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Record W3030685427 · doi:10.5539/ies.v13n6p78

Comparative Study on Physical Education Laws and Regulations Literature of Chinese and Japanese Schools

2020· article· en· W3030685427 on OpenAlexvenueno aff
Chen Xijun, Zhenhui Xu

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsViewpointsLegislationPhysical educationLawChinaEnforcementPolitical scienceEconomic JusticeLaw enforcementSociologyPedagogy

Abstract

fetched live from OpenAlex

By using the methods of document literature, induction and synthesis, this paper makes a literature review and comparative study on the relevant research of school physical education laws and regulations in China and Japan. Japan is a developed country of school physical education in the world. In the process of building school physical education laws and regulations, there are some methods and ideas to solve school physical education problems. Therefore, it is of great practical significance to analyze the relevant research on Japanese school physical education laws and regulations and to sum up their experience and lessons. This paper quotes the viewpoints of Chinese and Japanese experts and scholars, and makes a literature review on the research of school physical education laws and regulations in Japan from the aspects of the course of construction of school physical education laws and regulations, the system of laws and regulations, legislation, justice, law enforcement, law abiding, content and problems, and comparative study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0130.020
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.156
GPT teacher head0.481
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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