Bibliographic record
Abstract
性暴力被害を受けた子どもへの支援と、性加害など性的な問題行動を有する子どもへの教育的取り組みを行うため、児童相談所や支援学校等と連携をしながら実践研究を行った。被害を受けた子ども向けの教材として、『はなしてくれてありがとう』と題する心理教育用リーフレットを開発し、子どもの保護者や教職員向けの心理教育教材として『子どもを支えるためにできること』を開発した。また、性的な問題行動を有する子どもへの教育的支援として、研究協力校である支援学校をモデル校とし、性問題行動をもつ生徒への個別プログラムの実施および学校全体での性教育の体制づくりを行った。月1回程度の研究会議でケース検討を重ねたほか、年に2回程度の教職員研修を行い、教職員が性加害と性被害へ対応する際のスキル構築を目ざした。年度ごとに取り組みを報告書にまとめ、「知的障がいのある生徒のための性教育研究『問題となる性行動を有する生徒への支援に関する取り組み』報告書I～III」の3巻を発刊した。実践に役立てるために、米国CARES institute 等において TF-CBT(トラウマ焦点化認知行動療法)に関する研修の受講および資料収集を行い、またカナダで開催された第30回治療教育学会へ参加するなど、国内外の研究者との情報交換等を行った。|In order to support to the children who suffered sexual assault, and to work out the psycho-education for the children who have sexual behatioral problems, this practical research was done cooperating with some child protection centers and a special support school, etc. The material for the children who suffered sexual assault and another material for children's parents and teachers were developed. Moreover, the special support school which is a research partnership school was made into the model program as educational support to the children who sexual behavioral problems, and system for sexual education in whole school. The case conference was done in about 1 time per mouth, and also about two school teachers training were performed per year. These practices were summarized in report every year. In order to use for practice, such as taking some training about TF-CBT (trauma focused cognitive behavior therapy) in U.S. CARES institute and participating in the 30th association of treatment sexual assault in Canada, etc. were performed.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".