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Record W2727381817

Aesthetics vs Entrepreneurialism: Artists' Careers, the Market and Models for Art Business

2017· dissertation· en· W2727381817 on OpenAlexaff
Hayley Dawson

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2017
Typedissertation
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsSchwartz/Reisman Emergency Medicine Institute
Fundersnot available
KeywordsThe artsScholarshipProfit (economics)Contemporary artCreative industriesAestheticsCultural economicsValue (mathematics)Art marketEntrepreneurshipArtBusiness modelRepresentation (politics)Art worldSociologyPolitical scienceVisual artsMarketingBusinessEconomicsComputer scienceNeoclassical economicsLaw
DOInot available

Abstract

fetched live from OpenAlex

This thesis investigates the contemporary art market in relation to the practices of working artists. The social mechanisms that determine artistic value influence the decisions and processes of all artists. Simultaneously, the economic structure of the art world is complex and perhaps challenging to navigate for those who are engaged in a creative practice. As a critique of the current economic systems that govern the art industry, two key questions are addressed through this research: How are financial and symbolic values attributed to art? How do profit-driven art institutions affect cultural production? Issues of artists’ rights, representation, and the feasibility of a career in the arts are also examined. By looking at commercially-oriented institutions such as auction companies in juxtaposition to the knowledge-based institutions of art scholarship, this thesis considers the theoretical and discursive logics at play in artists’ financial decision making and suggests options for combining aesthetics with entrepreneurialism.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0090.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.269
Teacher spread0.207 · 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 designNot applicable
Domainnot available
GenreOther

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 routes1
Has abstractyes

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