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Record W2593364154 · doi:10.24095/hpcdp.37.1.04f

Lettre à la rédaction - À qui profite la professionnalisation de la promotion de la santé?

2017· article· fr· W2593364154 on OpenAlexaffvenueabout
J. Ross Graham

Bibliographic record

VenuePromotion de la santé et prévention des maladies chroniques au Canada · 2017
Typearticle
Languagefr
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsUniversity of British ColumbiaIsland Health
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

En 2007, Health Promotion Ontario (HPO) a entrepris de faire progresser la « profession » de praticien en promotion de la santé (PS) au Canada en établissant des compétences nationales à l’intention des promoteurs de la santé. Ce travail a été poursuivi par le Réseau pancanadien pour les compétences des promoteurs de la santé (« le Réseau »). Avec le financement de l’Agence de la santé publique du Canada, le Réseau a eu pour mandat, premièrement, de donner suite à la recommandation formulée par le Groupe de travail conjoint sur les ressources humaines en santé publique à propos des compétences spécifiques (notamment pour les « spécialistes de la promotion de la santé ») et, deuxièmement, de lutter contre la marginalisation que subissent les promoteurs de la santé dans l’exercice de leurs fonctions. Les compétences des promoteurs de la santé en vigueur actuellement ont été publiées en novembre 2015, à la suite d’une série de revues de la littérature et de consultations auprès de praticiens.

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)0.015
metaresearch head score (Gemma)0.024
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: Editorial · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0090.019
Scholarly communication0.0120.008
Open science0.0020.006
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0190.004

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 head0.034
GPT teacher head0.433
Teacher spread0.399 · 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
GenreEditorial

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
Published2017
Admission routes3
Has abstractyes

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