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Record W2139595451 · doi:10.7202/1032808ar

Les techniques de la documentation : un programme de formation collégiale en évolution

2015· article· fr· W2139595451 on OpenAlexaffvenue
Stéphane Ratté

Bibliographic record

VenueDocumentation et bibliothèques · 2015
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsCollège de Maisonneuve
Fundersnot available
KeywordsHumanitiesDocumentationPolitical scienceLibrary scienceArtComputer science

Abstract

fetched live from OpenAlex

Afin de maintenir la pertinence des contenus enseignés et d’assurer l’adéquation aux besoins du marché du travail, un projet d’actualisation locale du programme Techniques de la documentation a été lancé en 2014 au Collège de Maisonneuve. Dans le cadre de ce projet, le département a identifié plusieurs défis. Ces défis s’articulent autour de sept grands axes : le traitement documentaire, les services au public, la gestion des documents administratifs, les systèmes documentaires informatisés, la gestion de projet, les attitudes professionnelles et les stages. Cet article propose un survol général de ces défis et dresse un portrait de la réalité du programme Techniques de la documentation. Il contribue également à une meilleure compréhension des compétences attendues du futur technicien en documentation.

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)0.027
metaresearch head score (Gemma)0.048
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0070.007
Scholarly communication0.0150.010
Open science0.0030.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0160.005

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 head0.157
GPT teacher head0.383
Teacher spread0.226 · 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
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

Citations1
Published2015
Admission routes2
Has abstractyes

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