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Record W2370718508

Comparison on the contents of physical education and health course in middle schools among foreign countries

2007· article· en· W2370718508 on OpenAlexaboutno aff
Guo Hong-bo

Bibliographic record

VenueJournal of Shandong Institute of Physical Education and Sports · 2007
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical educationLifelong learningFlexibility (engineering)UnificationHealth educationSubjectivityMedical educationMathematics educationPsychologySociologyPedagogyEconomic growthMedicineHealth careManagementComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper comparatively analyzes and researches on the contents of physical education and health course among England,America,New Zealand,Canada and Japan.The conclusion shows that the common trend of the contents of physical education and health course among foreign countries is carving up the contents of PE according to the learning field;attaching importance to the contents of fitness and motor skills;appearing to the flexibility and selectivity,and fitting the difference of individual;the combination of PE and health teaching;emphasizing the lifelong PE and its contact with life.The inspiration of curricular contents' reform is that fitting the needs of society and science development;paying attention to the subjectivity needs of school PE and caring for the difference of individual;emphasizing the function of building the health of students and the unification of PE and health education,strengthening the education of PE and health knowledge;formally appearing to diversification and flexibility;reflecting the need of lifelong PE goal and paying attention to the unification of athletics,body building and entertainment.The learning field should provide the samples of knowledge and skill fitting the demand of contents.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.371
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2007
Admission routes1
Has abstractyes

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