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Record W2512509702 · doi:10.1057/978-1-137-47835-1_3

Defilement and Social Theory

2016· book-chapter· en· W2512509702 on OpenAlexaff
Matthew P. Unger

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSymbol (formal)Reading (process)Meaning (existential)Interpretation (philosophy)PoliticsDisgustAestheticsEpistemologySociologyPhilosophySocial psychologyPsychologyLinguisticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

In this chapter, Unger examines literature on the grotesque, the abject, and defilement to show the significance and historical lineage of grotesque aesthetics. Grotesque artistic expressions evoke a particular social experience that has prompted thinkers to examine the social, political and aesthetic meaning of visceral experiences of disgust and revulsion. While theorists have attempted to ground this experience in trans-historical necessity, Unger argues that a more hermeneutic and genealogical interpretation allows one to situate this experience within the social, political, and juridical in interesting ways. This chapter draws from Ricoeur’s text, The Symbolism of Evil , with an examination of the particular symbol of defilement and its possibility for reading contemporary conceptions of fault embedded within extreme metal. Unger compares Ricoeur’s understanding of defilement with those of contemporary theorists of transgression, the grotesque, and the abject in order to ground a more social reading of this particular symbol and to understand its significance within the genres of extreme metal. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.003
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 score0.009
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0080.077
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0030.004
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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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