A Critical Discourse Analysis of Mind Control Strategies in George Orwell’s Nineteen Eighty-Four
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".