Data and Code for: Meta-analysis of the Political Economy of Digital Labor in the Age of Explainable AI

This repository contains the data and analysis code for a random-effects meta-analysis of the effect of transparency/explainability interventions on worker outcomes (perceived fairness, trust, autonomy, performance) in algorithmic digital labor, submitted to PeerJ Computer Science. Effect sizes (Hedges' g) and moderator codes were extracted from k=40 empirical studies (2016-2024) following PRISMA 2020. The package includes raw coded data (CSV), processed data, analysis code (Python 3.8, numpy/scipy), manuscript tables and figures, and full reproduction instructions (see README.md).