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Record W3204146128 · doi:10.7202/1081285ar

Implantation du programme Lanterne en milieux éducatifs : une analyse qualitative des perceptions des éducatrices en petite enfance

2021· article· fr· W3204146128 on OpenAlexaffvenue
Andréanne Fortin, M Julien, Martine Hébert, Jacinthe Dion, Mireille Cyr

Bibliographic record

VenueNouveaux cahiers de la recherche en éducation · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité de MontréalUniversité du Québec à ChicoutimiUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArtPsychology

Abstract

fetched live from OpenAlex

Le programme Lanterne vise à prévenir la violence sexuelle et s’adresse aux enfants d’âge préscolaire ainsi qu’aux adultes qui gravitent autour d’eux. Cette étude vise à recueillir 1) les perceptions des personnes éducatrices concernant l’utilisation des outils pédagogiques du programme auprès des enfants et 2) l’expérience subjective des personnes-ressources qui agissent à titre de Lanterne. Selon les personnes interrogées, les outils sont très appréciés des tout-petits et le programme est adapté à leur niveau développemental. Les personnes Lanterne ont aussi observé des retombées positives du programme sur leur pratique professionnelle, elles rapportent notamment accorder un plus grand respect à l’intimité des jeunes enfants. Finalement, les données recueillies permettent d’offrir des recommandations en vue d’assurer la pérennité du 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 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)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.151
GPT teacher head0.481
Teacher spread0.329 · 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 designQualitative
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

Citations0
Published2021
Admission routes2
Has abstractyes

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