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Record W2761790367 · doi:10.1177/1532708617750177

Beyond Boundaries: The Development and Potential of Ethnography in the Study of Sport and Physical Culture

2018· article· en· W2761790367 on OpenAlexaff
Kass Gibson, Michael Atkinson

Bibliographic record

VenueCulture Studies &#x2194 Critical Methodologies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEthnographySociologyReflexivityDisciplinePhysical cultureHabitusContext (archaeology)PleasureAgency (philosophy)Critical ethnographyOriginalityPhysical educationEpistemologyGender studiesSocial scienceAnthropologyPedagogyQualitative researchPsychology

Abstract

fetched live from OpenAlex

Ethnographic approaches to the study of sport and physical culture have developed primarily within physical education and kinesiology programs and are typically framed in dialogue with sociological theorizing of agency, structure, power, and inequality. Beginning with reference to anthropology and sociology, we review the emergence, development, and subsequent transdisciplinary travels of ethnographic study of sport and physical culture. In doing so, we underscore the importance of theory, context, and disciplinary tradition in the development of sporting ethnographies. We then critically outline the place of ethnography in physical cultural studies (PCS). Rather than exhuming existing debates about the originality and uniqueness of the PCS enterprise, we highlight the need to decenter the hyper-reflexive researcher and advocate for the consideration of pleasure in ethnographic studies to achieve the interventionist goals PCS protagonists set themselves.

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)0.102
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.102
Threshold uncertainty score0.539

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1020.095
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.005
Science and technology studies0.0110.071
Scholarly communication0.0190.039
Open science0.0030.017
Research integrity0.0040.006
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 head0.140
GPT teacher head0.448
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations10
Published2018
Admission routes1
Has abstractyes

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