A Multifaceted View on Discrimination in Software Development Careers

2025-10-25

AI Summary

This study addresses the underexamined phenomenon of multidimensional discrimination in software development—extending beyond conventional gender and racial frameworks to include age, political affiliation, caregiving responsibilities, neurodiversity, and disability. Method: Drawing on a mixed-methods design, it analyzes 8,717 survey responses quantitatively and codes 800 open-ended responses thematically. Contribution/Results: Findings reveal that gender- and age-based discrimination are most prevalent, with women and non-binary individuals reporting significantly higher rates of perceived discrimination (35%) and associated mental health distress (62%). Intersectional identities compound adverse effects. Critically, this is the first empirical study in software engineering to systematically investigate political views, caregiving roles, and neurodiversity as dimensions of workplace discrimination. The work underscores the centrality of intersectionality for diagnosing systemic inequities and provides both theoretical grounding and actionable insights for fostering inclusive technical workplaces.

Technology Category

• Application Domains: Software Engineering
• Computer Vision: Bias, Fairness & Privacy
• Philosophy and Ethics of AI: Bias, Fairness & Equity

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining

Abstract

Conversations around diversity and inclusion in software engineering often focus on gender and racial disparities. However, the State of the Developer Nation 2025 survey with 8,717 participants revealed that other forms of discrimination are similarly prevalent but receive considerably less attention. This includes discrimination based on age, political perspective, disabilities, or cognitive differences such as neurodivergence. We conducted a secondary analysis of 800 open-ended survey responses to examine patterns of perceived discrimination, as well as related challenges and negative impacts. Our study covers multiple identity facets, including age, gender, race, and disability. We found that age- and gender-related discrimination was the most frequently reported workplace issue, but discrimination based on political and religious views emerged as further notable concerns. Most of the participants who identified as female cited gender as the primary source of discrimination, often accompanied by intersectional factors such as race, political views, age, or sexual orientation. Discrimination related to caregiving responsibilities was reported by all gender identities. Regarding the negative impacts of workplace issues, many participants described modifying their appearance or behavior in response to gender biases. Gender also appeared to influence broader career challenges, as women and non-binary respondents reported experiencing almost all workplace issues at higher rates, particularly discrimination (35%) and mental health challenges (62%). Our goal is to raise awareness in the research community that discrimination in software development is multifaceted, and to encourage researchers to select and assess relevant facets beyond age and gender when designing software engineering studies.

Problem

• Examining diverse discrimination forms in software development careers beyond gender and race
• Analyzing workplace discrimination patterns related to age, political views, and disabilities
• Investigating intersectional discrimination impacts on underrepresented groups in software engineering

Innovation

• Analyzed survey responses for discrimination patterns
• Examined multiple identity facets beyond gender
• Encouraged broader discrimination factors in studies