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Record W4310711613

pecifics for generalists: Teaching elementary physical education

2009· article· en· W4310711613 on OpenAlexaff
Chunlei Lu, Amanda De Lisio

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsUniversity of British ColumbiaBrock University
Fundersnot available
KeywordsGeneralist and specialist speciesMathematics educationPsychologyComputer sciencePedagogyBiology
DOInot available

Abstract

fetched live from OpenAlex

Quality physical education offered at the elementary school level is critical for children to understand and develop healthy living. In most countries, physical education is taught by a generalist teacher (i.e., an individual who has not undertaken extensive training in physical education) particularly at the elementary school level. Inadequate and inappropriate preparation has been identified as a major barrier for an elementary generalist to develop and implement a quality physical education program. The purpose of this paper is to identify and discuss helpful strategies used to employ each fundamental component of a quality physical education program and is intended for a generalist audience. More specifically, the paper will explore (a) the (dis)advantage of teaching physical education as a generalist teacher; (b) the ability of physical education to address the whole child; (c) the confusion surrounding physical education and physical activity; and (d) the strategies of a successful physical educator.

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)0.002
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0430.012

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 head0.491
GPT teacher head0.712
Teacher spread0.221 · 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
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
Published2009
Admission routes1
Has abstractyes

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