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Record W4385499752 · doi:10.46793/naskg2354.353vi

ESTETIKA RUŽNOG U „RIMSKIM PRIČAMA“ ALBERTA MORAVIJE

2023· article· en· W4385499752 on OpenAlexaboutno aff
Biljana Vlašković Ilić

Bibliographic record

VenueNasledje Kragujevac · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicReligious, Philosophical, and Educational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSublimeOpposition (politics)ArtBinary oppositionAestheticsObject (grammar)Order (exchange)PhilosophyLiteratureArt historyPoliticsLaw

Abstract

fetched live from OpenAlex

The paper juxtaposes the key postulates of Kant’s and Hartmann’s aesthetics of the beau- tiful and the sublime with Karl Rosenkranz’s aesthetics of ugliness in order to examine the dynamics of the relationship between the beautiful, the sublime, and the ugly in art. The paper’s working hypothesis is that the aesthetics of ugliness is necessary since the ugly and the beautiful form a binary opposition, given that the concept of the beautiful cannot be known and understood without the concept of the ugly. To investigate this hypothesis, the paper analyzes selected Roman Tales by Alberto Moravia (1907-1990), one of the most significant modern Italian writers, whose characters come from the margins of the society and belong to various categories of the ugly based on Rosenkranz’s nomenclature from The Aesthetics of Ugliness. With their physical and spiritual ugliness, Moravia’s characters negate the banalities of life and prove that the mundane is not beautiful per se, but is more often than not ugly and ordinary, and even as such it deserves to be the object of art.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.050
GPT teacher head0.377
Teacher spread0.327 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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