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Record W4407083675 · doi:10.4000/1388m

L’accompagnement dans les métiers de l’éducation et de la formation : dispositifs, acteurs, contextes

2023· article· fr· W4407083675 on OpenAlexaff
Éric Maleyrot, Thérèse Perez‐Roux, Joséphine Mukamurera, Jean-François Desbıens, Andréanne Gagné

Bibliographic record

VenueQuestions vives recherches en éducation · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Pour Jean-Pierre Boutinet (2009), « l’accompagnement doit être abordé en termes culturels et anthropologiques, comme un signe des temps. Dans une société qui est de plus en plus une société de complexité, une société qui connaît des crises rémanentes depuis 15 ou 20 ans, l’adulte prend en pleine figure cette double instabilité et complexité » (p. 95). Pour Caroline Verzat (2012), « l’accompagnement s’inscrit dans une exigence plus large de notre époque post-moderne, celle de développer l’aut...

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.013
Scholarly communication0.0090.008
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.430
GPT teacher head0.548
Teacher spread0.117 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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