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Record W2989293955 · doi:10.5539/ijel.v9n6p421

A Critical Discourse Analysis of Mind Control Strategies in George Orwell’s Nineteen Eighty-Four

2019· article· en· W2989293955 on OpenAlexvenueno aff
Khalid Sultan Thabet Abdu, Ayman Farid Khafaga

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSwearing, Euphemism, Multilingualism
Canadian institutionsnot available
FundersDeanship of Scientific Research, Prince Sattam bin Abdulaziz UniversityPrince Sattam bin Abdulaziz University
KeywordsIdeologyPower (physics)EuphemismCritical discourse analysisSociologyNarrativeControl (management)George (robot)Discourse analysisAestheticsEpistemologyLinguisticsLawPoliticsPolitical scienceHistoryPhilosophyManagementEconomics

Abstract

fetched live from OpenAlex

This paper attempts a Critical Discourse Analysis (CDA) of mind control strategies in George Orwell’s Nineteen Eighty-Four (1948). More specifically, the paper tries to shed lights on the discursive practices that are used to control the public’s minds in a way that guarantees complete compliance to a specific ideology. Orwell’s novel is one of the distinguished narratives in the twentieth century. This type of fiction has always been a site of power conflict reflecting the atrocities committed against the public by those in power. The main objective of the paper is to uncover the strategies employed to control minds. It tries to explore the extent to which these discursive tactics are used to direct attitudes and change behavior. The paper therefore attempts to offer a linguistic shield against the manipulative use of language. In doing so, the paper adopts CDA in the analysis of the selected data. Some CDA’s strategies have been marked and analyzed as indicative in exposing the extent to which language is biased towards mind control. Three main strategies are discussed here: simplification, euphemism and morphologicalization. The paper reveals that specific discursive practices have manipulatively been used by the elites to reformulate the ideological responses and attitudinal thinking of the masses.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0080.022
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.003
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 head0.019
GPT teacher head0.370
Teacher spread0.351 · 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 designQualitative
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

Citations8
Published2019
Admission routes1
Has abstractyes

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