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Labour Economics

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Labour Economics

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Research Frontiers in Discrimination and Algorithmic Bias in Hiring

Examines racial, gender, and other forms of discrimination amplified or mitigated by automated recruitment and hiring algorithms.

Algorithmic Gatekeeping in High-Skill Labour Markets
Intersectional Bias Amplification in Automated Recruitment
Proxy Discrimination Through Ostensibly Neutral Hiring Signals
Temporal Drift in Algorithmic Fairness Across Economic Cycles
Statistical Parity Versus Individual Fairness in Hiring Systems
Feedback Loops Between Algorithmic Selection and Occupational Segregation
Dark Patterns in Resume Screening and Candidate Exclusion
Protected Class Inference From Unprotected Data Attributes
Algorithmic Discrimination at Scale Across Organizational Hierarchies
Audit Methods for Detecting Hidden Bias in Black-Box Hiring Models

All Labour Economics PhD categories