MétaCan
Menu
Back to cohort
Record W2976959208 · doi:10.3917/raised.023.0177

Verbalisations écrites dans l’alternance : des traces explicites aux indicateurs plus implicites de développement professionnel

2019· article· fr· W2976959208 on OpenAlexaff
Kristine Balslev, Sandra Pellanda Dieci, Walther Tessaro

Bibliographic record

VenueRaisons éducatives · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsAssociation Québécoise des Enseignantes et des Enseignants du Primaire
Fundersnot available
KeywordsHumanitiesArtSociology

Abstract

fetched live from OpenAlex

Dans les formations à l’enseignement, les verbalisations écrites constituent autant des instruments au service du développement professionnel que des moyens pour les formés de montrer ce développement. Ainsi ces verbalisations contiennent à la fois les traces de développement que les étudiants choisissent de montrer et des indicateurs plus implicites accessibles par une analyse discursive de ces verbalisations. Cet article présente les particularités de l’écriture réflexive et les caractéristiques de deux dispositifs d’écriture réflexive destinés respectivement aux enseignants du primaire et du secondaire. Il analyse ces verbalisations écrites selon les deux niveaux de lecture et met en évidence qu’un grand nombre d’étudiants relate des actions régulées mais pas de conceptions ni de valeurs. Il s’attarde ensuite sur des indicateurs de développement professionnel révélés par une analyse discursive.

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)0.035
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
Metaresearch0.0070.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.009
Scholarly communication0.0050.007
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.406
GPT teacher head0.508
Teacher spread0.102 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueRaisons éducativesSame topicEducation, sociology, and vocational trainingFrench-language works237,207