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Record W2978495016 · doi:10.82308/41162

"Hail horrors": from the sublime to the grotesque and back

2018· article· en· W2978495016 on OpenAlexfundno aff
Danna Petersen-Deeprose

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
FundersStrongMcGill University
KeywordsSublimeRomanticismEnlightenmentPoetryArtParadise lostScholarshipHumanitiesPhilosophyParadisePerspective (graphical)Art historyLiteratureEpistemology

Abstract

fetched live from OpenAlex

This thesis explores the complex relationship between the sublime and the grotesque in literature. While the two might at first appear to have little in common, they frequently intersect in literary theory and history. My thesis considers that convergence in Paradise Lost (1674), Wuthering Heights (1847), and Hannibal (2013-2015). Written in very different time periods and social milieus, they each approach the sublime and the grotesque from a unique perspective. Milton was foundational in early scholarship on the sublime, but the grotesque is equally important throughout his epic poem. In Wuthering Heights, both the sublime and the grotesque become more psychological as Brontë engages with the legacies of the Enlightenment, the Gothic period, and Romanticism. Finally, my discussion of the television series Hannibal examines the role of the two aesthetic categories in today’s world. By putting these three works into dialogue with one another, my thesis follows the evolution of the overlap between the sublime and the grotesque, exploring the ways in which the two inform and affect one another.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.020
GPT teacher head0.256
Teacher spread0.236 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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