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Record W3025255710 · doi:10.1177/1757975920913547

Developing the culture of ethics in population health intervention research in Canada

2020· article· en· W3025255710 on OpenAlexaffabout
Anne-Marie Hamelin, Chantal Caux, Michel Désy, Anne Guichard, Samiratou Ouédraogo, Marie‐Claude Tremblay, Bilkis Vissandjée, Béatrice Godard

Bibliographic record

VenueGlobal Health Promotion · 2020
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversité LavalInstitut National de Santé Publique du QuébecUniversité de MontréalMcGill University
Fundersnot available
KeywordsEngineering ethicsResearch ethicsHealth equityEquity (law)SociologyPopulationPublic relationsEnvironmental ethicsPolitical scienceHealth careLawEngineering

Abstract

fetched live from OpenAlex

Population health intervention research (PHIR) is a particular field of health research that aims to generate knowledge that contributes to the sustainable improvement of population health by enabling the implementation of cross-sectoral solutions adapted to social realities. Despite the ethical issues that necessarily raise its social agenda, the ethics of PHIR is still not very formalized. Unresolved ethical challenges may limit its focus on health equity. This contribution aims to highlight some of these issues and calls on researchers to develop a culture of ethics in PHIR. Three complementary ways are proposed: to build an ethical concept specific to this field, to promote a shared space for critical reflection on PHIR ethics, and to develop the ethical competence in PHIR for which a preliminary framework is proposed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.590
GPT teacher head0.614
Teacher spread0.025 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2020
Admission routes2
Has abstractyes

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