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Record W2972974330 · doi:10.3138/cbmh.330-022019

Politics Ahead of Patients: The Battle between Medical and Chiropractic Professional Associations over the Inclusion of Chiropractic in the American Medicare System

2019· article· en· W2972974330 on OpenAlexvenueno aff
Kenneth J. Young

Bibliographic record

VenueCanadian Journal of Health History · 2019
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsChiropracticCompromiseInclusion (mineral)Health carePoliticsLegislatureMedicineHarmBattlePublic relationsLegislationValue (mathematics)IndoctrinationPolitical scienceMisinformationProfessional associationParliamentLegitimacyLawAlternative medicinePsychologyIdeologySocial psychology

Abstract

fetched live from OpenAlex

Health care professions struggling for legitimacy, recognition, and market share can become disoriented to their priorities. Health care practitioners are expected to put the interests of patients first. Professional associations represent the interests of their members. So when a professional association is composed of health care practitioners, its interests may differ from those of patients, creating a conflict for members. In addition, sometimes practitioners' perspectives may be altered by indoctrination in a belief system, or misinformation, so that a practitioner could be confused about the reality of patient needs. Politicians, in attempting to find an expedient compromise, can value a "win" in the legislative arena over the effects of that legislation. These forces all figure into the events that led to the acceptance of chiropractic into the American Medicare system. Two health care systems in a political fight lost sight of their main purpose: to provide care to patients without doing harm.

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)0.017
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0370.036
Scholarly communication0.0170.006
Open science0.0010.006
Research integrity0.0140.019
Insufficient payload (model declined to judge)0.0050.001

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 head0.057
GPT teacher head0.416
Teacher spread0.360 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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