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Record W3157060653 · doi:10.24908/iqurcp.8286

Traditional Medicine vs. the Chinese Government

2016· article· en· W3157060653 on OpenAlexvenueno aff
Rozena Crossman

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsLegitimacyGlobeChinaGovernment (linguistics)PoliticsAsideSuperstitionModernization theoryPolitical scienceEnvironmental ethicsSocial scienceSociologyEpistemologyLawPsychologyHistoryPhilosophy

Abstract

fetched live from OpenAlex

This presentation investigates China’s policy towards traditional Chinese healing practices. The Chinese government’s policies are highly influenced by “Western” philosophy and ideals that are not always compatible with older aspects of Chinese culture, such as healing practices. (The term “Western” is put in quotations because while it refers to a euro‐centric culture, the idea of“west” varies depending upon one’s position on the globe.) China’s attitude towards traditional healing is indicative of a greater problem faced by most of today’s nations: in a world dominated by “Western”language and philosophy, holistic principles and practices tend to not only be misunderstood but completely shunted aside. By examining modern Chinese attitudes toward non‐scientific healing, this project intends to expose the flaws in the underlying logic of modern biomedicine—flaws common to both China and the West. The research is divided into five main categories: the origin and nature of traditional healing and healing cults; traditional healing as a religion; traditional healing as a science; “Western” influence on Chinese government; and, government definition and designation of superstition and cults. These five topics combined create a comprehensive understanding of traditional healing practices as well an understanding of their current political state. Within these categories, problems surrounding freedom of belief will naturally arise. Accompanying these problems will be the issues concerning legitimacy of traditional healing, and how “legitimacy” itself is defined—and who defines it.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.013
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.283
GPT teacher head0.514
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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