1 Study selection rule

Studies investigating the development of the male=brilliance stereotype in children will be included.

2 p-curve disclosure table

Table 1: p-curve disclosure table
Paper Hypothesis Study design Key statistical result Quoted result Result Robustness result
Bian, Leslie & Cimpian (2017) As the relevant cultural notions are being assimilated, children’s responses should likewise differentiate between these traits. 2x2x2 Design Three-way Interaction Study 1: The crucial three-way interaction among trait, gender, and age (5- vs. 6- and 7-year-olds) was significant, Wald chi-squared = 10.01, P = .002. Study 2: the three-way interaction among trait, gender, and age (5- [younger]vs. 6- and 7-year-olds [older]) was significant, Wald chi-squared = 7.51, P = .006. (Found in the supplementary materials, df calculated) Wald chi-squared(15) = 10.01, P = .002. Wald chi-squared(9) = 7.51, P = .006. NA
Cvencek, Meltzoff & Greenwald (2011) American elementary school children will associate math more strongly with boys than with girls on both implicit and self-report measure. 2x2 Design Both simple effects On the implicit measure, boys associated math with own gender more strongly than girls did in Grades 1-2, t(83) = 3.91, p < .001, and similar t tests were significant at each adjacent two-grade level thereafter (all ps < .001). For self-report measures, boys were more likely than girls to pick the same-sex character as liking to do math in Grades 1-2, t(87) = 2.66, p < .01, and this was stable for subsequent grade levels (all ps < .05). t(83) = 3.91, p < .001. t(87) = 2.66, p < .01 NA
Martinot, Bagès, Désert (2012) The age of the stereotyped target moderates the effect of gender target on math-ability stereotype awareness among elementary school children for both direct and indirect measures. 2x2 Design 2x2 Interaction and both simple effects The analysis revealed a Stereotyped Target’s Gender X Participants’ Gender interaction effect, F(1, 379) = 13.02, p<.001, =.18. Indirect measure: children thought that the best student in math is a girl compared to a boy, and compared to either a girl or a boy, ² (2, N=383) = 92.15, p<.001. Regardless of their gender, they believed that the best character to do long studies in math is a man compared to a woman, and compared to a woman or a man, ² (2, N=387) = 83.04, p<.001. They also thought that the best character to teach math is a man compared to a woman, and compared to either a woman or a man, ² (2, N=389) = 30.61, p<.001. Finally, the children believed that the best character to be a mathematician is a man compared to a woman, and compared to either a woman or a man, ² (2, N=385) = 98.53, p<.001. F(1, 379) = 13.02, p<.001. ² (2, N=383) = 92.15, p<.001. ² (2, N=387) = 83.04, p<.001. ² (2, N=389) = 30.61, p<.001. ² (2, N=385) = 98.53, p<.001. NA

3 p-curve results

Figure 1: p-curve

Figure 1: p-curve

The p-curve shows that, for the papers and results cited, there is a strong right-skew (towards very low p-values), indicating what seems to be true effects.

4 References

Bian, L., Leslie, S. J., & Cimpian, A. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science, 355(6323), 389-391.

Cvencek, D., Meltzoff, A. N., & Greenwald, A. G. (2011). Math-gender stereotypes in elementary school children. Child development, 82(3), 766-779.

Martinot, D., Bages, C., & Desert, M. (2012). French children’s awareness of gender stereotypes about mathematics and reading: When girls improve their reputation in math. Sex Roles, 66(3-4), 210-219.