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Record W4403477145 · doi:10.1136/bmjsem-2024-002170

Finding a way in and making it stick: an exploration of chiropractor experiences working in team-oriented elite sport practice settings

2024· article· en· W4403477145 on OpenAlexaff
Corrie Myburgh, Alexander D Lee, Mohsen Kazemi, Samuel J. Howarth, Jacob Hill, Silvano Mior

Bibliographic record

VenueBMJ Open Sport & Exercise Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsEliteElite athletesPsychologyEngineering ethicsApplied psychologyEngineeringAthletesMedicinePolitical sciencePhysical therapy

Abstract

fetched live from OpenAlex

Interprofessional healthcare teams have become the benchmark for optimising athlete health and performance in high-stakes sports. Despite a history of utility as provider partners, chiropractors are currently a relatively underutilised human resource in this rapidly developing and challenging field. Consequently, our study explored the global experiences and distinct perspectives of elite-level career sports chiropractors. Through a qualitative explorative single case study, we purposively sampled and interviewed 15 chiropractors active in elite-level athletic contexts. ‘ Professional characteristics and competencies’, ‘Running the gamut of professional career development’ and ‘Navigating team development in a small organisational structure’ emerged as the three key themes from the data. Our data indicate that chiropractors gain provider as members of the elite athletic health and performance management team as multirole manual medicine practitioners. However, thriving in a team-oriented practice, this context appears to be reliant on their capacity for development as part of a small organisational group.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.058
GPT teacher head0.419
Teacher spread0.361 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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