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Record W2243686031 · doi:10.7202/1030023ar

Vers une meilleure compréhension des besoins informationnels des cadres intermédiaires municipaux. Premières pistes de réflexion

2015· article· fr· W2243686031 on OpenAlexaffvenue
Dominique Maurel, Pierrette Bergeron

Bibliographic record

VenueDocumentation et bibliothèques · 2015
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCompetitive and Knowledge Intelligence
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La capacité des organisations à créer et à exploiter l’information et les connaissances est déterminée entre autres par les comportements informationnels des acteurs organisationnels. Chargés de décisions stratégiques, tactiques et opérationnelles, les cadres intermédiaires sont au coeur du processus de création des connaissances, et leurs comportements informationnels doivent être soutenus par des sources et des systèmes d’information. Cet article examine la manière dont des cadres intermédiaires municipaux répondent à leurs besoins informationnels dans le contexte de leurs activités de gestion. Nous souhaitons notamment contribuer à fournir des pistes de réflexion pour l’élaboration de stratégies de gestion de l’information organisationnelle.

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)0.004
metaresearch head score (Gemma)0.015
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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.009
Science and technology studies0.0030.004
Scholarly communication0.0110.010
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.003

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 head0.051
GPT teacher head0.326
Teacher spread0.275 · 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
Published2015
Admission routes2
Has abstractyes

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