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Record W2154463601 · doi:10.1123/ssj.19.4.370

Moving beyond the Biomedical: The Use of Physical Activity to Negotiate Illness

2002· article· en· W2154463601 on OpenAlexaff
James Gillett, Roy Cain, Dorothy Pawluch

Bibliographic record

VenueSociology of Sport Journal · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsNegotiationSociology of health and illnessPhysical activityValue (mathematics)PoliticsSociologyPhysical culturePsychologyEpistemologySocial scienceHealth careAlternative medicineMedicinePolitical science

Abstract

fetched live from OpenAlex

Despite the growing interest in the therapeutic value of sport, limited attention has been devoted to understanding the meanings that individuals attribute to their use of physical activity as a complementary therapy. In our analysis, we draw on literature in the sociology of lay knowledge in order to better understand the use of physical activity as a health practice among people with HIV/AIDS. Our objective is to move beyond a biomedical focus, and explore the social, cultural, and political dimensions of using sport and physical activity to negotiate illness. The themes that emerge illustrate the diverse significance of physical activity as a complementary approach to health. Our analysis indicates that research in the sociology of sport can make an important contribution to understanding the therapeutics of physical activity and sport for people with health problems.

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)0.008
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0070.068
Scholarly communication0.0090.007
Open science0.0010.009
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.079
GPT teacher head0.338
Teacher spread0.259 · 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

Citations7
Published2002
Admission routes1
Has abstractyes

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