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Record W7071927335

Teachers' Understanding of Students' Attitudes and Values Toward Physical Activity in Physical Education Dropout Rates and Adolescent Obesity

2014· article· en· W7071927335 on OpenAlexaff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsPhysical educationFeelingPhysical activityPhysical fitnessOverweightPhysical activity level
DOInot available

Abstract

fetched live from OpenAlex

Structured interviews were used to explore 10th grade teachers' understanding of students' attitudes and values toward physical education and physical activity as a variable in students' probability of dropping physical education and adolescent obesity. When asked how school-based physical education could help combat the problem of students dropping physical education, teachers suggested providing a greater range of choices among activities and providing further opportunity for positive experiences in physical education. Furthermore, teachers stated that the greatest barriers to students who are overweight and/or poorly skilled from enjoying physical education were their feelings of being humiliated, ridiculed, embarrassed, and discriminated against. Teachers demonstrated a lucid understanding of students' attitudes and values, as well as of more debilitating barriers, to increasing physical activity. Notwithstanding, if physical educators are to provide a safe and encouraging environment, they must acknowledge that what they do, or choose not to do, may have an enduring impact on students. Although teachers are unable to do much about extracurricular physical activity, they can do something about the physical education offered in schools. Results of the study suggest that teachers must offer more activities from which students may choose including sports that do not demand highly developed motor skills, but still emphasize fitness and health.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.342
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.372
Teacher spread0.340 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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