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Record W61026050 · doi:10.71781/17944

Évaluation d’implantation d’un programme de transfert de connaissances par agents multiplicateurs pour la prévention des mauvais traitements chez les jeunes enfants

2010· dissertation· fr· W61026050 on OpenAlexaboutno aff
Mélodie Briand-Lamarche

Bibliographic record

VenuePapyrus : Institutional Repository (Université de Montréal) · 2010
Typedissertation
Languagefr
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyNursingHumanitiesMedicine

Abstract

fetched live from OpenAlex

L’étude des pratiques de prévention en santé publique laisse voir que les innovations basées sur des données probantes ne sont pas toujours les plus utilisées (Ringwalt et al. 2002, Wandersman et Florin 2003). Dans la volonté de mettre de l’avant non seulement une innovation basée sur des données probantes, mais aussi une innovation réellement utile à la communauté que le Centre de liaison sur l’intervention et la prévention psychosociale (CLIPP) a mis sur pied en 2006 le programme de formation par agents multiplicateurs «Agir en milieu de garde» ayant pour principal objectif la prévention des mauvais traitements chez les jeunes enfants. La présente étude vise à décrire l’implantation de ce programme dans les services de garde en milieu familial du Québec et à examiner les processus qui ont influencé cette implantation. Les résultats exposent le niveau d’implantation sur deux plans : le dosage et la fidélité. L’étude des processus d’implantation permet de documenter l’influence sur le niveau d’implantation de quatre types de facteurs : individuels, organisationnels, communautaires et propres à l’innovation ainsi que l’influence des interactions entre ces différents facteurs.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0190.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.002
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 head0.043
GPT teacher head0.296
Teacher spread0.253 · 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.

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

Citations1
Published2010
Admission routes1
Has abstractyes

Explore more

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