ALTERNATIVE SCHOOL DISCIPLINE PRINCIPLES AND INTERVENTIONS: AN OVERVIEW OF THE LITERATURE
Bibliographic record
Abstract
Increasing evidence shows that punitive discipline is ineffective and detrimental. Using empowerment theory and the opportunity-to-learn conceptual framework, this literature review seeks to broaden school personnel’s knowledge of alternative discipline interventions. Searching ERIC and JSTOR databases, we looked for English language, North American literature published between 1996 and 2016 that discussed alternative individual and school-wide disciplinary approaches. The literature we found indicates that punitive measures are counter-productive; that several alternative disciplinary models share common principles; and that studies point to favourable outcomes of some alternative school discipline models. While the transition towards alternative discipline may require additional resources and years of adjustment, a healthier school climate can foster the empowerment and academic achievement of marginalized students.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".