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Over the years, ageism in the workplace has become an important topic. However, it remains unclear whether and how gender and occupation relate to age discrimination in hiring decisions. The current study addresses this issue by investigating job suitability ratings and selection decisions by comparing two hypothetical job applicants who differ in age (younger vs. older) and gender (male vs. female) for two occupations (software engineer vs. nurse) in two industries (high-tech and healthcare). This study employed a 2 × 2 × 2 incomplete mixed-factorial design, in which age was a within-subjects factor, and gender and occupation were between-subjects factors. A total of 309 adults participated in the study via Amazon MTurk, and the final sample consisted of 250 participants after data cleaning. Among several findings, the most important results were that when a younger man competed against an older woman as software engineer applicants, he was rated as more suitable for the position, selected more often for the job, and more likely to be hired as a full-time employee. Conversely, when a younger woman competed against an older man for a nursing position, she received more favorable ratings (i.e., job suitability, interpersonal skills, and hiring selections) than him. These results suggest that hiring decisions may be jointly determined by age, gender, and occupation. For example, older female job applicants may be discriminatory targets as software engineers, whereas older male job applicants may be discriminated against as nurses. Organizations should make an effort to reduce biases in hiring decisions.
Advisor: | Hosoda, Megumi |
Commitee: | Trafalis, Sandra, Carr, Valerie |
School: | San Jose State University |
Department: | Psychology-Industrial/Organizational |
School Location: | United States -- California |
Source: | MAI 82/1(E), Masters Abstracts International |
Source Type: | DISSERTATION |
Subjects: | Psychology, Organizational behavior, Occupational psychology, Gender studies, Aging |
Keywords: | Age discrimination, Gender bias, Healthcare, Hiring, Recruitment, Technology |
Publication Number: | 27957257 |
ISBN: | 9798662400191 |