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Record W639497162

The Genealogy of Aesthetics

2002· book· en· W639497162 on OpenAlexaboutno aff
Ekbert Faas

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicPhilosophy, Ethics, and Existentialism
Canadian institutionsnot available
Fundersnot available
KeywordsHegelianismPhilosophyPostmodernismDifféranceLiteratureSublimeThe RenaissanceArt historyArtAestheticsTheologyEpistemologyMetaphysics
DOInot available

Abstract

fetched live from OpenAlex

"Is it body or spirit that makes us appreciate beauty and create art? The distinguished Canadian critic Ekbert Faas argues that, with occasional exceptions like Montaigne and Mandeville, the mainstream of western thinking about beauty from Plato onwards has overemphasized the spirit or even execrated the body and sexuality as inimical to the aesthetic disposition. The Genealogy of Aesthetics redresses this imbalance, and offers a radical rereading of seminal thinkers like Plato, Augustine, Kant, Hegel, Heidegger, and Derrida. Professor Faas tells a new and exciting story, of the Platonic inversion of Homeric pagan values, of their absorption into Christian theology and eventual secularization, of Kant's grand reworking of this tradition, of Hegel's prophesy of the death of art in the ultimate triumph of spirit over body; and, finally, of the revival of the aesthetic/ascetic ideal in Heidegger, Derrida and their followers. Faas attacks both the traditional and postmodern consensus, and offers a new prosensualist aesthetics, heavily influenced by Nietzsche, as well as drawing on contemporary neo-Darwinian cognitive science. A work of both polemic and profound learning, The Genealogy of Aesthetics marks a radical new departure in thinking about art which no future work in this field can afford to ignore."--BOOK JACKET.

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: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.046

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 studies0.0050.046
Scholarly communication0.0070.005
Open science0.0010.002
Research integrity0.0010.004
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 head0.081
GPT teacher head0.248
Teacher spread0.167 · 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
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

Citations9
Published2002
Admission routes1
Has abstractyes

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