MétaCan
Menu
Back to cohort
Record W2272946665 · doi:10.3149/thy.0601.166

Boys, Bullying and Biopedagogies in Physical Education

2012· article· en· W2272946665 on OpenAlexaffabout
Michael Atkinson, Michael Kehler

Bibliographic record

VenueBoyhood Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsHumiliationMasculinityLiminalityHeterotopia (medicine)Gender studiesSociologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

There has been a dramatic rise in public, and particularly the media, attention directed at concerns regarding childhood obesity, and body shape/contents/images more broadly. Yet amidst the torrential call for increased attention on so-called “body epidemics” amongst youth in Canada and elsewhere, links between youth masculinities and bodily health (or simply, appearance) are largely unquestioned. Whilst there is a well-established literature on the relationship between, for example, body image and marginalized femininities, qualitative studies regarding boys and their body images (and how they are influenced within school settings) remain few and far between. In this paper, we offer insight into the dangerous and unsettled spaces of high school locker-rooms and other “gym zones” as contexts in which particular boys face ritual (and indeed, systematic) bullying and humiliation because their bodies (and their male selves) simply do not “measure up.” We draw on education, masculinities, health, and the sociology of bodies literature to examine how masculinity is policed by boys within gym settings as part of formal/informal institutional regimes of biopedagogy. Here, Foucault’s (1967) notion of heterotopia is drawn heavily upon in order to contextualize physical education class as a negotiated and resisted liminal zone for young boys on the fringes of accepted masculinities in school spaces.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.274

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 head0.111
GPT teacher head0.420
Teacher spread0.309 · 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 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

Citations24
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueBoyhood StudiesSame topicSports, Gender, and SocietyFrench-language works237,207