Opposition to Women Political Leaders: Gender Bias and Stereotypes of Politicians Among Japanese Voters

Figures & data

Figure 1. Multivariate Estimates of Opposition to Women Political Leaders.

Note: Dots and triangles represent estimated proportions of respondents who oppose women political leadership (prime minister and defense minister, respectively) by respondent attributes, and the lines are 95% confidence intervals from the regression model.

Figure 2. Policy Stereotypes Among Japanese and American Voters.

Note: The X-axis shows the average value across all respondents for each policy issue domain, with a value of 1 if the respondent answered that men politicians are better suited, −1 if the respondent answered that women politicians are better suited, and 0 if the respondent answered neither. No comparable data are available on birthrate, social welfare, and diplomacy issues in the US survey (Dolan 2014a).

Figure 3. Personal Trait Stereotypes Among Japanese and American Voters.

Note: The X-axis shows the average value across all respondents for each personality trait, with a value of 1 if the respondent answered that men politicians are more applicable, −1 if the respondent answered that women politicians are more applicable, and 0 if the respondent answered neither. No comparable data are available on trust and competence attributes in the US survey (conducted by Dolan 2014a).

Table 1. Results of Logistic Regression on Gender Stereotypes Toward Policy Issue Domains.

	Child Care	Birthrate	Education	Social Welfare	Health Care	Immigration	Deficit	Crime	Economy	Diplomacy	National Security
Men	−0.368***	−0.420***	−0.076	0.115	0.140	0.206**	0.197**	0.125	0.203**	0.266***	0.333***
	(0.091)	(0.084)	(0.083)	(0.087)	(0.090)	(0.096)	(0.087)	(0.083)	(0.085)	(0.083)	(0.083)
Age	0.003	0.001	−0.005**	0.004	−0.001	0.008**	0.007***	0.008***	0.005**	0.013***	0.014***
	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)
Education	−0.071**	−0.024	−0.092***	−0.070**	−0.109***	−0.104***	−0.089***	−0.111***	−0.073**	−0.143***	−0.115***
	(0.033)	(0.030)	(0.030)	(0.031)	(0.032)	(0.034)	(0.031)	(0.030)	(0.030)	(0.030)	(0.030)
LDP	0.109	0.222**	0.289***	0.390***	0.331***	0.706***	0.692***	0.726***	0.799***	0.908***	0.920***
	(0.104)	(0.097)	(0.095)	(0.099)	(0.102)	(0.106)	(0.097)	(0.094)	(0.096)	(0.096)	(0.097)
Others	0.174	0.218*	0.336***	0.540***	0.265**	0.151	0.284**	0.035	0.315***	0.088	0.082
	(0.128)	(0.117)	(0.115)	(0.117)	(0.124)	(0.135)	(0.120)	(0.116)	(0.117)	(0.114)	(0.114)
Num.Obs.	2681	2681	2681	2681	2681	2681	2681	2681	2681	2681	2681
AIC	3179.8	3569.3	3590.6	3381.9	3222.8	2920.3	3383.1	3612.0	3499.4	3616.4	3608.0
BIC	3486.3	3875.8	3897.1	3688.3	3529.2	3226.7	3689.5	3918.5	3805.9	3922.9	3914.4
Log.Lik.	−1537.888	−1732.660	−1743.296	−1638.931	−1559.380	−1408.126	−1639.527	−1754.004	−1697.702	−1756.201	−1751.976

* p < 0.1, ** p < 0.05, *** p < 0.01. Standard errors are in parentheses. The reference group of party supports is Independent.

Table 2. Results of Logistic Regression on Gender Stereotypes Toward Personality Traits.

	Compassion	Honest	Intelligent	Trust	Competent	Consensus Building	Decisive	Leadership	Political Experience	Dominate
Men	−0.081	−0.011	−0.076	0.196*	−0.033	0.130	0.170**	0.185**	0.118	−0.171**
	(0.084)	(0.096)	(0.098)	(0.107)	(0.109)	(0.091)	(0.086)	(0.084)	(0.081)	(0.083)
Age	0.002	0.010***	−0.007**	0.000	−0.002	0.004	0.007***	0.010***	0.014***	0.015***
	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)	(0.003)
Education	−0.080***	−0.065*	−0.063*	−0.077**	−0.056	0.007	−0.088***	−0.101***	−0.010	0.013
	(0.030)	(0.034)	(0.035)	(0.037)	(0.038)	(0.032)	(0.030)	(0.030)	(0.029)	(0.029)
LDP	0.272***	0.216*	0.510***	0.442***	0.717***	0.857***	0.866***	1.147***	0.558***	0.183*
	(0.096)	(0.111)	(0.110)	(0.119)	(0.121)	(0.100)	(0.096)	(0.097)	(0.094)	(0.095)
Others	0.284**	0.435***	0.512***	0.310**	0.447***	0.157	0.363***	0.141	0.216*	0.367***
	(0.115)	(0.127)	(0.132)	(0.145)	(0.150)	(0.129)	(0.118)	(0.116)	(0.112)	(0.117)
Num.Obs.	2681	2681	2681	2681	2681	2681	2681	2681	2681	2681
AIC	3575.2	2924.5	2855.2	2526.1	2424.9	3159.8	3448.7	3543.8	3706.8	3639.7
BIC	3881.7	3231.0	3161.7	2832.6	2731.4	3466.3	3755.2	3850.2	4013.3	3946.2
Log.Lik.	−1735.604	−1410.274	−1375.624	−1211.060	−1160.463	−1527.900	−1672.334	−1719.876	−1801.386	−1767.848

* p < 0.1, ** p < 0.05, *** p < 0.01. Standard errors are in parentheses. The reference group of party supports is Independent.

