Racial Bias in Fans and Officials: Evidence from the Italian Serie A
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent scholarship studying the impact of race-based prejudice has emphasized its rampant persistence throughout all aspects of modern society, including the world of sports. Prior research from American leagues has shown that even referees, trained officials intended to enact neutral judgements, are subject to bias against Black and dark-skinned players. To extend these studies and inform policies aimed at combating racial bias in public spaces more broadly, we report results from a unique dataset of over 6500 player-year observations from the Italian Serie A to examine whether these biases persist in European football. Our results show that darker-skinned players receive more foul calls and more cards than lighter-skinned players, controlling for a range of potential confounders and productivity-relevant mediators. By exploiting an absence of fans induced by the COVID-19 pandemic, we also present preliminary evidence that fans may play a key role in inducing poor calls against darker-skinned players.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it