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Record W2738173863 · doi:10.18162/ritpu.2011.202

10.18162/ritpu.2011.202

2016· dataset· fr· W2738173863 on OpenAlexaff
Stéphane Allaire

Bibliographic record

Venuenot available
Typedataset
Languagefr
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Les communautés d’apprenants en réseau, incluant celles en formation initiale à l’enseignement, offrent un contexte propice à la réflexion sur l’action. Cette étude descriptive documente en quoi le discours asynchrone élaboré collectivement est réinvesti par les stagiaires en enseignement lorsqu’ils sont de retour en classe. Les variables de l’intervention en classe favorisant l’apprentissage des élèves ont servi de cadre de référence. La méthodologie combine des analyses qualitatives et quantitatives. Les résultats indiquent que les futurs enseignants estiment que les idées partagées au sein de la communauté en réseau aiguillent leur action en classe dans une proportion appréciable.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.802
Threshold uncertainty score0.661

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0040.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1980.498

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 head0.064
GPT teacher head0.414
Teacher spread0.350 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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