Are We "There" Yet?: A Comparative Analysis of the Canadian Standards on the Corporal Punishment of Children in Schools
Bibliographic record
Abstract
In 1973, British Columbia (B.C.) became the first province in Canada to forbid corporal punishment in public schools (B.C.School Act), followed by the majority of the other provinces.Alberta and Manitoba however, still have no provincially enacted legal prohibition, although many school boards have updated their policies to state that corporal punishment should be prohibited.The spotlight on efforts to repeal Section 43 of the Criminal Code may have dimmed over time on the national stage, but the recent Canadian Truth and Reconciliation report has ignited this issue once again.My article explores the existing laws with a comparative approach (Reimann & Zimmermann, 2008;Orucu & Nelken, 2007), in terms of where Canada stands in relation to other nations' legislative standards and practices.It also addresses the severe behavioural and psychological implications on impacted children.As a developed nation, Canada needs to reconsider its current state of "progress" by inspecting and reviewing existing discourses and legislatives to ensure successful prevention of corporal punishment in schools.This paper intends not only to contribute to the advancement of Canadian legislative standards, but also to practices in local and international education.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".