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Record W2277108171 · doi:10.3138/ptc.2015-19lhc

Boys, Transitions, and Physical (In)activity: Exploring the Socio-Behavioural Mediators of Participation

2016· article· en· W2277108171 on OpenAlexaffvenue
Patrick Jachyra, Barbara E. Gibson

Bibliographic record

VenuePhysiotherapy Canada · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsSocial connectednessPsychologyQualitative researchGrounded theoryPerceptionMeaning (existential)Physical activityAttritionSocial psychologyDevelopmental psychologyMedicinePsychotherapistSociology

Abstract

fetched live from OpenAlex

PURPOSE: To explore the socio-behavioural mechanisms that motivate or dissuade boys' participation in physical activity (PA) as they transition into adolescence and their implications for physical therapy. METHODS: This critical qualitative study involved in-depth interviews using active interviewing techniques with 15 adolescent boys. Data generation and analysis were driven by techniques of grounded theory and Bourdieu's sociology of practice. RESULTS: The analysis identified intersectional relationships among emotions, the inherent pleasures of movement, and a sense of connectedness to PA, each of which acted as a mediating mechanism in motivating participation in PA. Analogously, body dissatisfaction, negative self-perceptions, and repeated instances of explicit and symbolic bullying intersected to dissuade boys from participating and created apathy toward PA. CONCLUSION: Identifying socio-behavioural mechanisms that motivate or dissuade physically active behaviour contributes new knowledge toward understanding PA attrition among boys transitioning to adolescence. As health advocates and movement experts, physiotherapists have an important role in helping adolescents of all abilities to participate in activities that provide them with meaning, inclusivity, and a sense of connectedness to PA.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.744

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.105
GPT teacher head0.439
Teacher spread0.334 · 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

Citations25
Published2016
Admission routes2
Has abstractyes

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