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Record W4399082388 · doi:10.53967/cje-rce.5741

L’expérience d’étudiants universitaires ayant agi comme pairs aidants dans le cadre du programme Korsa

2024· article· fr· W4399082388 on OpenAlexaffvenue
Simon Grégoire, Gaëlle Saules, E.B.A. St. Cyr, Lise Lachance

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Au cours des dernières années, des établissements postsecondaires ont implanté des programmes de soutien par les pairs afin de promouvoir le mieux-être. Bien que des études aient évalué la portée de ces programmes auprès des aidés, peu de chercheurs se sont intéressés à l’expérience des étudiants qui œuvrent comme pairs aidants. Dans cette étude, l’équipe de recherche a mené un groupe de discussion et des entretiens semi-dirigés afin d’explorer l’expérience de 11 étudiants universitaires ayant agi comme pairs aidants dans le cadre d’un programme de soutien par les pairs offert dans 3 universités montréalaises. Les résultats permettent de mieux comprendre ce qui a motivé les pairs aidants à entreprendre ce programme, leurs inquiétudes, leur expérience, ce qu’ils ont apprécié et trouvé difficile, de même que les retombées qu’a eues le programme pour eux. Cette étude permet aussi de dégager certaines recommandations pour implanter un programme de soutien par les pairs en milieu postsecondaire.

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)0.008
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 score0.179
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0190.007
Scholarly communication0.0080.003
Open science0.0010.010
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0110.002

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 head0.051
GPT teacher head0.280
Teacher spread0.228 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

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