Stereotyping Latinas: candidate gender and ethnicity on the political stage

ABSTRACT

Current scholarship analyzes how gender influences the character-based traits and belief-based traits that women candidates are attributed. Yet little is known about the effect of the intersection of candidate sex and ethnicity on stereotyping. Thus, I explore whether candidate stereotyping functions similarly for Latina candidates as it does for white women. I also test if the race or ethnicity of the voter plays any role in how Latina women candidates are stereotyped. Given that we know that race/ethnicity matter for voters, particularly voters of color, I assess what occurs when candidate sex is also included. With the use of original survey data and through the use of difference of means tests I analyze how a Latina candidate compares with three other candidate types on feminine, masculine, and belief-based traits. I also compare how stereotyping varies based on the race and ethnicity of the voter. On the one hand my results are mixed regarding how Latina candidates are stereotyped, while on the other I do find that Latina/o respondents assess Latina candidates in a more favorable manner relative to white respondents.

KEYWORDS:

• Candidate stereotypes
• Latina candidates
• Latina politicians
• gender stereotypes
• race/ethnic stereotypes
• women candidates
• candidate evaluations

View correction statement:

Correction

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article was originally published with errors, which have now been corrected in the online version. Please see Correction (https://doi.org/10.1080/21565503.2021.1968646)

Notes

1 Arciniega et al. (2008) explain machismo as aggressive, sexist, chauvinistic, and hypermasculine behavior. The term machismo has a long history of being associated with the Latina/o community, which is why it is possible that when Latina candidates are stereotyped people may perceive that her upbringing was more conservative. Thus, thinking of her as ideologically conservative.

2 In 2018 it was reported that the percentage of Latinas/os who identify as Catholic went down by 10% from 57% in 2008 to 47%. Subsequently, Latinas/os leaving the Catholic faith are choosing to identify as unaffiliated and this percentage increased by 8% between 2009 and 2018 (Molina, 2019).

3 Gender incongruencies are present when the stereotyped gender of a professional role does not fit with the gender of the person that is seeking the role – thus resulting in a negative evaluation of that person (Smith, Paul, and Paul 2007).

4 At the time this survey was conducted, YouGov did not have a sample of Latinas/os who are primarily Spanish speakers. Undoubtedly, there is a value in including the opinions of those who are Spanish language dominant. However, existing surveys that have been partially conducted in Spanish, such as the Latino National Survey, do not have the questions necessary to address candidate stereotyping of Latinas.

5 For clarity and parsimony, a principal component factor analysis was conducted of all of the traits and two factors with eiganvalues over 1 were found. One factor was composed of traits usually associated with women candidates (warm, compassionate, people skills, administrative skills, able to compromise, democratic and trustworthy) as well as one agentic trait, that of strong leader. This factor is labeled feminine factor. On the second factor the traits highly associated with male candidates loaded highly (assertive, aggressive, and ambitious) and is labeled masculine factor.

6 Please refer to Table 1 where you will see that the Latina candidate is stereotyped as warm, compassionate, having administrative skills, being democratic, and trustworthy more so than her male counterpart or the female candidate and the differences are significant.

7 Significance values can be found in Appendix B in Table 2b.

8 For more information regarding measurements and coding for OLS and Ordered Logit Regressions see Appendix C.

9 This variable is a scale variable that ranges from 1–7 where 1 = very liberal and 7 = very conservative.

10 Considering that the standard error values and significance values for interacted variables cannot be attained from the regression alone a linear combination of estimators was conducted and is what is reported in Table 3.