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Guston, Philip (1913–1980)

2018· book-chapter· en· W4243773594 on OpenAlexaboutno aff
Antonia Pocock

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicArt, Politics, and Modernism
Canadian institutionsnot available
Fundersnot available
KeywordsPaintingArt historyIconographyPerformance artArtStyle (visual arts)FrescoPoliticsPollockThe artsComic stripComicsVisual artsHistoryLiteratureLaw

Abstract

fetched live from OpenAlex

American artist Philip Guston is best known for the comic-strip-inspired paintings he created during the last decade of his life. Though they prompted scathing reviews when first exhibited in 1970, Guston’s late works became a precedent for 1980s Neo-expressionism. Born Philip Goldstein to Jewish-Ukrainian immigrants in Montreal, Guston was raised in Los Angeles, where he attended the Otis Art Institute, as well as the Manual Arts High School with Jackson Pollock. Inspired by Italian Renaissance frescoes and Mexican muralism, Guston began his career painting political murals—first in California and Mexico, and later in New York as part of the WPA’s Federal Art Project. While teaching at the University of Iowa and Washington University in St Louis in the 1940s, Guston gained critical acclaim for his allegorical street scenes. In 1951, he moved to New York and began producing gestural abstractions in the manner of Willem de Kooning. His return to figuration in the late 1960s, prompted by the social and political unrest of the period, combines the iconography of his early paintings; specifically, these works feature hooded figures and brick walls, with an expressionist style marked by his signature short, thick brushstrokes.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0270.008

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 head0.080
GPT teacher head0.245
Teacher spread0.165 · 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
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
Published2018
Admission routes1
Has abstractyes

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