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The integration of chiropractors into healthcare teams: a case study from sport medicine

2007· article· en· W2058968542 on OpenAlexafffund
Nancy Théberge

Bibliographic record

VenueSociology of Health & Illness · 2007
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsChiropracticAmateurScope of practiceContext (archaeology)Health careSports medicineScope (computer science)DisciplineInclusion (mineral)Medical educationAlternative medicineAthletesMedicinePublic relationsPsychologyPhysical therapyPolitical scienceSociologySocial science

Abstract

fetched live from OpenAlex

This article examines the integration of chiropractors into multi-disciplinary healthcare teams in the specialisation of sport medicine. Sport medicine is practised in a number of contexts in professional and amateur sport. The current analysis focuses on the highest levels of amateur sport, as exemplified by the Olympics. Data are taken from interviews with 35 health professionals, including physicians, physiotherapists, athletic therapists and chiropractors. A defining feature of sport medicine is an emphasis on performance, which is the basis for a client-centred model of practice. These two elements have provided the main grounds for the inclusion of chiropractic in sport medicine. While the common understanding that 'athletes wanted them' has helped to secure a position for chiropractic within the system of sport medicine professions, this position is marked by ongoing tensions with other professions over the scope and content of practice, and the nature of the patient-practitioner relationship. In the context of these tensions, chiropractors' success in achieving acceptance on sport medicine teams is contingent on two factors: (a) reduced scope of practice in which they work primarily as manual therapists; and (b) the exemplary performance of individual practitioners who 'fit' into multi-disciplinary sport medicine teams.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.398
Teacher spread0.371 · 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 designObservational
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

Citations66
Published2007
Admission routes2
Has abstractyes

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