Relic of a Bygone Era? A Comparative Review of the Defence of “Reasonable Correction” in Canadian and Israeli Criminal Law
Bibliographic record
Abstract
On January 25, 2000, the Supreme Court of Israel delivered its celebrated decision in Plonit. In a landmark ruling, the country’s highest court abolished the criminal law defence of “reasonable correction,” thus making Israel the first common law jurisdiction to recognize children’s right to equal protection from assault. Contrarily, in the Charter case of Canadian Foundation four years later, a majority of the Supreme Court of Canada elected to uphold a similar defence of reasonable correction in section 43 of the Criminal Code. This article therefore takes a fresh look at Canadian Foundation through the instructive lens of Plonit. It seeks, firstly, to supply an abolitionist frame of reference within which Canadian Foundation may be critically assessed. It endeavours, moreover, to buttress four minority positions expressed in Canadian Foundation: (a) section 43 offends Canada’s international commitments, (b) section 43 constitutes an unworkable criminal law standard, (c) section 43 is incongruous with a child’s right to dignity, and (d) striking down section 43 will not open the floodgates to criminal sanction for every trivial or necessary application of force. In doing so, this article concludes that section 43 of the Criminal Code has outlived not only its legal defensibility, but also its social acceptability.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.029 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".