Gender Stereotypes and Hiring Biases in Female-Dominated Occupations
Abstract
Previous research supports that the disproportionate gender presence among certain fields may be due to discrimination based on gender stereotypes (Samuel & Mokoaleli, 2017; Forsman & Barth, 2017; Heilman & Caleo, 2018). For example, women may be hired over men for a nursing position due to their assumed compassionate and nursing dispositions. Additionally, men may be hired over women for leadership positions based on assumed qualities of assertiveness and logical thinking (Rice & Barth, 2017). This study extends current research by investigating the relationship between individual stereotype endorsements and hiring decisions. Current literature examines fields where women are typically underrepresented, such as science, technology, engineering, and math: also known as STEM (Cundiff & Vescio, 2016). This study lends a contribution by focusing on positions where men are likely underrepresented, such as nursing and specific leadership positions, as it is unclear how gender stereotypes will influence hiring decisions in these fields. Participants will assess statements of potential employees for either a nursing or leadership position, rate each individual’s skill sets, and ultimately make a hiring decision between the two applicants. Participants will also be surveyed to assess their degree of stereotype endorsement. Using a 2x2 mixed method ANOVA, we will analyze whether traditional gender stereotypes influence lab simulated hiring decisions. Supported by previous research, we hypothesize that participants with high levels of stereotype endorsement will select applicants whose gender is congruent with the stereotypical gender of the field (Rice & Barth, 2017). For example, choosing the female applicant for the nursing position and the male applicant for the leadership position. Furthermore, participants with low stereotype endorsement are expected to have relatively similar skillset ratings for applicants regardless of gender. Understanding the relationship between gender stereotypes and discrimination in various fields will assist fostering workforces that are fair and equal.
Gender Stereotypes and Hiring Biases in Female-Dominated Occupations
Previous research supports that the disproportionate gender presence among certain fields may be due to discrimination based on gender stereotypes (Samuel & Mokoaleli, 2017; Forsman & Barth, 2017; Heilman & Caleo, 2018). For example, women may be hired over men for a nursing position due to their assumed compassionate and nursing dispositions. Additionally, men may be hired over women for leadership positions based on assumed qualities of assertiveness and logical thinking (Rice & Barth, 2017). This study extends current research by investigating the relationship between individual stereotype endorsements and hiring decisions. Current literature examines fields where women are typically underrepresented, such as science, technology, engineering, and math: also known as STEM (Cundiff & Vescio, 2016). This study lends a contribution by focusing on positions where men are likely underrepresented, such as nursing and specific leadership positions, as it is unclear how gender stereotypes will influence hiring decisions in these fields. Participants will assess statements of potential employees for either a nursing or leadership position, rate each individual’s skill sets, and ultimately make a hiring decision between the two applicants. Participants will also be surveyed to assess their degree of stereotype endorsement. Using a 2x2 mixed method ANOVA, we will analyze whether traditional gender stereotypes influence lab simulated hiring decisions. Supported by previous research, we hypothesize that participants with high levels of stereotype endorsement will select applicants whose gender is congruent with the stereotypical gender of the field (Rice & Barth, 2017). For example, choosing the female applicant for the nursing position and the male applicant for the leadership position. Furthermore, participants with low stereotype endorsement are expected to have relatively similar skillset ratings for applicants regardless of gender. Understanding the relationship between gender stereotypes and discrimination in various fields will assist fostering workforces that are fair and equal.