Table A1. Summary Statistics of Respondent Attributes.

Variable	Category	Target (%)	Completes (%)
Age	18 to 29 years old	15.40	14.73
	30 to 39 years old	15.30	15.18
	40 to 49 years old	19.60	19.54
	50 to 59 years old	16.40	16.41
	Over 60 years old	33.30	34.13
Sex	Male	50.40	51.36
	Female	49.60	48.64
Region	Hokkaido	4.17	4.03
	Tohoku	6.87	6.71
	Kanto	35.20	35.66
	Chubu	16.70	16.49
	Kinki	17.70	17.83
	Chugoku	5.53	5.45
	Shikoku	2.83	2.87
	Kyushu	11.00	10.97

Table C1. Univariate Results of List Experiment.

Demographic	Control	Prime Minister	Defense Minister	Prime Minister - Control	Defense Minister - Control	US Estimate
All respondents	1.506 (0.027)	1.602 (0.027)	1.627 (0.027)	0.095* (0.038)	0.120** (0.038)	0.260*** (0.049)
Women	1.541 (0.036)	1.611 (0.038)	1.655 (0.039)	0.070 (0.052)	0.114* (0.053)	0.256*** (0.066)
Men	1.467 (0.041)	1.593 (0.039)	1.599 (0.038)	0.126* (0.056)	0.132* (0.056)	0.260*** (0.072)
No BA	1.591 (0.037)	1.635 (0.038)	1.679 (0.039)	0.044 (0.053)	0.088 (0.053)	0.232*** (0.063)
BA	1.411 (0.039)	1.570 (0.038)	1.573 (0.038)	0.158** (0.055)	0.162** (0.055)	0.264*** (0.078)
18–29 years old	1.429 (0.071)	1.490 (0.074)	1.591 (0.062)	0.061 (0.102)	0.163 (0.094)	0.249* (0.121)
30–50 years old	1.413 (0.044)	1.589 (0.045)	1.466 (0.045)	0.176** (0.063)	0.053 (0.063)	0.359*** (0.081)
51–65 years old	1.522 (0.053)	1.632 (0.051)	1.669 (0.049)	0.110 (0.074)	0.147* (0.072)	0.222* (0.107)
66 years old or above	1.698 (0.055)	1.659 (0.058)	1.895 (0.066)	−0.039 (0.080)	0.198* (0.086)	0.123 (0.095)
Lower class	1.578 (0.047)	1.639 (0.043)	1.684 (0.046)	0.061 (0.064)	0.106 (0.066)	0.268* (0.122)
Middle class	1.451 (0.044)	1.554 (0.045)	1.596 (0.041)	0.103 (0.063)	0.146* (0.060)	0.288** (0.091)
Upper class	1.510 (0.081)	1.534 (0.078)	1.442 (0.083)	0.023 (0.112)	−0.069 (0.116)	0.293* (0.143)
LDP	1.325 (0.045)	1.531 (0.042)	1.537 (0.045)	0.206*** (0.062)	0.212*** (0.064)
Others	1.651 (0.048)	1.696 (0.046)	1.760 (0.050)	0.044 (0.066)	0.108 (0.069)
Independent	1.536 (0.045)	1.584 (0.053)	1.596 (0.047)	0.048 (0.070)	0.060 (0.065)

Note: Entries in the first three columns are mean number of items, with standard errors in parentheses. Social class is measured as explicit categories in our study but is measured by annual income groupings in Streb et al. (2008). The last column shows the results of Burden, Ono and Yamada (2017) in the US. * p < 0.05, ** p < 0.01, *** p < 0.001.

Table C2. Estimated Coefficients from the Regression Models.

	Control		Prime Minister		Defense Minister
	Estimate	SE	Estimate	SE	Estimate	SE
(Intercept)	1.484	0.154	0.161	0.209	0.079	0.216
Male dummy	−0.010	0.062	0.000	0.088	0.017	0.088
BA dummy	−0.144	0.066	0.130	0.091	0.096	0.091
Age	0.007	0.002	−0.005	0.003	−0.001	0.003
Class evel	−0.015	0.046	−0.015	0.064	−0.067	0.066
LDP dummy	−0.344	0.077	0.256	0.105	0.225	0.108
Independent dummy	−0.208	0.078	0.121	0.110	0.137	0.110

Figure F1. Policy Domain Stereotypes by Respondents’ Gender

Note: The X-axis shows the predicted value for respondents’ gender, with a value of 1 indicating that the respondent exhibits gender-based stereotypes. The lines indicate the 95% confidence intervals.

Figure F2. Personality Trait Stereotypes by Respondent Gender

Note: The X-axis shows the predicted value for respondents’ gender, with a value of 1 indicating that the respondent exhibits gender-based stereotypes. The lines indicate the 95% confidence intervals.

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