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Record W2796279693 · doi:10.1177/2158244018768677

Medical Pluralism and the State: Regulatory Language Requirements for Traditional Acupuncturists in English-Dominant Diaspora Jurisdictions

2018· article· en· W2796279693 on OpenAlexaffabout
Nadine Ijaz, Heather Boon

Bibliographic record

VenueSAGE Open · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiasporaMultilingualismEquity (law)Public relationsLanguage policySociologyPluralism (philosophy)UnderpinningPublic policyMedicinePolitical scienceLawPedagogyGender studies

Abstract

fetched live from OpenAlex

Regulation of traditional acupuncturists has proven controversial in several jurisdictions. In this work, we detail and analyze the range of English-language registration, practice, and record-keeping requirements for regulated traditional acupuncturists across Canada, the United States, and Australia. Drawing on the results of an extensive documentary review and 28 qualitative interviews, we identify five primary themes underpinning policy-related discourses and debate: patient safety; standardized, integrated health care systems; economic considerations; traditional knowledge protection; and culturally inclusive care delivery. We critically examine these policy discourses, positioning them within a broader literature related to language policies in multiculturalist states and considering their relevance to the question of traditional medicine professional regulation in diaspora. With reference to the principle of regulatory equity, and to the concept of a pluralistic public, we present a set of recommendations for traditional medicine regulators contending simultaneously with clinical and cultural considerations.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.366
Teacher spread0.312 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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