Rewarding Trespass & Other Enigmas: The Strange World of Self-Exclusion & Casino Liability
Bibliographic record
Abstract
In this paper the authors address many contractual and tortious issues associated with the liability of casinos to problem gamblers. The issues in tort are analyzed through the traditional elements of the action – duty of care, standard of care, proximity and recognizable loss. The issues in contract arise from self-identified problem gamblers who may have signed a contractual undertaking to be excluded from casinos (and other gaming venues). Here we examine problems with consideration and capacity in this contractual undertaking. Many of the references cited in this work still relate to the Province of Ontario, since an earlier article (and report) on the issue of problem gambling posited that Ontario’s gaming venues owed a duty of care to problem gamblers. However, many of the basic principles of contract law and tort law raised within this paper will be applicable throughout the Commonwealth and the United States.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.071 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".