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Moving forward? Complementary and alternative practitioners seeking self‐regulation

2004· article· en· W1972313015 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSociology of Health & Illness · 2004
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsInstitute of AgingUniversity of Toronto
Fundersnot available
KeywordsLegitimacyGovernment (linguistics)Public relationsInclusion (mineral)Statutory lawAlternative medicineMedical educationSociologyPsychologyPolitical scienceMedicineLawSocial science

Abstract

fetched live from OpenAlex

Complementary and alternative medicine (CAM) occupations continue to struggle towards achieving professional status, especially in the form of statutory regulation. Many consider professional status a worthwhile goal for CAM occupations, yet it is a process fraught with tensions. In this paper we present in-depth interview data from the leaders of three CAM groups (naturopaths, traditional Chinese medicine practitioners acupuncturists, and homeopaths) in Ontario, Canada that demonstrate four main strategies used by these groups to professionalize. The strategies discussed are related to how the knowledge base of each group is organised and transmitted. These strategies include: improving educational standards, improving practice standards, engaging in peer-reviewed research and increasing group cohesion. At the core of these strategies is the demarcation of who is qualified to practice, and a signalling to 'outsiders', such as medicine and the government, that practitioners are qualified and legitimate. Across the three groups, the leaders referred to the inclusion of medical science as a basis for distinguishing between 'science' and 'non-science' as well as who should practice and who should not. We highlight how internal battles over the infusion of medical science into the knowledge base are part of the process for establishing legitimacy for the three CAM groups in our study. We end with a brief discussion of the implications of these internal battles over medical science knowledge for the future of CAM groups.

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.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.298
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.036
GPT teacher head0.365
Teacher spread0.329 · 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