Language and gender: Computerized text analyses predict gender ratios from organizational descriptions

Area of Science:

• Computational Linguistics
• Sociology of Work
• Gender Studies

Background:

• Job advert language can perpetuate gender stereotypes, influencing perceived job fit and maintaining labor market segregation.
• Organizational descriptions may implicitly reflect and reinforce existing gender segregation within companies.

Purpose of the Study:

• To investigate if and how language in organizational descriptions mirrors gender segregation.
• To analyze differences in language used by organizations with predominantly female versus male workforces.

Main Methods:

• Computational text analysis of organizational descriptions from LinkedIn for 409 large Swedish companies.
• Statistical analysis to correlate language features with employee gender ratios.
• Comparative analysis of language in organizations with majority female vs. male employees.

Main Results:

• Language in organizational descriptions significantly predicted employee gender ratios.
• Organizations with more women employees used language emphasizing local focus and internal relations.
• Organizations with more men employees used language highlighting international focus and sales/customer relations.

Conclusions:

• Organizational descriptions reflect gender stereotypes, associating women with local and men with global workplaces.
• Disparities in language may deter underrepresented genders from applying, thus perpetuating job market segregation.
• Language in recruitment materials plays a crucial role in maintaining gendered labor market structures.