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Record W2329908309 · doi:10.1093/res/hgr125

HEATHER CLARK. The Grief of Influence: Sylvia Plath and Ted Hughes.

2011· article· en· W2329908309 on OpenAlexaff
John Xiros Cooper

Bibliographic record

VenueThe Review of English Studies · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicPoetry Analysis and Criticism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWifePoetryServantConversationGriefLiteratureArtHistoryPsychoanalysisPhilosophyPsychologyTheologyLinguistics

Abstract

fetched live from OpenAlex

The publication of a volume of poems by one poet very rarely leads to a flurry of critical activity being devoted to another, especially one dead for 35 years. But that is exactly what happened after the publication of Birthday Letters by Ted Hughes in 1998. Birthday Letters revealed that since the death of Sylvia Plath in 1963 a kind of one-sided conversation between husband and wife, poet and poet, had been going on for decades in the husband’s head. There had been other muted or oblique fragments of that conversation in some of his poems written in the intervening years, but in Birthday Letters the husband finally put it all down as his last word on the matter. Inevitably the new materials stimulated not only interest in Plath, but in a sub-field of Plath and Hughes studies that had lain more or less fallow ever since Margaret Uroff’s ground-breaking study of the two poets together in 1979. Of course, in any study of Plath over the years, Hughes was never far off, but, typically, his presence was seen in one dimension only, either as a loyal servant of the wife’s brilliant but flawed imaginings or, more commonly, as a malign force.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0050.006
Scholarly communication0.0040.009
Open science0.0020.004
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0180.006

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 head0.067
GPT teacher head0.277
Teacher spread0.210 · 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 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
Published2011
Admission routes1
Has abstractyes

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