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Harold Pinter: Traumatic Neuroses and Nervous Shock in Ashes to Ashes

2013· article· en· W1721890161 on OpenAlexvenueno aff
Vafa Nadernia, Ruzy Suliza Hashim, Noraini Md. Yusof

Bibliographic record

VenueHigher education of social science · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTranceHysteriaPsychePsychoanalysisFreudian slipPsychologyNeurosisPerspective (graphical)Shock (circulatory)PsychotherapistPhilosophyArtMedicineVisual arts

Abstract

fetched live from OpenAlex

The main purpose of this article is to present the hidden features of Post Ttraumatic Stress Disorders (PTSD) in one of the major works of Harold Pinter, English playwright and 2005 Nobel Prize winner for literature. The selected play is Ashes to Ashes which was written in 1996. This play has been analyzed from the perspective of Trauma Theory which refers back to the Freudian psychoanalysis in second half of the nineteenth century where the effects of trauma depicted the trembling shocks of a mental and physical wound on the memory. In the 1860s, Sigmund Freud coined the terms Traumatic Neuroses and Nervous Shock as a reaction to the hysteric and trance states of those people who suffered from a mentally wounded psyche in deathly violent conditions. To prove our contention, we choose the main motifs of traumatic neurosis such as Hysteria, Trance states, Violent mood swings, Amnesias, Partial paralysis of the body, Anxiety and physical pain, Shell shock, Blocking of memory, and Post Traumatic Stress Disorder (PTSD).

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)0.004
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.006
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.283
Teacher spread0.253 · 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
Published2013
Admission routes1
Has abstractyes

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