Bibliographic record
Abstract
The word “enforcer” or “hockey goon” does not appear in the 2007–2008 National Hockey League (NHL) rulebook. However, every player and coach knows the meaning of those words. Hockey has always had its share of enforcers or “goons” that have protected star players. Steve Moore, former Harvard captain, and his parents have sued NHL tough-man Todd Bertuzzi, the Vancouver Canucks, and the partnership that owned the Canucks for an on-ice incident that occurred between Moore and Bertuzzi on March 8, 2004. Dedicated hockey fans have followed the lawsuit, but with the “incident” now over four years old many have forgotten about the vicious nature of the hit Bertuzzi rendered on Moore. Much of the discussion circulating around the Moore lawsuit has been that of hockey’s unwritten rule dealing with enforcers and hockey’s code of retaliation. Steve Moore’s lawsuit challenges hockey’s unwritten rules dealing with fighting and retaliation. Moore’s civil lawsuit has been frowned upon by some players. The outcome of the lawsuit could set the boundaries for future play in the NHL. Consider a sport where physically fit athletes are moving on skates at more than 20 miles an hour, wielding large wooden or metal sticks, and all vying for a 1 inch frozen piece of vulcanized rubber that has the ability to travel at more than 100 miles per hour. In addition, all of this activity takes place on a rock hard sheet of ice, 200 by 85 feet, with boundaries made of boards and glass. Whoever controls the puck also controls his future. A player could gain worldwide notoriety, obtain a lucrative contract, and eventually be presented with Lord Stanley’s Cup. Simply put, a lot is at stake.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".