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
4,310,7063,742,916681,69718.2 %
3,060,70281.8 %5170.0 %

[arwiki] Gender Gap

TotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
141,175138,26622,96516.6 %
115,27583.4 %260.0 %

[arwiki] Gender Gap by year of birth

Years of birthTotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
1800 → 1809618618487.8 %total under the threshold of 2000 people57092.2 %00.0 %
1810 → 1819685685568.2 %total under the threshold of 2000 people62991.8 %00.0 %
1820 → 18296926917010.1 %total under the threshold of 2000 people62189.9 %00.0 %
1830 → 1839759759658.6 %total under the threshold of 2000 people69491.4 %00.0 %
1840 → 184986586511012.7 %total under the threshold of 2000 people75587.3 %00.0 %
1850 → 18591,0911,088918.4 %total under the threshold of 2000 people99791.6 %00.0 %
1860 → 18691,3891,38816211.7 %total under the threshold of 2000 people1,22688.3 %00.0 %
1870 → 18791,7141,7091629.5 %total under the threshold of 2000 people1,54790.5 %00.0 %
1880 → 18892,3412,32523410.1 %
2,09089.9 %10.0 %
1890 → 18992,4952,48432713.2 %
2,15786.8 %00.0 %
1900 → 19093,4793,45741111.9 %
3,04688.1 %00.0 %
1910 → 19193,9463,91947712.2 %
3,44287.8 %00.0 %
1920 → 19295,3905,35565512.2 %
4,70087.8 %00.0 %
1930 → 19396,4506,40080812.6 %
5,59187.4 %10.0 %
1940 → 19498,3538,3181,18414.2 %
7,13085.7 %40.0 %
1950 → 19599,3749,3211,49016.0 %
7,82984.0 %20.0 %
1960 → 196911,26811,1942,16419.3 %
9,02880.7 %20.0 %
1970 → 197914,90714,7843,19521.6 %
11,58578.4 %40.0 %
1980 → 198921,88521,7984,69621.5 %
17,09678.4 %60.0 %
1990 → 199910,76310,6422,45323.1 %
8,18576.9 %40.0 %
2000 → 200927827613448.6 %total under the threshold of 2000 people14251.4 %00.0 %
2010 → 20192323834.8 %total under the threshold of 2000 people1565.2 %00.0 %

[arwiki] Gender Gap by country of citizenship

Country ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
United States of America23,99723,9954,95220.6 %
19,02979.3 %140.1 %
United Kingdom7,0457,0441,14416.2 %
5,89583.7 %50.1 %
Japan6,7296,64279412.0 %
5,84788.0 %10.0 %
France6,0696,06989714.8 %
5,17285.2 %00.0 %
Germany5,1405,13975714.7 %
4,38285.3 %00.0 %
Spain3,3613,36141812.4 %
2,94387.6 %00.0 %
Egypt3,5903,5431,05629.8 %
2,48770.2 %00.0 %
Saudi Arabia2,5122,5111767.0 %
2,33493.0 %10.0 %
Italy2,6312,63130611.6 %
2,32588.4 %00.0 %
Brazil2,1672,1671949.0 %
1,97391.0 %00.0 %

