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Health, Promotion of

2018· other· en· W3082033365 on OpenAlexaff
Chantal Robillard

Bibliographic record

VenueThe International Encyclopedia of Anthropology · 2018
Typeother
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHealth promotionPublic healthSocial determinants of healthHealth equityHealth careInstitutionalisationHealth policyPolitical scienceMedicineEconomic growthSociologyEnvironmental healthNursing

Abstract

fetched live from OpenAlex

Advocating for health as a basic human right, health promotion focuses on sustaining health and wellbeing rather than on the prevention of risk and disease. In the 1970s it offered a potential response to growing public health concerns about increasing health disparities and, later on, to inequities in access to health care. Anthropology, more precisely ethnomedicine and medical anthropology, contributes to health promotion through the study of medical pluralism, power differentials between health systems, and the institutionalization of health inequities. Anthropologists continue to support health promotion by investigating the social determinants of health, coping and resilience strategies, and the potential of technology to reduce health inequities.

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)0.003
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.040
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0400.008

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 head0.052
GPT teacher head0.466
Teacher spread0.414 · 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
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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