565.8 %
2,52394.1 %20.1 %
Middle management2,6072,5901465.6 %
2,44294.3 %20.1 %
civil servant2,5982,5811455.6 %
2,43494.3 %20.1 %
administrator2,6062,5891455.6 %
2,44294.3 %20.1 %
bureaucrat2,6052,5881455.6 %
2,44194.3 %20.1 %
faculty member2,7722,7721374.9 %
2,63595.1 %00.0 %
university teacher2,7662,7661364.9 %
2,63095.1 %00.0 %
academic2,9252,9231414.8 %
2,78195.1 %10.0 %
humanities scholar2,5312,5251184.7 %
2,40795.3 %00.0 %
competitive player15,66215,3096094.0 %
14,69996.0 %10.0 %
manual worker2,7492,727401.5 %
2,68598.5 %20.1 %
combatant2,7332,711361.3 %
2,67398.6 %20.1 %
warrior2,7272,705361.3 %
2,66798.6 %20.1 %
military personnel2,1202,100261.2 %
2,07298.7 %20.1 %
association football player11,15911,116650.6 %
11,05199.4 %00.0 %
baseball player2,0122,01220.1 %
2,01099.9 %00.0 %