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Record W4390325291 · doi:10.3917/reru.165.1127b

Tremblay Diane-Gabrielle, Klein Juan-Luis et Fontan Jean-Marc (2015), Initiatives Locales et Développement socioterritorial , Québec, TÉLUQ, 2015, 388 p.

2016· article· fr· W4390325291 on OpenAlexaboutno aff
Patrick Mundler

Bibliographic record

VenueRevue d’Économie Régionale & Urbaine · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Au travers de l'analyse exploratoire, cette note de recherche examine comment les entreprises de la filière nautique bretonne perçoivent et évaluent les outils proposées par les acteurs politiques pour dynamiser leur territoire. À cette fin elle utilise des entretiens qualitatifs comportant une phase de codage et d'analyse. Elle procède à l'extraction d'hypothèses et réalise ensuite une étude quantitative des résultats du questionnaire fait auprès des entreprises de la filière. Les résultats indiquent que les entreprises de la filière nautique bretonne plébiscitent les stratégies de clusters et les actions incitatives indirectes mais semblent plutôt hostiles aux aides économiques directes. Il apparaît aussi que la multiplication des niveaux de décision lors de la mise en œuvre des politiques publiques est perçue comme un frein à l'efficacité. Toutes les entreprises ne perçoivent pas cependant les politiques de la même manière. Une typologie d'entreprise est proposée. Il y a les entreprises collaborantes, sceptiques et opportunistes. Ce résultat montre la complexité de l'évaluation des politiques publiques favorables à l'entrepreneuriat, car chaque groupe va utiliser les outils de dynamisation des territoires de manière différenciée.

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)0.002
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0080.003
Scholarly communication0.0070.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0380.007

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 head0.035
GPT teacher head0.311
Teacher spread0.276 · 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
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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