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Record W3093113480 · doi:10.3138/md.63.3.1076

Matters of the Heart: The Poetics of Trauma in Harold Pinter’s <i>Ashes to Ashes</i>

2020· article· en· W3093113480 on OpenAlexvenueno aff
Matthew Roberts

Bibliographic record

VenueModern Drama · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature and Cultural Memory
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryPoeticsRepresentation (politics)Interpretation (philosophy)LiteraturePoliticsActive listeningArtPsychoanalysisHistoryPhilosophyPsychologyLinguisticsLawCommunicationPolitical science

Abstract

fetched live from OpenAlex

Harold Pinter’s Ashes to Ashes, comprising an extended dialogue between two protagonists, Rebecca and Devlin, repeatedly returns to a “guide” who steals babies from their mothers at a railway station. This image has led Pinter scholars to interpret the play as a representation of the Shoah and its impact on Pinter’s life. However, during the play’s conclusion, Rebecca assumes the position of one of the mothers and, while ventriloquizing her, disavows the existence of her child at the very moment when another woman asks her to confirm the infant’s whereabouts. Rather than maintaining the customary position that Ashes to Ashes represents a specific historical atrocity, I read the play’s engagement with trauma through the figure of this abducted, but ultimately disowned, infant. Specifically, I attend to how the infant’s disappearance informs the poetic qualities of Ashes to Ashes as its heartbeat figures prominently throughout the play, resonates in its dialogue, and organizes its rhythmic structure. By examining how these poetic features situate Rebecca’s mode of listening as an exemplary ethico-political response to suffering, I propose an alternative to the interpretation of Pinter’s use of dramatic speech in terms of referentiality or language games.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0140.028
Scholarly communication0.0080.003
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.217
Teacher spread0.185 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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