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Record W1772434089

Physical Education Teacher Education (PETE) in Canada

2011· article· en· W1772434089 on OpenAlexaffabout
Nancy Melnychuk, Daniel B. Robinson, Chunlei Lu, David Chorney, Lynn Randall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsSt. Francis Xavier UniversityUniversity of New BrunswickBrock UniversityUniversity of Alberta
Fundersnot available
KeywordsTeacher educationPhysical educationPedagogyCurriculumSociologyUnderpinningWork (physics)PsychologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to identify physical education (PE) teacher educators and examine physical education teacher education (PETE) programs presently offered at undergraduate degree-granting Canadian universities. The investigation was conceptualized by issues related to the dislodging of PETE from a central to a marginal role in higher education, contrasting discourses, and the education of children and youth in a post-modern society. In an effort to examine the worldview orientation, underpinning discourses, curricula, structure, and organization of Canada's programs, 36 PE teacher educators from 20 universities completed an online survey. Results enabled a profile of Canada's PE teacher educators and the PETE programs in which they work. Collectively, the findings suggest a need for critical consideration and/or revisiting of programs in light of changing societal and student needs for global, socially, and culturally responsive PETE. Key words: physical education teacher education (PETE), teacher education

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.295

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.107
GPT teacher head0.471
Teacher spread0.364 · 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 designQualitative
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

Citations30
Published2011
Admission routes2
Has abstractyes

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