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Record W2160384032

SCHOOL CULTURE AND PHYSICAL ACTIVITY: A SYSTEMATIC REVIEW

2013· review· en· W2160384032 on OpenAlexvenueno aff
Greg Rickwood

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2013
Typereview
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Physical culturePhysical educationPsychologyBasketballPhysical activityPedagogyTheme (computing)Mathematics educationSociologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

This review examines literature on aspects of school culture and students’ physical activity participation. The following questions were addressed:  (1) what aspects of school culture have been examined in relation to physical activity, (2) what is the weight of evidence concerning the relationships between school culture factors and physical activity participation, and (3) what are the areas of need in this line of research. Edgar Schein’s organizational culture model offered the framework for analysis in which pertinent articles were categorized into one of three levels of school culture: (1) artifacts, (2) espoused values, and (3) underlying member assumptions. School artifacts associated with physical activity were used more frequently by students and staff when these spaces and equipment were maintained, relevant to the school context and when daily practices allowed access to these artifacts during leisure times. A secondary theme revealed the importance of school-based, adult and student role models; when both were plentiful in schools, students and staff were more active at school on a daily basis. Another key finding indicated that students in Physical Education (PE) classes that reinforced traditional, team games (i.e., basketball, volleyball) were less active than students in PE classes that incorporated culturally relevant, lifestyle, and small-sided games.

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 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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.739
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.142
GPT teacher head0.539
Teacher spread0.398 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2013
Admission routes1
Has abstractyes

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