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Record W4366818093 · doi:10.24985/kjss.2023.34.1.155

Analysis on Elective Courses in Ontario and New South Wales State

2023· article· en· W4366818093 on OpenAlex
Keejoon Yoon, Joo‐Youn Lee

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKorean Journal of Sport Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Safety, and Science Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumChristian ministryPhysical educationMedical educationMedicinePsychologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

PURPOSE This study aims to analyze elective courses in overseas physical education curricula and explore directions to improve the national physical education curriculum. METHODS Physical education curricula from the Ontario Ministry of Education and New South Wales Department of Education, and an administrative announcement book of the 2022 Revised Physical Education Curriculum were collected and analyzed. RESULTS The Ontario physical education curriculum offers a range of elective subjects that fit students’ need to enter universities and colleges. It also has a systematic curriculum flowchart within elective courses. The NSW physical education places importance on learning life skills and offers content-endorsed courses that comprises core studies and optional modules. CONCLUSIONS This study clarified the differences between the learning content of elective subjects and suggested the necessity of developing plans to provide students with effective course path.

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.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.049
GPT teacher head0.345
Teacher spread0.296 · 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