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Record W2079461567 · doi:10.1080/09548963.2011.563907

Independent artist-run centres: an empirical analysis of the Montreal non-profit visual arts field

2011· article· en· W2079461567 on OpenAlexaffabout
Giorgio Tavano Blessi, Pier Luigi Sacco, Thomas Pilati

Bibliographic record

VenueCultural Trends · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversité TÉLUQUniversité du Québec à Montréal
Fundersnot available
KeywordsThe artsEmpirical researchProfit (economics)Performing artsField (mathematics)Relevance (law)SociologyArts administrationPublic relationsMarketingVisual artsPolitical scienceBusinessEconomicsLawArtArts in education

Abstract

fetched live from OpenAlex

Canadian independent artist-run centres provide an interesting case study of the potential role and relevance of non-profit institutions in the contemporary arts field. Predominantly established during the 1970s, they have been founded by artist collectives typically operating within urban contexts, with the aim of providing new opportunities to cope with the physical, economic and cultural constraints that generally impede the professional development of artists. A remarkable urban environment in which it is possible to find, and study, a large number of such organizations is the city of Montreal, in the Quebec Province of Canada, which constitutes an excellent reference to track the onset and the evolution of independent artist-run spaces, and to understand why, how and to what extent they are currently experiencing new pressures and challenges, both on the internal and external sides. This article offers an empirical study of these organizations with reference to their organizational, managerial and strategic vision, and to co-operative interaction and network building practices. It contributes to the field of research on cultural management through its study of the effects of management systems on the strategic action of independent visual arts organizations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.107
GPT teacher head0.369
Teacher spread0.263 · 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 teacher head, not a consensus.

Study designObservational
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

Citations19
Published2011
Admission routes2
Has abstractyes

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