USING THE THEME OF BULLYING TO TEACH ABOUT HUMAN RIGHTS IN THE SOCIAL STUDIES CURRICULUM
Bibliographic record
Abstract
ABSTRACT. This article argues that bullying is a human rights violation and should be a social studies curriculum concern. It treats bullying not only as a school incident but also as part of any systematic, continuous violence in any context. There is a discussion of legal implications, applicable educational theory, and attempts to deal with bullying in Canada and foreign jurisdictions. Ten classroom lessons present bullying as a social studies issue for teaching about rights. The lessons include history and current events as well as local, national, and international concerns. A supplementary Internet resource section is provided. UTILISATION DU THEME DE L'INTIMIDATION POUR ENSEIGNER LES DROITS DE LA PERSONNE DANS LE PROGRAMME D'ETUDES SOCIALES RESUME. Cet article soutient que l'intimidation constitue une violation des droits de la personne et que ce probleme doit faire partie du programme d'etudes sociales. Il traite l'intimidation non seulement comme un incident qui survient en milieu scolaire, mais egalement comme un element de toute violence systematique soutenue dans n'importe quel contexte. On y discute des repercussions juridiques, de la theorie de l'education pertinente et des tentatives d'apporter des solutions au probleme de l'intimidation au Canada et a l'etranger. Dix cours en classe presentent l'intimidation comme un sujet d'etudes sociales pour l'enseignement sur les droits. Les cours incluent un historique et des evenements courants ainsi que des preoccupations regionales, nationales et internationales. On y trouve egalement une section sur des ressources Internet additionnelles.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".