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Record W1985673938 · doi:10.7202/017856ar

“Art’s Neurosis”: Medicine, Mass Culture and the Romantic Artist in William Hazlitt

2008· article· en· W1985673938 on OpenAlexvenueno aff
Gavin Budge

Bibliographic record

VenueRomanticism and Victorianism on the Net · 2008
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsnot available
FundersErasmus+
KeywordsRomanceRomanticismAmbivalenceTheme (computing)CriticismDenialGeniusAestheticsArtLiteraturePsychoanalysisPsychology

Abstract

fetched live from OpenAlex

Although criticism has traditionally focussed on the Romantic celebration of artistic genius, there is also an emphasis on artistic abjection in Romantic writing. This essay argues that the Romantic theme of abjection is linked to the claims of early nineteenth-century Brunonian medicine that conditions of nervous over- and understimulation are the cause of diseases such as consumption and hypochondria, a case which is made with particular reference to the writings of William Hazlitt. Brunonian medical theory also informs Romantic period analyses of a newly emergent mass culture, enabling Romantic depictions of artistic abjection to be understood as a denial of the Romantic artist's involvement in a mediatization of experience which potentially distances the audience from the intuition of reality to which Romanticism ultimately appeals. This ambivalence about the position of the Romantic artist is reflected in the Romantic period debate surrounding the aesthetic category of the picturesque, which is shown to draw on Brunonian ideas about nervous stimulation in a way which makes it exemplary of conflicted Romantic attitudes towards the effects of mediatization.

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 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 score0.670
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.274
Teacher spread0.253 · 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.

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

Citations4
Published2008
Admission routes1
Has abstractyes

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