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Record W2767131573 · doi:10.18357/tar81201716809

The Barbizon School (1830-1870): Expanding the Landscape of the Modern Art Market

2017· article· en· W2767131573 on OpenAlexaffvenue
Lorinda Christine Fraser

Bibliographic record

VenueThe Arbutus Review · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsArt marketIdealizationPaintingGlobeModern artSubject (documents)Visual artsContemporary artArtAbstract artArt historyPerformance artPsychologyLibrary scienceComputer science

Abstract

fetched live from OpenAlex

During the 1830s to the 1870s, a cohort of French artists developed new approaches to landscape painting and became known collectively as the Barbizon School. This informal group of artists were proponents of an innovative way of painting in which nature was the central subject of their artworks. Moreover, nature was depicted without the classical idealization or polished refinement required by the French Academy at the time. Barbizon artists were also the catalysts for changes in how art was sold during the 19th century, paving the way for an open art market system that spread across the globe and continues unchanged to this day. Using Jean-Baptiste-Camille Corot (1796-1875) as a case study, I establish the ways in which the Barbizon School forged new stylistic and economic possibilities for later modern art movements, most prominently Impressionism, outside the purview of the French Academy. I also highlight the ways in which the Barbizon artists and their supporters contributed to the formation of a new art market founded upon an interconnected network of producers, consumers, and distributors.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.090
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.259
Teacher spread0.226 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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