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Record W2138671513 · doi:10.4000/ripes.374

Le mentorat en début de carrière : retombées sur la charge professorale et conditions de mise en œuvre d’un programme en milieu universitaire

2010· article· fr· W2138671513 on OpenAlexaff
Paul-Armand Bernatchez, Sylvie C. Cartier, Marilou Bélisle, Claire Bélanger

Bibliographic record

VenueRevue internationale de pédagogie de l’enseignement supérieur · 2010
Typearticle
Languagefr
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyPhysics

Abstract

fetched live from OpenAlex

Cette synthèse d’écrits a été menée dans le but de faire état des retombées du mentorat en milieu éducatif, plus précisément, le mentorat destiné aux enseignants universitaires en début de carrière et des conditions de mise en œuvre d’un programme. Les principaux constats tirés de cette synthèse montrent que la question du mentorat informel par rapport au mentorat formel reste sans réponse définitive quant à la supériorité d’une forme sur l’autre. De plus, en dépit des divergences de points de vue dans la littérature, il ressort que le mentorat joue un rôle positif dans le développement professionnel des nouveaux enseignants pour l’ensemble des fonctions composant leur charge professorale, incluant la fonction enseignement. Enfin, les expériences menées dans différents établissements nous permettent d’examiner des modalités d’implantation et de fonctionnement ainsi que de proposer un modèle de mentorat en trois étapes.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.310
Teacher spread0.286 · 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 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

Citations10
Published2010
Admission routes1
Has abstractyes

Explore more

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