Does School/Site Based Management (SBM) in Japan Achieve its Policy Purposes? A Policy Analysis of Japanese Education Reform RegardingSchool Advisors and School Management Councils
Bibliographic record
Abstract
The purpose of this paper is to analyze decentralized education reform in Japan in terms of School/Site-Based Management (SBM). In the literature, SBM embraces two major elements, namely, the devolution of decision-making authority to the individual school level and Shared Decision-Making (SDM). In Japan, school advisors and school management councils have been established with similar purposes with SBM since 2000. However, because the decision-making authority is not sufficiently devolved to each school and many groups of stakeholders are not significantly involved in decision-making processes, a SBM form of school governance has not been realized in Japan. Cet article a pour but d’analyser la réforme de décentralisation de l’éducation au Japon en termes de l’Administration basée sur l’école ou le site (SBM). Dans la littérature, la SBM se comprend de deux éléments: la dévolution au niveau de chaque école les droits d'exécuter des décisions et la politique des décisions partagées (SDM). Au Japon, les postes de conseillers et les conseils d’administration ont été établis depuis l’an 2000. Et pourtant, parce que les instances ne sont pas assez engagées dans le processus décisionnel, une forme de gouvernance des écoles selon la SBM n’a pas pu se réaliser au Japon.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| 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".