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Record W2605591536 · doi:10.7202/1039070ar

Ressources humaines : du mode hiérarchique au mode transversal et participatif, les bibliothèques sont-elles prêtes au changement ?

2017· article· fr· W2605591536 on OpenAlexvenueno aff
Jean‐Philippe Accart

Bibliographic record

VenueDocumentation et bibliothèques · 2017
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

À partir de trois études de cas (Bibliothèque nationale suisse, Faculté des sciences de l’Université de Genève, Bibliothèques et Archives de la Ville de Lausanne), il m’a été possible d’expérimenter trois manières de conduire des équipes et des projets de services, et donc des changements. Plusieurs constats peuvent en être tirés : le management participatif est bénéfique pour conduire des projets et des équipes vers le succès ; la démarche projet est un plus pour construire des équipes solides ; le leadership peut être partagé en se fondant sur la confiance réciproque. Dépendant fortement du contexte de travail, des compétences à disposition et des orientations stratégiques prises, le management par projet et le management transversal sont de réelles opportunités de développement pour les équipes.

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)0.012
metaresearch head score (Gemma)0.031
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 score0.040
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.023
Science and technology studies0.0090.012
Scholarly communication0.0270.024
Open science0.0020.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0240.004

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 head0.228
GPT teacher head0.410
Teacher spread0.183 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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