Gambling Addiction Defence on Trial: Canadian Expert Witness Perspectives
Bibliographic record
Abstract
The American Psychiatric Association’s evolving recognition of pathological gambling as a behavioral addiction (DSM-III, 1980; DSM-V, 2013) has occasioned increased use of the gambling addiction defence in criminal trials. Reflecting upon our experiences as expert witnesses in criminal and civil liability proceedings where gambling addiction was a significant factor, we a) describe the expert witness role; b) examine the links among frequent and intense EGM play, gambling addiction, and financially-based crimes; c) review how revisions to the Diagnostic and Statistical Manual influenced the Canadian judicial system response to such crime; and d) explore prospects for reducing criminal activity by addicted EGM players. We discuss how and why gambling addiction has become generally accepted as a mitigating factor in Canadian criminal trials. In this commentary we also analyze how the plight of addicted gamblers who resort to criminal behavior might be remediated by a) gambling-specific consumer protection measures; b) tighter regulatory control over the addictive elements of EGM play; c) the implementation of gambling courts; and d) a legislated duty of care owed by gambling providers to EGM players.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".