Littératie numérique, culture maker et bibliothèques : le futur de l'éducation
Bibliographic record
Abstract
The goal of this paper is to review the literature on knowledge creation of digital literacy in creative laboratories (LC) situated in libraries, with particular attention to the situation in Quebec. It aims to facilitate the dissemination of this knowledge among staff working in these spaces in order to contribute to the development of a new professional practice. The article consists of a review of the literature about the link between digital literacy and maker culture complemented by an analysis of collaborative knowledge creation practices used by the staff and the public in these spaces. This analysis helps deepen the reflection on the educational potential of LC, in particular in Quebec. Despite the existence of significant challenges to the emergence of unifying practices, Quebec libraries are particularly well positioned to play a central role in the development of digital literacy. L’objectif de cet article est de brosser un portrait de la littérature sur la création de connaissances en littératie numérique dans les laboratoires créatifs (LC) en bibliothèque en portant une attention particulière aux pratiques québécoises. Il vise à faciliter la diffusion de ces connaissances chez le personnel travaillant dans ces espaces afin de contribuer au développement d’une nouvelle pratique professionnelle en bibliothèque. L’article consiste en une revue de littérature portant sur l’intersection entre la littératie numérique et la culture maker complétée par une analyse des pratiques collaboratives de création de connaissances par le personnel et le public de ces espaces. Cette analyse permet d’approfondir une réflexion sur le potentiel éducatif des LC, en particulier au Québec. Malgré l’existence de défis importants à l’émergence de pratiques fédératrices, les bibliothèques québécoises sont particulièrement bien positionnées pour jouer un rôle central dans le développement de la littératie numérique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".