Estimation of Abuse by Teachers in Special Needs Schools in Japan
Bibliographic record
Abstract
Children with disabilities are at high risk of being abused at school by their teachers. Based on legislation in Japan, the authors assessed the implementation of measures to prevent abuse and reasonable accommodations (arrangements) available at special needs schools in Japan. Government data has concentrated only on physical maltreatment by teachers; thus, we also collected grievances from parents to estimate the prevalence rate of abuse at special education settings. Of the 1,077 schools that were sent questionnaires, 333 completed them. Educational programmes for staff were the most common measure employed to prevent abuse. Various forms of support, including communication with internet-communication technology, were provided in relation to reasonable accommodations. After the implementation of the abuse prevention act for persons with disabilities, 14 (4.20%) schools reported grievances from parents claiming that their child had been bullied by teachers. Because Japan does not have educational inspection systems, such as the United Kingdom and the Netherlands, we assumed the incidence rate. Provided that all the grievances were related to abuse, the incidence rate was 0.02–0.05% (95% CI).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".