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Record W4395036697 · doi:10.59876/a-6x5r-0fdq

Accompagner l’entreprenance (artistique) : une nouvelle quête ?

2024· article· en· W4395036697 on OpenAlexvenueno aff
Sandrine Émin, Nathalie Schieb-Bienfait

Bibliographic record

VenueManagement international · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipScope (computer science)Perspective (graphical)SociologyModalitiesProcess (computing)Work (physics)EpistemologyVisual artsComputer scienceArtSocial sciencePolitical sciencePhilosophyEngineeringLaw

Abstract

fetched live from OpenAlex

This article deals with artistic entrepreneurship from a process-relational perspective. The authors explore via a literature review the singularity of the entrepreneurial process of artists. Then, they examine the modalities of a renewed accompaniment to support it. Methodologically, the data were collected through observations and interviews with emerging performing artists and structures offering support programs to artists. Five support programs have been closely studied. The contributions of the research are twofold. Theoretically, the authors define the concept of artistic entrepreneurship, that is based on three dimensions : entrepreneurial work, hybrid entrepreneurship, serial entrepreneurship. From a managerial point of view, artistic entrepreneurship questions the scope, actors and nature of traditional entrepreneurial support.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.010
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.009
Scholarly communication0.0100.008
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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