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Global Gender Gap

TotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
3,787,3713,617,627635,73117.573 %
2,980,62682.392 %1,2700.035 %

[Portuguese Wikipedia] Gender Gap

TotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
227,982225,81240,98418.150 %
184,64281.768 %1860.082 %

[Portuguese Wikipedia] Gender Gap by year of birth

Years of birthTotalTotal with genderFemales% FemalesGapMales% MalesOthers% Others
1800 → 18091,5861,5861328.323 %total under the threshold of 10000 people1,45391.614 %10.063 %
1810 → 18191,7161,7161398.100 %total under the threshold of 10000 people1,57791.900 %00.000 %
1820 → 18291,7771,7761659.291 %total under the threshold of 10000 people1,61190.709 %00.000 %
1830 → 18392,0802,0781748.373 %total under the threshold of 10000 people1,90391.578 %10.048 %
1840 → 18492,4382,4352309.446 %total under the threshold of 10000 people2,20590.554 %00.000 %
1850 → 18592,7962,7922408.596 %total under the threshold of 10000 people2,55291.404 %00.000 %
1860 → 18693,3623,36039411.726 %total under the threshold of 10000 people2,96688.274 %00.000 %
1870 → 18794,0534,04345911.353 %total under the threshold of 10000 people3,58488.647 %00.000 %
1880 → 18895,4815,4715369.797 %total under the threshold of 10000 people4,93290.148 %30.055 %
1890 → 18996,1176,09774612.236 %total under the threshold of 10000 people5,35187.764 %00.000 %
1900 → 19097,5117,47990412.087 %total under the threshold of 10000 people6,57487.899 %10.013 %
1910 → 19198,9058,8491,06712.058 %total under the threshold of 10000 people7,77987.908 %30.034 %
1920 → 192910,91610,8401,47413.598 %
9,36386.375 %30.028 %
1930 → 193912,00811,9331,62513.618 %
10,30386.340 %50.042 %
1940 → 194916,01315,9332,50715.735 %
13,41184.171 %150.094 %
1950 → 195916,51416,3993,12619.062 %
13,26180.865 %120.073 %
1960 → 196918,08717,9464,10822.891 %
13,82477.031 %140.078 %
1970 → 197921,39721,2745,48625.787 %
15,76474.100 %240.113 %
1980 → 198925,40525,2907,20528.490 %
18,04971.368 %360.142 %
1990 → 199912,32412,2113,59229.416 %
8,59670.396 %230.188 %
2000 → 200955253725246.927 %total under the threshold of 10000 people28352.700 %20.372 %
2010 → 201929291344.828 %total under the threshold of 10000 people1655.172 %00.000 %

[Portuguese Wikipedia] Gender Gap by country of citizenship

Country ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
United States of America37,56737,5658,66323.061 %
28,84176.776 %610.162 %
United Kingdom10,62410,6232,18220.540 %
8,42879.337 %130.122 %
Brazil41,31040,2486,90417.154 %
33,31882.782 %260.065 %
France10,71110,7111,60915.022 %
9,09784.931 %50.047 %
Portugal11,07811,0481,57814.283 %
9,47085.717 %00.000 %
Germany11,23211,2321,59414.192 %
9,63385.764 %50.045 %

[Portuguese Wikipedia] Gender Gap by occupation

Occupation ▴ Total ▾ Total with gender ▾ Females ▾ % Fem. ▾ GapMales ▾ % Mal. ▾ Others ▾ % Oth. ▾
film actor13,50313,5006,55548.556 %
6,91051.185 %350.259 %
actor24,38924,33110,96445.062 %
13,30954.700 %580.238 %
singer12,03911,9985,35644.641 %
6,60855.076 %340.283 %
vocalist12,71612,6675,50543.459 %
7,12856.272 %340.268 %
television actor10,43410,4123,83936.871 %
6,55762.975 %160.154 %
artist56,28256,04217,02730.383 %
38,92069.448 %950.170 %
musician21,99821,8726,22628.466 %
15,60171.329 %450.206 %
creator103,605103,19723,93323.192 %
79,13276.681 %1320.128 %
media professional14,98114,9323,02520.259 %
11,88779.608 %200.134 %
writer34,09533,9866,73519.817 %
27,21180.065 %400.118 %
composer11,17611,1362,09218.786 %
9,02481.034 %200.180 %
author43,99343,8038,18018.675 %
35,56981.202 %540.123 %
agent212,566211,64538,15418.027 %
173,31081.887 %1810.086 %
athlete65,04564,93110,00215.404 %
54,91484.573 %150.023 %
sports figure65,82465,70710,03515.272 %
55,65684.703 %160.024 %
leader20,75920,7053,04614.711 %
17,64485.216 %150.072 %
professional75,25374,87210,08913.475 %
64,71086.428 %730.097 %
businessperson11,28811,2631,50013.318 %
9,74686.531 %170.151 %
visual artist11,23511,2011,43512.811 %
9,74887.028 %180.161 %
worker102,400101,94113,03212.784 %
88,80887.117 %1010.099 %
politician34,78234,5154,30012.458 %
30,18887.463 %270.078 %
competitive player43,85443,7545,36112.253 %
38,38687.731 %70.016 %
position40,56240,5214,96112.243 %
35,53787.700 %230.057 %
erudite34,10934,0683,58810.532 %
30,46089.409 %200.059 %
manager14,49314,4611,4329.902 %
13,02090.035 %90.062 %
executive14,84514,8111,4609.858 %
13,34190.075 %100.068 %
leader of organisation14,82914,7961,4569.840 %
13,33090.092 %100.068 %
educator13,56913,5621,3329.822 %
12,22190.112 %90.066 %
teacher13,32613,3191,2749.565 %
12,03790.375 %80.060 %
researcher32,89632,8593,1229.501 %
29,71990.444 %180.055 %
humanities scholar11,27911,2601,0379.210 %
10,22090.764 %30.027 %
scientist24,28624,2692,1578.888 %
22,09991.059 %130.054 %
academic11,61611,6108387.218 %
10,76792.739 %50.043 %
faculty member10,90410,9037526.897 %
10,14793.066 %40.037 %
university teacher10,88510,8847476.863 %
10,13393.100 %40.037 %
combatant13,67813,6426454.728 %
12,98595.184 %120.088 %
association football player28,87628,7911,0133.518 %
27,77796.478 %10.003 %
employee15,20415,1575273.477 %
14,61696.431 %140.092 %
military personnel10,24510,2161831.791 %
10,02198.091 %120.117 %
warrior10,70010,6711891.771 %
10,47098.116 %120.112 %