After the Serpent Beguiled Me: Entrapment and Sentencing in Australia and Canada
Bibliographic record
Abstract
Undercover investigations frequently result in allegations of entrapment by the accused. These allegations can give rise to judicial remedies designed to censure the misconduct of law enforcement, to acknowledge the accused’s diminished culpability, or to do both. The authors survey the Australian and Canadian jurisprudence, revealing an important divergence that has emerged in the use of sentencing as a judicial response to entrapment. In both Canada and Australia, a judge may order the exclusion of evidence or a stay of proceedings where the accused was induced to commit a crime that he or she would not have contemplated but for the inducement by investigators. In Australia, however, courts also have the discretion to mitigate an offender’s sentence in instances where police conduct may have fallen short of entrapment but nevertheless contributed to or escalated the offender’s illegal conduct. Canadian judges do not enjoy this discretion, even where the conduct of investigators raises questions about the offender’s culpability.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".