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L’innovation sociale ouverte comme stratégie de gestion de la baisse des subventions dans les organismes communautaires culturels

2017· article· fr· W2610470700 on OpenAlexaffvenueabout
Benjamin Houessou, Diane‐Gabrielle Tremblay

Bibliographic record

VenueInterventions économiques · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec en OutaouaisUniversité TÉLUQ
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Les organismes communautaires connaissent de plus en plus de difficultés financières de nos jours, entre autres, en raison de la diminution des subventions des financeurs publics ou privés. Dans ce contexte plusieurs de ces organismes abandonnent, modifient tout ou partie de leurs missions ou cherchent de nouvelles orientations. Face à cette problématique, la question principale qui guide notre recherche est la suivante : comment les organismes communautaires montréalais en lien avec leurs parties prenantes gèrent-ils la baisse de subventions ? Pour tenter de répondre à cette question, nous avons réalisé une recherche qualitative sur les orientations que prennent ces organismes dans ce contexte, et en particulier, sur ce que nous pouvons appeler l’émergence d’une orientation culturelle, créative ou artistique dans les organismes communautaires à Montréal. Les résultats montrent que l’innovation sociale ouverte est une stratégie majeure de gestion de la baisse des subventions dans ces organismes communautaires.

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)0.006
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.013
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.168
GPT teacher head0.402
Teacher spread0.234 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

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