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Record W3119846092 · doi:10.1123/ssj.2020-0038

The Nature of the Body in Sport and Physical Culture: From Bodies and Environments to Ecological Embodiment

2020· article· en· W3119846092 on OpenAlexaff
Samantha King, Gavin Weedon

Bibliographic record

VenueSociology of Sport Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsQueen's University
Fundersnot available
KeywordsSensibilityMateriality (auditing)Physical cultureConstitutionSociologyGenerative grammarAestheticsEcologyEpistemologyEnvironmental ethicsPsychologyPolitical scienceArtLawPhilosophyComputer scienceBiologyMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

This article raises the ecological substance and relational co-constitution of bodies as a generative question for sociologists of sport and physical culture. It proceeds from our observation that recent research on the materiality of athletic bodies, and on the environmental issues in which sport is implicated, tends to run on parallel tracks. By exploring how biological, environmental, and social natures cohere in the making and unmaking of healthy bodies, our aim is to connect and extend these vibrant areas of research. We do so by developing the concept of “ecological embodiment,” a descriptor for a fluid state of becoming and a sensibility for thinking about hierarchical socioecological entanglements. To illustrate this concept, we draw on a study of whey protein powder, a key ingredient in contemporary fitness cultures.

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)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.046
Scholarly communication0.0070.006
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.289
Teacher spread0.277 · 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
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
Published2020
Admission routes1
Has abstractyes

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