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Record W4410867449 · doi:10.1017/s0714980825000157

Perspectives de personnes aînées et de personnes employées à propos de leur communication et interaction en bibliothèque

2025· article· fr· W4410867449 on OpenAlexafffund
Marie‐Christine Hallé, Caroline Malo, Virginie Martel, Guylaine Le Dorze, Sophie Chesneau

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2025
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité de MontréalBibliothèque et Archives nationales du QuébecUniversité du Québec à Trois-Rivières
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La communication constitue un élément déterminant dans la participation sociale des personnes aînées. Or, les interactions entre ces dernières et le personnel d'institutions publiques, dont les bibliothèques, demeurent peu étudiées. Cette étude visait donc à identifier les composantes déterminantes de l'interaction entre les personnes aînées et le personnel de la bibliothèque. Des entrevues individuelles et de groupes ont été menées auprès de 10 personnes employées et de 19 personnes aînées avec et sans troubles cognitifs ou de communication, puis analysées qualitativement. Un modèle théorique représentant comment l'interaction en bibliothèque est influencée par des facteurs relatifs à la personne aînée (ex.: besoin d'interaction), la personne employée (ex.: stratégies de communication), l'environnement (ex.: achalandage) et la modalité (ex.: téléphone) a été développé. L'identification de ces facteurs pourra soutenir les bibliothèques dans l'adaptation de leurs modes de fonctionnement pour promouvoir la pleine participation sociale des personnes aînées.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.057
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0110.008
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.022
GPT teacher head0.335
Teacher spread0.313 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissement→Same topicAging, Elder Care, and Social Issues→French-language works237,207→