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Record W2787951237 · doi:10.3917/spub.176.0821

Développement d’un cours francophone en ligne sur les politiques publiques en santé : une collaboration internationale

2018· article· fr· W2787951237 on OpenAlexaff
Réjean Hébert, Yves Coppieters, Christian Pradier, Bryn Williams–Jones, Cora Brahimi, Céline Farley

Bibliographic record

VenueSanté Publique · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsÉcole Nationale d'Administration PubliqueUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

OBJECTIVE: To present the process and challenges of developing an online competency-based course on public health policy using a collaborative international approach. METHODS: Five public health experts, supported by an expert in educational technology, adopted a rigorous approach to the development of the course: a needs analysis, identification of objectives and competencies, development of a pedagogical scenario for each module and target, choice of teaching methods and learning activities, material to be identified or developed, and the responsibilities and tasks involved. RESULTS: The 2-credit (90-hour) graduate course consists of six modules including an integration module. The modules start with a variety of case studies: tobacco law (neutral packaging), supervised injection sites, housing, integrated services for the frail elderly, a prevention programme for mothers from disadvantaged backgrounds, and the obligatory use of bicycle helmets. In modules 1, 3, 4 and 5, students learn about different stages of the public policy development process: emergence, formulation and adoption, implementation and evaluation. Module 2 focuses on the importance of values and ideologies in public policy. The integration module allows the students to apply the knowledge learned and addresses the role of experts in public policy and ethical considerations. CONCLUSION: The course has been integrated into the graduate programmes of the participating universities and allows students to follow, at a distance, an innovative training programme.

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)0.010
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.629
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.048
GPT teacher head0.434
Teacher spread0.386 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2018
Admission routes1
Has abstractyes

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