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Record W4313656373 · doi:10.4000/bssg.1188

Appréhender les usages d’une institution culturelle. Entretien avec Christophe Evans, responsable du service Études et recherche de la Bibliothèque publique d’information

2022· article· fr· W4313656373 on OpenAlexaff
Cécile Barth-Rabot, Christophe Evans

Bibliographic record

VenueBiens Symboliques / Symbolic Goods · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsHumanitiesPublicsPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet entretien avec Christophe Evans, sociologue, porte sur la possibilité pour les institutions culturelles de produire par elles-mêmes des connaissances sur leurs publics, à partir du cas singulier de la Bibliothèque publique d’information (Bpi) du Centre Pompidou. Cet établissement national de lecture publique situé au centre de Paris a été doté, dès sa création à la fin des années 1970, d’un service Études et recherche, dont Christophe Evans est aujourd’hui responsable. Ce service fait de la Bpi un lieu inédit d’expérimentation et d’observation des publics des bibliothèques, mais aussi de réflexion sur ce que signifie, pour une institution, tenter d’appréhender ses usagers. Observatoire in situ mobilisant plusieurs disciplines, il enrichit les savoirs en matière de pratiques de lecture et d’usages des bibliothèques autant qu’il démontre l’intérêt des sciences sociales pour l’action publique.

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)0.009
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0140.031
Scholarly communication0.0160.022
Open science0.0010.007
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0060.001

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 head0.173
GPT teacher head0.433
Teacher spread0.260 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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