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Sound and Emotion in Milton's <i>Paradise Lost</i>

2011· article· en· W1966057437 on OpenAlexaff
Cynthia Whissell

Bibliographic record

VenuePerceptual and Motor Skills · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPoetryParadiseHeavenSound (geography)Paradise lostNarrativeSpellingLiteraturePsychologyArtHistoryPhilosophyLinguisticsAcousticsArt history

Abstract

fetched live from OpenAlex

This research was designed to test the hypothesis that Milton's poem Paradise Lost is meaningfully patterned with respect to sound. Thirty-six segments from 12 Books of Paradise Lost were scored (Whissell, 2000) in terms of their proportional use of Pleasant, Cheerful, Active, Nasty, Unpleasant, Sad, Passive, and Soft sounds. Paradise Lost includes more Active, Nasty, and Unpleasant sounds and fewer Pleasant, Passive, Soft, and Sad sounds than a representative sample of anthologized poetry. The way in which emotional sounds are patterned (e.g., the rise and fall in the proportion of Pleasant sounds across Books) suggests the presence of three narratives within the work: Sin and Salvation-Foreseen in Heaven (Books I-II), The Fall of Man (Books IV-IX), and Sin and Salvation-Foretold on Earth (Books X-XI). The poem analyzed had updated spelling, and the author's exact intentions when creating it are not accessible to direct investigation, for this among other reasons.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.258
Teacher spread0.231 · 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 designQualitative
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

Citations7
Published2011
Admission routes1
Has abstractyes

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