What Job Would You Apply To? Findings on the Impact of Language on Job Searches
Bibliographic Data
| ID | 12311368 |
|---|---|
| Authors | Ana Maria Diaz (0000-0001-7964-4877, Pontificia Universidad Javeriana, corresponding author), Luz Magdalena Salas (0000-0002-8814-5356, Centro de Estudios Científicos), Claudia Piras (Inter-American Development Bank), Agustina Suaya (0009-0003-0202-249X, Inter-American Development Bank) |
| Year | 2026 |
| Volume | 33 |
| Issue | 4 |
| Pages | 1270-1282 |
| Publication date | 2026-02-28 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Gender Work and Organization (JOURNAL) |
| Journal identifiers | ISSN: 0968-6673 • E-ISSN: 1468-0432 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/gwao.70117 |
| OpenAlex | W7134165998 |
| Language | EN |
| References cited | 12 |
This study examines whether gender‐inclusive language in job advertisements can increase women's interest in applying for male‐dominated occupations. We implemented a discrete choice experiment with 5679 participants in Argentina, Chile, Colombia, Mexico, and Peru. Each respondent evaluates multiple paired ads for the same job with job content held constant and language cues varied within sets. The experimental treatments included replacing masculine‐coded skills with neutral descriptions, omitting skills altogether, using gender‐inclusive grammatical forms, and adding diversity statements. We find that inclusive language increases women's stated interest in applying with no evidence of backlash among men. Describing skills in neutral terms raises selection probabilities for both genders by around 40 percentage points. The use of gender‐inclusive endings increases women's likelihood of selecting an ad by 43 points, whereas diversity statements raise it by 58 points. In contrast, omitting skills reduces interest across the board. Effects are consistent across countries and subgroups. Our results add experimental evidence from Spanish‐speaking labor markets where grammatical gender is salient
Backlash · Constant (computer programming · Diversity (politics · Empirical evidence · Job performance · Respondent · Selection (genetic algorithm · Variation (astronomy · Gender Diversity and Inequality · Gender Studies in Language · Names, Identity, and Discrimination Research
| Citation velocity | historical |
|---|---|
| Highly cited | No |