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Record W2507227226 · doi:10.1080/18377122.2016.1196112

Boys, bodies, and bullying in health and physical education class: implications for participation and well-being

2016· article· en· W2507227226 on OpenAlexaffabout
Patrick Jachyra

Bibliographic record

VenueAsia-Pacific Journal of Health Sport and Physical Education · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsReflexivityEthnographyPsychologyDevelopmental psychologyClass (philosophy)LiteracyAttritionSocial psychologyPedagogySociologyMedicineSocial science

Abstract

fetched live from OpenAlex

In Ontario, Canada, adolescent boys are increasingly developing a disinterest towards health and physical education (HPE) class, and also are withdrawing from HPE as soon as they institutionally are allowed to do so. To date however, there has been a dearth of research that has explored the various mechanisms that are dissuading boys from active participation, and prompting boys to develop a cultural disaffection towards HPE. Drawing on data from an ethnographic case study, this paper begins to provide some insights in further understanding the emerging disaffection towards HPE, and increasing attrition rates among Canadian boys. As illustrated in the study findings, this paper suggests that boys who disengage from HPE do so not because they are genetically predisposed to be lazy, or are unmotivated. Rather, their repeated experiences of explicit and symbolic abuse, degradation, and ignominy from teachers and peers alike dissuade them from active HPE participation. The findings of this study suggest the need for teachers to initiate a reflexive stance in their teaching practices, while concomitantly teaching students critical health literacy skills in an effort to meet the health and well-being needs of adolescent boys.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.856

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.008
Scholarly communication0.0050.002
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.058
GPT teacher head0.471
Teacher spread0.414 · 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

Citations49
Published2016
Admission routes2
Has abstractyes

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