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Record W1977384195 · doi:10.1177/1090198105285327

Effect of a Ban on Extracurricular Sports Activities by Secondary School Teachers on Physical Activity Levels of Adolescents: A Multilevel Analysis

2006· article· en· W1977384195 on OpenAlexaff
Roman Pabayo, Jennifer O’Loughlin, Lise Gauvin, Gilles Paradis, Katherine Gray‐Donald

Bibliographic record

VenueHealth Education & Behavior · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsMcGill UniversityUniversité de MontréalToronto Public Health
Fundersnot available
KeywordsPhysical activityPhysical educationConfidence intervalPsychologyOdds ratioMedicinePhysical activity levelPhysical therapyMathematics education

Abstract

fetched live from OpenAlex

To study the effect of a teachers' ban on supervising sports-related extracurricular physical activities (ECAs), levels of physical activity among 979 grade 7 students (mean age=12.7 [0.5] years at baseline) were compared during and after the ban in seven schools that fully implemented the ban, and three schools that did not implement the ban fully. On average, schools offered 18.0 (SD=5.1) ECAs during a no-ban school year. Students attending full implementation schools were significantly more likely than students in nonimplementation schools to be active after the ban ended (odds ratio for being active=1.89 [95% confidence interval: 1.39, 2.58]). They also increased the number of physical activities in which they participated (coefficient=4.04; SE=1.01). Ending a teachers' ban on sports-related ECAs was associated with increased involvement in physical activity among secondary school students.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.405
Teacher spread0.388 · 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 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

Citations18
Published2006
Admission routes1
Has abstractyes

Explore more

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