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Record W4415432076 · doi:10.7202/1119353ar

Évaluation émancipatrice des besoins de formation des formateur·rice·s de terrain belges francophones

2024· article· fr· W4415432076 on OpenAlexaffvenue
Christophe Baco, Antoine Derobertmasure, Marie Bocquillon, Marc Demeuse

Bibliographic record

VenueRevue des sciences de l éducation · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicEducational Practices and Policies
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsTerrainRegional studiesRaised-relief map

Abstract

fetched live from OpenAlex

L’article présente une analyse des besoins de formation des formateur·rice·s de terrain belges francophones. Un questionnaire construit à partir d’un référentiel de formation, complété par 854 personnes, visait à évaluer l’écart (donc le besoin de formation) entre la maitrise actuelle et la maitrise désirée de diverses compétences nécessaires à l’accompagnement de stagiaires. Pour la plupart des compétences, les résultats du questionnaire révèlent que les personnes chargées de la formation de terrain éprouvent des besoins non prioritaires ou des besoins prioritaires de formation. Ces résultats peuvent servir à proposer des pistes pour leur formation et permettent de prendre du recul par rapport aux objectifs du législateur.

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)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.790

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.397
GPT teacher head0.464
Teacher spread0.067 · 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

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