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Record W7117274968 · doi:10.5281/zenodo.18049608

Post-Surface Painting and the Structural Limits of Academic Painting Education

2025· preprint· en· W7117274968 on OpenAlexaboutno aff
Daniel A. Freedman

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPaintingHigher educationVisual cultureQuarter (Canadian coin)PhotographyUkrainian

Abstract

fetched live from OpenAlex

This preprint presents a structural analysis of academic painting education in the first quarter of the twenty-first century and introduces post-surface painting as a response to its historical and institutional limits. The study argues that contemporary painting pedagogy remains largely grounded in surface-based, pigment-centred models formed in the nineteenth century, despite the central role of light as a primary medium of contemporary visual culture. Post-surface painting is articulated not as a technological trend or stylistic innovation, but as a reconfiguration of pictorial logic in which light functions as a generative medium governed by optical processes. The paper examines why attempts to integrate such practices into existing academic painting frameworks are structurally untenable and proposes the emergence of parallel educational systems as a necessary alternative. The analysis is supported by theoretical foundations, historical precedents of light-based art, and evidence of marginalised practices within the Ukrainian and Soviet cultural context. The work is intended as a conceptual and methodological contribution to discussions on painting education, materiality, and the future of pictorial practice.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.274
Teacher spread0.231 · 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
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
Published2025
Admission routes1
Has abstractyes

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