Rose-Colored Glasses: Competing Media Perceptions of the Pete Rose Betting Scandal
Bibliographic record
Abstract
In a 2004 autobiography, legendary player Pete Rose confessed to gambling on baseball games, even those that included his Cincinnati Reds. The passage of time has clarified much about the betting scandal that plagued Major League Baseball (MLB) in 1989. Over the course of the six-month saga, Rose’s denials and his adversarial relationship with the Commissioner’s Office shrouded MLB’s investigation in controversy. This study explores the press coverage of the scandal in 1989 and determines that the Cincinnati press was more sympathetic to, and supportive of Rose than out-of-market coverage, represented in this investigation by The New York Times. These findings are consistent with previous research that indicates that local media favors hometown institutions during times of crisis. This study expands that theory by demonstrating that favoritism extends to individual players whose connection to the city is significant, and furthers our understanding of the media’s role in shaping the narratives of scandal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".