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Record W2945995018 · doi:10.3917/enic.022.0061

L’offre de services des espaces numériques de la Bibliothèque municipale de Lyon : étude de cas

2018· article· fr· W2945995018 on OpenAlexaff
Talal Zouhri, Mabrouka El Hachani

Bibliographic record

VenueLes Enjeux de l information et de la communication · 2018
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Résumé Les bibliothèques de lecture publique participent-elles au développement de la culture numérique de leurs usagers ? Pour répondre à cette question, cet article examine un ensemble de services proposés aux usagers par les espaces numériques du réseau de la Bibliothèque municipale de Lyon (BmL). L'ensemble de ces services prend en compte leur âge et leur niveau de maîtrise de l'outil informatique. Deux types de démarches pour l’apprentissage informel sont identifiés. Le premier est l'accompagnement, à travers la mise en place d’ateliers numériques appuyés par une restitution-trace à travers le blog, une forme de mémo pour ceux ayant suivi les ateliers et une forme de valorisation de ce service pour les autres internautes. Le second vise à développer l’autonomie des usagers. Ce second type de démarche se déploie à travers la mise à disposition d’outils d’autoformation et des ressources documentaires comme support pédagogique. La médiation est présente comme un élément central autour duquel se construit l'ensemble des services des espaces numériques examinés.

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)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.015
Science and technology studies0.0060.003
Scholarly communication0.0090.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.003

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 head0.086
GPT teacher head0.351
Teacher spread0.265 · 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 designQualitative
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
Published2018
Admission routes1
Has abstractyes

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