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Record W2525507994 · doi:10.20360/g21w2h

Litteraties et creacollage numerique

2016· article· fr· W2525507994 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueLanguage and Literacy · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversité du Québec en Outaouais
FundersDepartment for Children, Schools and FamiliesUniversity of Ontario Institute of Technology
KeywordsMedicine

Abstract

fetched live from OpenAlex

Le présent article s’intéresse aux littératies numérique et informationnelle ainsi qu’aux liens qu’elles entretiennent avec le créacollage numérique. Le modèle de créacollage numérique présenté fait le rapprochement entre les compétences informationnelles, rédactionnelles et de référencement documentaire, expliquant comment les stratégies de créacollage numérique se retrouvent à toutes les étapes de la création d’un texte. L’article se termine par un plaidoyer pour la formation des élèves de tous les niveaux scolaires afin que ceux-ci puissent développer leurs habiletés liées aux littératies numérique et informationnelle ainsi que leurs stratégies de créacollage numérique pour apprendre à bien rédiger leurs travaux scolaires avec intégrité intellectuelle.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.333
Teacher spread0.321 · 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