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Record W4364376467 · doi:10.25035/jade.05.01.01

The Production of Docility in Professional Ice Hockey

2023· article· en· W4364376467 on OpenAlexaff
Andre Andrijiw, Luke Jones

Bibliographic record

VenueJournal of Athlete Development and Experience · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIce hockeyDeviance (statistics)DisciplineConformityGeneral partnershipPower (physics)SociologyAthletesPsychologyPolitical scienceSocial psychologySocial scienceLawMedicine

Abstract

fetched live from OpenAlex

The social relations and practices that imbue the sport of ice hockey have prompted several limiting and problematic outcomes for athletes. Concerned by such outcomes, and informed by the anatomo-politics of French poststructuralist philosopher Michel Foucault (1991), an examination into the relations of power that govern North American professional ice hockey was undertaken. The examination revealed that athletes were routinely subject to disciplinary power and a commonplace set of practices that closely resemble Foucault’s (1991) ‘means of correct training’: managers, in partnership with coaches under their remit, choreographed and engaged in constant supervision (e.g., scouting and monitoring), organized highly ritualized examinations (e.g., combines, training camps), rewarded conformity (e.g., contractual benefits), and punished deviance (e.g., inter- and intra-team reassignments). These practices were additionally undergirded by clearly identifiable panoptic arrangements that stretched across the athletic lifespan. Ultimately, the observed workings of disciplinary power served not the development of a whole individual, but rather the production of docility.

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)0.001
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0040.001
Open science0.0000.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.331
Teacher spread0.288 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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