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Record W2146639938 · doi:10.1080/13573322.2011.608942

‘Thrash yourself Thursday’: the production of the ‘healthy’ child through a fitness-based PE practice

2011· article· en· W2146639938 on OpenAlexaffabout
Lisa McDermott

Bibliographic record

VenueSport Education and Society · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsThursdayAccountabilityPublic relationsGovernment (linguistics)Power (physics)SociologyPedagogyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Saturating the Canadian landscape are media and health industry discourses representing childhood physical ‘(in)activity’ and ‘obesity’ as being at ‘epidemic’ proportion. Increasingly identified as a focus of concern within such representations is the school setting, simultaneously positioned both as a cause of and a key institutional site for redressing these ‘pathologies’. Drawing on qualitative research carried out at a Canadian elementary school, this discussion offers a Foucaultian governmental analysis of one school's navigation of this gauntlet of accountability to improve children's health. Specifically, the school-wide fitness-based initiative known as ‘Thrash yourself Thursdays’, whose objective is the production of ‘healthy’ students, is examined to understand the power relations enacted through it, and how the target of this practice (i.e. the children) negotiated such efforts to shape their bodily conduct. This in turn, offers a unique contribution to the governmental literature, which is more characterised by attending to discourses and strategies of government rather than how the subjects of such strategies respond to such efforts.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.043
GPT teacher head0.351
Teacher spread0.308 · 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

Citations19
Published2011
Admission routes2
Has abstractyes

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