Bibliographic record
Abstract
Towards the beginning of March 1983, reports of a gang rape that took place in a barroom in New Bedford, Massachusetts, entered the national media. The following New York Times report provides an early account of the crime that came to be known as the “Big Dan’s gang rape”: A 21-year-old woman, recent to the neighbourhood, stopped at Big Dan’s tavern for some cigarettes and a drink about 9 P.M. Sunday, March 6. She emerged sometime after midnight, bruised, half naked and screaming for help. Her clothes had been torn from her, she told the police officers who were called by a motorist who had stopped to help her. She said she had been hoisted to the bar’s pool table, tormented and raped beyond count by a group of men who held her there for more than two hours while the rest of the men in the bar stood watching, sometimes taunting her, and cheering. When the police fetched her clothing and took her back inside, two of the men she identified as her assaulters were still there. Big Dan’s, which is one large room, had apparently been open for business the whole time. No one had called the police. One unidentified witness was quoted as saying in The New Bedford Standard-Times, “Why should I care?”(Clendinen A16)
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".