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Record W1906081206 · doi:10.5539/ass.v11n24p95

Trauma of Displacement in V.S. Naipaul’s The Mimic Men

2015· article· en· W1906081206 on OpenAlexvenueno aff
Masoumeh Mehni, Noritah Omar, Ida Baizura Bahar

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsnot available
Fundersnot available
KeywordsDisplacement (psychology)PsychologySubject (documents)PsychoanalysisWorking throughSocial psychologyComputer science

Abstract

fetched live from OpenAlex

This research considers displacement in Naipaul’s The Mimic Men as a traumatic experience. Taking an interdisciplinary approach to the subject of my study, it explores the historical and psychological dimensions of the displacement in the novel, as well as its literary representations. In the first step, I depicted the displacement as a traumatic experience for the protagonist by the illness which displacement causes Post Traumatic Stress Disorder. In the second step, I suggested two ways the protagonist goes through to remember their trauma. These ways are two different kinds of memory, namely, “acting out” and “working through”. I take “acting out” and “working through” as different but not opposite processes. “Acting out” and “working through” may never be totally separated from each other, and the two may always mark or be implicated in each other. In the third step, I also looked at the impacts of trauma of displacement on the structural and formal components of The Mimic Men.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0100.007
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.277
Teacher spread0.226 · 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 designTheoretical or conceptual
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

Citations1
Published2015
Admission routes1
Has abstractyes

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