Women through the glass ceiling: gender asymmetries in Wikipedia

Wagner, Claudia; Graells-Garrido, Eduardo; Garcia, David; Menczer, Filippo

doi:10.1140/epjds/s13688-016-0066-4

EPJ Data Science

Table 2 Notability via number of language editions

From: Women through the glass ceiling: gender asymmetries in Wikipedia

	0-1899			1900-present			0-present
	β	Std. err.	p	β	Std. err.	p	β	Std. err.	p
C(class)[T. Ambassador]	0.083	0.148	0.574	−0.537	0.076	^∗∗∗	−0.412	0.068	^∗∗∗
C(class)[T. Architect]	0.355	0.041	^∗∗∗	0.574	0.047	^∗∗∗	0.421	0.031	^∗∗∗
C(class)[T. Artist]	0.853	0.012	^∗∗∗	0.420	0.005	^∗∗∗	0.508	0.005	^∗∗∗
C(class)[T. Astronaut]	–	–	–	1.403	0.038	^∗∗∗	1.428	0.038	^∗∗∗
C(class)[T. Athlete]	−0.344	0.011	^∗∗∗	0.042	0.004	^∗∗∗	0.084	0.003	^∗∗∗
C(class)[T. BeautyQueen]	–	–	–	−0.290	0.035	^∗∗∗	−0.206	0.035	^∗∗∗
C(class)[T. BusinessPerson]	−1.066	0.254	^∗∗∗	−0.929	0.173	^∗∗∗	−0.983	0.143	^∗∗∗
C(class)[T. Chef]	0.272	0.571	0.633	−0.268	0.070	^∗∗∗	−0.217	0.070	0.002
C(class)[T. Cleric]	0.545	0.022	^∗∗∗	0.417	0.020	^∗∗∗	0.477	0.015	^∗∗∗
C(class)[T. Coach]	−0.932	0.042	^∗∗∗	−0.938	0.023	^∗∗∗	−0.941	0.020	^∗∗∗
C(class)[T. Criminal]	0.468	0.073	^∗∗∗	0.197	0.030	^∗∗∗	0.244	0.028	^∗∗∗
C(class)[T. Economist]	1.504	0.099	^∗∗∗	0.941	0.045	^∗∗∗	1.043	0.041	^∗∗∗
C(class)[T. Engineer]	0.411	0.054	^∗∗∗	0.002	0.079	0.979	0.243	0.044	^∗∗∗
C(class)[T. FictionalCharacter]	–	–	–	−1.021	0.418	0.015	−0.969	0.419	0.021
C(class)[T. Historian]	−0.579	0.172	0.001	−0.756	0.117	^∗∗∗	−0.730	0.097	^∗∗∗
C(class)[T. HorseTrainer]	−0.983	0.563	0.081	−0.999	0.107	^∗∗∗	−0.987	0.106	^∗∗∗
C(class)[T. Journalist]	−0.899	0.176	^∗∗∗	−1.032	0.078	^∗∗∗	−1.005	0.072	^∗∗∗
C(class)[T. Judge]	−0.580	0.055	^∗∗∗	−0.700	0.040	^∗∗∗	−0.677	0.033	^∗∗∗
C(class)[T. MilitaryPerson]	−0.014	0.011	0.195	−0.287	0.013	^∗∗∗	−0.166	0.008	^∗∗∗
C(class)[T. Model]	−0.146	0.704	0.836	0.249	0.030	^∗∗∗	0.332	0.030	^∗∗∗
C(class)[T. Monarch]	1.024	0.064	^∗∗∗	1.313	0.119	^∗∗∗	1.227	0.056	^∗∗∗
C(class)[T. Noble]	0.096	0.029	0.001	0.009	0.135	0.944	0.175	0.028	^∗∗∗
C(class)[T. OfficeHolder]	0.340	0.011	^∗∗∗	0.300	0.007	^∗∗∗	0.308	0.006	^∗∗∗
C(class)[T. Philosopher]	1.992	0.050	^∗∗∗	1.180	0.040	^∗∗∗	1.547	0.031	^∗∗∗
C(class)[T. PlayboyPlaymate]	–	–	–	−0.068	0.078	0.381	−0.014	0.078	0.854
C(class)[T. Politician]	0.067	0.011	^∗∗∗	0.098	0.009	^∗∗∗	0.068	0.007	^∗∗∗
C(class)[T. Presenter]	0.121	0.458	0.792	−0.758	0.068	^∗∗∗	−0.701	0.068	^∗∗∗
C(class)[T. Religious]	0.295	0.115	0.010	0.112	0.076	0.145	0.172	0.064	0.007
C(class)[T. Royalty]	1.175	0.017	^∗∗∗	1.077	0.029	^∗∗∗	1.155	0.015	^∗∗∗
C(class)[T. Scientist]	1.191	0.014	^∗∗∗	0.631	0.012	^∗∗∗	0.854	0.009	^∗∗∗
C(class)[T. SportsManager]	0.306	0.053	^∗∗∗	0.464	0.010	^∗∗∗	0.493	0.010	^∗∗∗
C(gender)[T. female]	−0.044	0.011	^∗∗∗	0.116	0.004	^∗∗∗	0.119	0.004	^∗∗∗
birth_decade	−0.017	0.000	^∗∗∗	0.010	0.001	^∗∗∗	−0.010	0.000	^∗∗∗
Intercept	4.269	0.060	^∗∗∗	−0.684	0.131	^∗∗∗	3.022	0.038	^∗∗∗
AIC	660,646.944			2,206,624.237			2,873,689.603
Num. obs.	134,306.000			456,435.000			590,741.000

Results of three negative binomial regression models that use the number of language editions including a person as dependent variable and gender as independent variable, while controlling for profession and birth century. In the full dataset and the subset of people born after 1900, women are slightly more notable than men since the coefficient is significantly positive even when controlling for other variables. ^∗∗∗: p<0.001.

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