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Record W2060343114 · doi:10.2190/fwga-m9db-p9d4-11x6

Poetic Emotion and Poetic Style: The 100 Poems Most Frequently Included in Anthologies and the Work of Emily Dickinson

2004· article· en· W2060343114 on OpenAlexaff
Cynthia Whissell

Bibliographic record

VenueEmpirical Studies of the Arts · 2004
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPoetryStyle (visual arts)LiteraturePsychologyArtLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

The 100 most frequently anthologized English poems and the work of Emily Dickinson were analyzed empirically in terms of emotion, sound, and style. Results for the 100 poems indicated that poetry was significantly more Pleasant, less Active, more highly Imaged, and in several ways more complex than normal everyday English. In terms of sounds, the 100 poems included significantly more Sad, Passive, Soft, and Pleasant sounds and fewer Active and Nasty sounds than everyday English. Because of relationships between measures, seven factors were sufficient to explain most of the differences among poems. The 100 most frequently anthologized poems are ranked individually in terms of these factors. The poems of Emily Dickinson were significantly less Pleasant, less Active, and more Negative, though containing more Active and Nasty sounds.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.408
Teacher spread0.280 · 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.

Study designObservational
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

Citations5
Published2004
Admission routes1
Has abstractyes

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