Comments on Schaffner 2019 "How political scientists should measure sexist attitudes"

Brian Schaffner posted a paper ("How Political Scientists Should Measure Sexist Attitudes") that engaged my critique in this symposium entry about the gender asymmetry in research on gender attitudes. This post provides comments on the part of the paper that engages with my critiques.

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Schaffner placed men as the subject of five hostile sexism items, used responses to these items to construct a male-oriented hostile sexism scale, placed that scale into a regression alongside a female-oriented hostile sexism scale, and discussed results, such as (p. 39):

...including this scale in the models of candidate favorability or issue attitudes does not alter the patterns of results for the hostile sexism scale. The male-oriented scale demonstrates no association with gender-related policies, with coefficients close to zero and p-values above .95 in the models asking about support for closing the gender pay gap and relaxing Title IX.

The hostile sexism items include "Most men interpret innocent remarks or acts as being sexist" and "Many men are actually seeking special favors, such as hiring policies that favor them over women, under the guise of asking for equality".

These items reflect negative stereotypes about women, and it's not clear to me that these items should be expected to perform as well measuring "hostility towards men" (p. 39) as the items perform measuring hostility against women when women are the target of the items. I discussed in this prior post Schaffner 2019 Figure 2, which indicated that participants at low levels of hostile sexism discriminated against men; so the Schaffner 2019 data have participants who prefer women to men, but the male-oriented version of hostile sexism doesn't sort them sufficiently well.

If a male-oriented hostile sexism scale is to compete in a regression against a female-oriented hostile sexism scale, then interpretation of the results needs to be informed by how well each scale measures sexism against its target. I think an implication of the Schaffner 2019 results is that placing men as the target of hostile sexism items doesn't produce a good measure of sexism against men.

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The male-oriented hostile sexism might be appropriate as a "differencer" in the way that stereotype scale responses about Whites can be used to better measure stereotype scale responses about Blacks. For example, for the sexism items, a sincerely-responding participant who strongly agrees that people in general are too easily offended would be coded as a hostile sexist by the woman-oriented hostile sexism item but would be coded as neutral by a "differenced" hostile sexism item.

I don't know that this differencing should be expected to overturn inferences, but I think that it is plausible that this differencing would improve the sorting of participants by levels of sexism.

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Schaffner 2019 Figure A.1 indicates that the marginal effect of hostile sexism reduced the favorability ratings of female candidates Warren and Harris and increased the favorability ratings of Trump; see Table A.4 for more on this, and see Table A.5 for associations with policy preferences. However, given that low hostile sexism associates with sexism against men, I don't think that these associations in isolation are informative about whether sexism against women causes such support for political candidates or policies.

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If I analyze the Shaffner 2019 data, here are a few things that I would like to look for:

[1] Comparison of the coefficient for the female-oriented hostile sexism scale to the coefficient for a "differenced" hostile sexism scale, predicting Trump favorability ratings.

[2] Assessment of whether responses to certain items predict discrimination by target sex in the conjoint experiment, such as for participants who strongly supported or strongly opposed the pay gap policy item or participants with relatively extreme ratings of Warren, Harris, and Trump (say, top 25% and bottom 25%).

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