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Record W2968260377 · doi:10.3138/seminar.55.3.1

“Zum ersten Mal sah ich ein <i>Bild</i>”: Goethe’s Cognitive Viewing Subject as Scientist and Artist

2019· article· en· W2968260377 on OpenAlexvenueno aff
Andrea Meyertholen

Bibliographic record

VenueSeminar A Journal of Germanic Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Aesthetics, and Perception
Canadian institutionsnot available
Fundersnot available
KeywordsSubjectivitySubject (documents)PaintingArtReading (process)PraxisPhilosophyArt historyPsychologyVisual artsCognitive scienceAestheticsEpistemologyLinguisticsComputer science

Abstract

fetched live from OpenAlex

This article investigates the significance of Goethean natural science for the development of abstract modes of painting that would emerge with Wassily Kandinsky in the early twentieth century. While early abstractionists like Kandinsky unveiled their artworks with publications providing intellectual justification for an objectless art, a theoretical framework for a mode of viewing necessary for engaging with abstract art was already in existence, having been conceived by Goethe in his 1792 essay “Versuch als Vermittler von Objekt und Subjekt.” Close reading of this text reveals a primary model for a cognitive viewing subject who draws on sensory experience and cognitive faculties to assume a critically significant degree of subjectivity in aesthetic encounters. To demonstrate how the mode of viewing theorized by Goethe might operate in praxis, this article analyzes an exemplary moment of spectatorship credited for bringing about abstract art: Kandinsky’s storied first encounter with Claude Monet’s Haystacks.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.031
Scholarly communication0.0050.007
Open science0.0000.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.294
Teacher spread0.258 · 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 designTheoretical or conceptual
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

Citations1
Published2019
Admission routes1
Has abstractyes

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