The Consequences of NBA Commissioner Adam Silver Arbitrating the Dispute Between the New York Knicks and the Toronto Raptors
Bibliographic record
Abstract
Back in August 2023, the New York Knicks sent a letter addressed to the owner of the Toronto Raptors Larry Tanenbaum claiming the Raptors are engaging in illegal activity involving a former Knicks employee whom they just hired. They claimed that Ikechukwu Azotam, who at the time of his employment with the Knicks was an assistant video coordinator, “had illegally provided the Raptors with more than 3,000 confidential files.” Several days after the letter was sent the Knicks filed a lawsuit in the U.S. Southern District Court of New York against Maple Leaf Sports & Entertainment (Toronto Raptors), Darko Rajakavic, Noah Lewis, Ikechukwu Azotam, and 10 unnamed John Does, requesting damages and asking the court to order the defendants to refrain from using, altering, sharing, reviewing, and copying any of the Knicks confidential information.\nThis post was originally published on the Cardozo Journal of Conflict Resolution website on March 6, 2024. The original post can be accessed via the Archived Link button above.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 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".