Comment by Gemma Galdón-Clavell

Fairness outcomes can thus arise from interactions among automated processing, human discretion, data quality, vendor opacity, and pipeline structure. We build on prior calls for sociotechnical, end-to-end fairness evaluation, showing empirically why model-level assessment alone can be insufficient for understanding fairness in deployed systems.