[arwiki] Gender Gap by occupation

Occupation ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
research subject111,344111,00319,17917.3 %
91,79882.7 %260.0 %
athlete52,02751,8375,0839.8 %
46,75190.2 %30.0 %
competitive player43,01742,8273,7838.8 %
39,04391.2 %10.0 %
creator45,53545,39712,02026.5 %
33,35473.5 %230.1 %
association football player27,85927,6701920.7 %
27,47899.3 %00.0 %
artist24,90424,8028,71135.1 %
16,07264.8 %190.1 %
worker16,42116,4191,5179.2 %
14,89690.7 %60.0 %
author18,20018,1633,81921.0 %
14,33478.9 %100.1 %
writer16,73216,6973,65821.9 %
13,02978.0 %100.1 %
researcher14,24214,2401,3449.4 %
12,89490.5 %20.0 %
erudite13,85413,8521,3139.5 %
12,53790.5 %20.0 %
scientist13,84213,8401,3129.5 %
12,52690.5 %20.0 %
politician14,49314,4842,24715.5 %
12,23284.5 %50.0 %
actor16,37616,2826,74541.4 %
9,52158.5 %160.1 %
basketball player8,2898,2897308.8 %
7,55991.2 %00.0 %
manual worker5,8145,8132173.7 %
5,59396.2 %30.1 %
combatant5,7955,7942113.6 %
5,58096.3 %30.1 %
non-fiction writer6,9476,9461,47221.2 %
5,46878.7 %60.1 %
coach5,4385,4381182.2 %
5,31897.8 %20.0 %
employee5,4415,4403276.0 %
5,11294.0 %10.0 %
educator5,5555,55557310.3 %
4,98289.7 %00.0 %
administrator5,2525,2513085.9 %
4,94294.1 %10.0 %
Middle management5,2525,2513085.9 %
4,94294.1 %10.0 %
bureaucrat5,2495,2483085.9 %
4,93994.1 %10.0 %
civil servant5,2465,2453085.9 %
4,93694.1 %10.0 %
teacher5,4735,47354610.0 %
4,92790.0 %00.0 %
academic5,2635,2634428.4 %
4,82091.6 %10.0 %
faculty member4,9544,9543948.0 %
4,56092.0 %00.0 %
university teacher4,9324,9323917.9 %
4,54192.1 %00.0 %
film actor7,7117,7093,21241.7 %
4,48858.2 %90.1 %
humanities scholar4,6874,6863337.1 %
4,35392.9 %00.0 %
musician6,5776,5702,41136.7 %
4,15063.2 %90.1 %
businessperson4,8764,87576315.7 %
4,10984.3 %30.1 %
head coach4,0834,08350.1 %
4,07899.9 %00.0 %
association football manager4,0804,08050.1 %
4,07599.9 %00.0 %
poet4,6624,6341,01221.8 %
3,61878.1 %40.1 %
performer5,5435,5432,04436.9 %
3,49463.0 %50.1 %
journalist4,3874,3861,09825.0 %
3,28374.9 %50.1 %
manager3,7793,77652013.8 %
3,25686.2 %00.0 %
television actor5,1485,1471,95838.0 %
3,18261.8 %70.1 %
jurist3,3543,3542968.8 %
3,05891.2 %00.0 %
official3,0103,0101254.2 %
2,88495.8 %10.0 %
martial artist3,0023,0021434.8 %
2,85995.2 %00.0 %
warrior2,7772,776672.4 %
2,70697.5 %30.1 %
military personnel2,6972,696622.3 %
2,63197.6 %30.1 %
screenwriter3,1453,14351516.4 %
2,62783.6 %10.0 %
social scientist2,7612,7612669.6 %
2,49590.4 %00.0 %
entrepreneur3,0393,03854618.0 %
2,48981.9 %30.1 %
composer3,1493,14771622.8 %
2,42777.1 %40.1 %
boxer2,4102,410281.2 %
2,38298.8 %00.0 %
lawyer2,5812,5812489.6 %
2,33390.4 %00.0 %
vocalist4,5524,5452,21148.6 %
2,32851.2 %60.1 %
singer4,4794,4732,20849.4 %
2,25950.5 %60.1 %
director2,6162,61336614.0 %
2,24786.0 %00.0 %
cyclist2,4162,4162108.7 %
2,20591.3 %10.0 %
sport cyclist2,4162,4162108.7 %
2,20591.3 %10.0 %
tennis player3,7973,7961,60842.4 %
2,18757.6 %10.0 %
diplomat2,2632,2631546.8 %
2,10993.2 %00.0 %
film director2,3572,35433014.0 %
2,02486.0 %00.0 %
visual artist2,3832,38342818.0 %
1,95482.0 %10.0 %
theatrical occupation3,0293,0291,13337.4 %
1,89562.6 %10.0 %
professional2,2572,25435715.8 %
1,89584.1 %20.1 %
health professional2,2252,22234915.7 %
1,87184.2 %20.1 %
producer2,2352,23544519.9 %
1,78780.0 %30.1 %
stage actor2,8752,8751,11838.9 %
1,75661.1 %10.0 %
voice actor2,5932,5931,01539.1 %
1,57660.8 %20.1 %
model2,4642,4622,07284.2 %
38215.5 %80.3 %