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Record W3000002460 · doi:10.5539/ijel.v10n1p414

Traumatic Speech Acts in Toni Morrison’s Beloved

2020· article· en· W3000002460 on OpenAlexvenueno aff
Tamsila Naeem, Zafar Iqbal Bhatti, Mushira Habib

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiterary Theory and Cultural Hermeneutics
Canadian institutionsnot available
Fundersnot available
KeywordsRhetorical questionWhite (mutation)PsychologyOrder (exchange)SociologyArtLiterature

Abstract

fetched live from OpenAlex

This qualitative study aims to scrutinize the traumatic effects of rhetorical and political excitable speech acts in Toni Morrison’s most commended novel Beloved, which presents haunting situations of slavery in USA. The novel demonstrates that the white masters attempt to interpellate the minds of the black slaves in order to make them recognize that they are sub-human creatures. These interpellative forces consequence in life time enslavement of the victims, since they never come out of the traumatic effects of the verbal abuse, they were victimized with. The data are collected from Toni Morrison’s novel, Beloved, which presents haunting situations in which the black slaves after their freedom, evoke in their mind traumatic memories of their slavery. In order to examine the traumatic speech acts, relevant excerpts were taken through purposive sampling under the method of content analysis. The applied theoretical model is based on Judith Butler’s postulates about burning speech acts presented in her famous book, Excitable Speech. The analysis of the selected traumatic speech acts shows that the pricking state of the victims’ self and ego traumatize them even after they get freedom. They repeat the injurious speech acts and atrocities of the white masters to further aggravate the situations through traumatic speech acts.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.011
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)0.0010.000

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 head0.040
GPT teacher head0.267
Teacher spread0.227 · 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.

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
Published2020
Admission routes1
Has abstractyes

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