Pro-female discrimination among low sexism respondents, in a survey experiment about police chiefs

Political Research Quarterly published Huber and Gunderson 2022 "Putting a fresh face forward: Does the gender of a police chief affect public perceptions?". Huber and Gunderson 2022 reports on a survey experiment in which, for one of the manipulations, a police chief was described as female (Christine Carlson or Jada Washington) or male (Ethan Carlson or Kareem Washington).

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Huber and Gunderson 2022 has a section called "Heterogeneous Responses to Treatment" that reports on results that divided the sample into "high sexism" respondents and "low sexism" respondents. For example, the mean overall support for the female police chief was 3.49 among "low sexism" respondents and was 3.41 among "high sexism" respondents, with p=0.05 for the difference. Huber and Gunderson 2022 (p. 8) claims that [sic on the absence of a "to"]:

These results indicate that respondents' sexism significantly moderates their support for a female police chief and supports role congruity theory, as individuals that are more sexist should react more negatively [sic] violations of gender roles.

But, for all we know from the results reported in Huber and Gunderson 2022, "high sexism" respondents might merely rate police chiefs lower relative to how "low sexism" respondents rate police chiefs, regardless of the gender of the police chief.

Instead of the method in Huber and Gunderson 2022, a better method to test whether "individuals that are more sexist...react more negatively [to] violations of gender roles" is to estimate the effect of the male/female treatment on ratings about the police chief among "high sexism" respondents. And, to test whether "respondents' sexism significantly moderates their support for a female police chief", we can compare the results of that test to results from a corresponding test among "low sexism" respondents.

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Using the data and code for Huber and Gunderson 2022, I ran the code up to the section for Table 4, which is the table about sexism. I then ran my modified code of the Huber and Gunderson 2022 code for Table 4, among respondents Huber and Gunderson 2022 labeled "high sexism", which is for a score above 0.35 on the measure of sexism, and then among respondents Huber and Gunderson 2022 labeled "low sexism", which is for a score below 0.35 on the measure of sexism.

Results are below, indicating a lack of p<0.05 evidence for a male/female treatment effect among these "high sexism" respondents, along with a p<0.05 pro-female bias among the "low sexism" respondents on all but one of the Table 4 items.

HIGH SEXISM RESPONDENTS------------------
                     Female Male
                     Chief  Chief
Domestic Violence    3.23   3.16  p=0.16
Sexual Assault       3.20   3.16  p=0.45
Violent Crime Rate   3.20   3.23  p=0.45
Corruption           3.21   3.18  p=0.40
Police Brutality     3.17   3.17  p=0.94
Community Leaders    3.33   3.31  p=0.49
Police Chief Support 3.41   3.39  p=0.52

LOW SEXISM RESPONDENTS------------------
                     Female Male
                     Chief  Chief
Domestic Violence    3.40   3.21  p<0.01
Sexual Assault       3.44   3.22  p<0.01
Violent Crime Rate   3.40   3.33  p=0.10
Corruption           3.21   3.07  p=0.01
Police Brutality     3.24   3.11  p=0.01
Community Leaders    3.40   3.32  p=0.02
Police Chief Support 3.49   3.37  p<0.01

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I'm sure that there might be more of interest, such as calculating p-values for the difference between the treatment effect among "low sexism" respondents and the treatment effect among "high sexism" respondents, and assessing whether there is stronger evidence of a treatment effect among "high sexism" respondents higher up the sexism scale than the 0.35 threshold used in Huber and Gunderson 2022.

But I at least wanted to document another example of a pro-female bias among "low sexism" respondents.