MétaCan
Menu
Back to cohort
Record W3042212692 · doi:10.52358/mm.vi3.110

Recension : Rinaudo, J.-L. (2018). La téléprésence en formation. Londres : Éditions ISTE

2020· article· fr· W3042212692 on OpenAlexaffvenueabout
Matthieu Petit

Bibliographic record

VenueMédiations et médiatisations · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Dirigé par Jean-Luc Rinaudo, « La téléprésence en formation » découle de la tenue en 2017 d’un symposium ayant regroupé des chercheuses et chercheurs de quatre différents pays (France, Belgique, Suisse et Canada) lors des rencontres du Réseau international de recherche en éducation et formation (RÉF). Composé de neuf chapitres répartis selon trois thèmes, l’ouvrage repose sur différents travaux de recherche s’intéressant à la téléprésence, et offre ainsi un vaste panorama de ce sujet phare pour la formation en ligne

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)0.004
metaresearch head score (Gemma)0.017
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.098
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.006
Science and technology studies0.0040.003
Scholarly communication0.0090.008
Open science0.0020.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0980.040

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 head0.042
GPT teacher head0.334
Teacher spread0.292 · 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
GenreReview

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
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueMédiations et médiatisationsSame topicFrench Language Learning MethodsFrench-language works237,207