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Record W2164872227 · doi:10.33524/cjar.v14i3.98

GETTING GIRLS IN THE GAME: ACTION RESEARCH IN THE GYMNASIUM

2015· article· en· W2164872227 on OpenAlexaffvenue
Daniel B. Robinson

Bibliographic record

VenueThe Canadian Journal of Action Research · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsAction researchPsychologyAction (physics)Mathematics educationPhysical educationPedagogyMedical educationMedicine

Abstract

fetched live from OpenAlex

This article presents an action research project focused on improving physical education (PE) for adolescent female students. One university researcher, three male PE teachers, and 13 of their most disengaged female students participated in the one-year, two-cycle, action research project. The process and results are offered so that future PE teacher educators and PE teachers might recognize action research as a possibility for effecting positive change within PE programs. The results suggest PE teachers and their students can benefit from similar action research projects.

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)0.025
metaresearch head score (Gemma)0.019
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0060.005
Open science0.0030.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.874
GPT teacher head0.712
Teacher spread0.163 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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