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Record W3042104566 · doi:10.18103/mra.v6i5.1750

How Holistic is Complementary and Alternative Med-icine (CAM)? Examining Self-Responsibilization in CAM and Biomedicine in a Neoliberal Age

2018· article· en· W3042104566 on OpenAlexaff
Ana Ning

Bibliographic record

VenueMedical Research Archives · 2018
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsBiomedicineIndividualismHolismSociologyHealth careChiropracticAlternative medicineHolistic healthEpistemologySocial scienceEngineering ethicsMedicinePolitical scienceLawEngineeringPhilosophy

Abstract

fetched live from OpenAlex

This review paper adds to recent social science interrogation of common boundaries between CAM (complementary and alternative medicine) and biomedicine, by examining an unquestioned dichotomy often ascribed to them: holism vs. individualism. Drawing from social scientific literature review, this paper draws attention to the individualistic focus of CAM by situating contemporary CAM developments within a neoliberal climate that emphasizes individual responsibility for health care. Focusing on the individualistic features of CAM helps rethink commonly held assumptions regarding the holistic features of CAM, which tend to gain the most attention in popular and scholarly representations of CAM as distinct from biomedicine. As well, the individualistic features of CAM shed light on the significant role of CAM in health care as a form of individual consumptive choice rather than as a collective responsibility on the part of the state to complement national health care systems.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.027
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.195
GPT teacher head0.460
Teacher spread0.266 · 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.

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

Citations9
Published2018
Admission routes1
Has abstractyes

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