MétaCan
Menu
Back to cohort
Record W4377084353 · doi:10.7202/1096848ar

Le programme de prévention Fluppy : historique, contenu et diffusion au Québec

2023· article· fr· W4377084353 on OpenAlexaffvenueabout
France Capuano, François Poulin, Frank Vitaro, Pierrette Verlaan, Isabelle Vinet

Bibliographic record

VenueRevue de psychoéducation · 2023
Typearticle
Languagefr
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité de SherbrookeUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Fluppy est un programme de prévention de la violence et du décrochage scolaire destiné aux enfants de la maternelle. Ce programme combine des interventions universelles et ciblées qui sont implantées en milieu scolaire auprès des élèves et des enseignantes et en milieu familial auprès des parents. Il a été créé en 1990 et est largement diffusé au Québec et connu dans plusieurs pays. Cet article trace l’historique et les origines du programme, présente une description détaillée des interventions et rapporte les résultats d’une enquête portant sur sa diffusion et ses conditions d’implantation au Québec depuis 1990. Cette enquête révèle que le programme a été diffusé et implanté dans toutes les régions du Québec. Certaines régions ont mis en place une structure permettant d’implanter le programme tel que prescrit par les concepteurs. Dans plusieurs milieux, le programme est implanté de façon très partielle et seul le volet universel est administré. Enfin, l’intensité de l’intervention tant auprès des enfants que des parents, est plus faible que ce qui est proposé par les concepteurs et les diffuseurs. La discussion porte sur les conséquences possibles du non respect des conditions d’implantation de ce programme de prévention.

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)0.004
metaresearch head score (Gemma)0.010
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.047
GPT teacher head0.347
Teacher spread0.300 · 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
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

Citations6
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueRevue de psychoéducationSame topicChild Abuse and TraumaFrench-language works237,207