Fictionalizing the Language of Power: A Comparative Study of Pakistani and Latin American Novels
Bibliographic record
Abstract
Latin American dictator fiction has a long tradition and is widely acclaimed in critical studies, while Pakistani dictator fiction began to emerge in recent years. The study is analytical and comparative research based on the contents of two culturally, historically, and geographically diverse novels—Mario Vargas Llosa’s The Feast of the Goat and Mohammad Hanif’s A Case of Exploding Mangoes so as to locate their common and contrasting aspects. It is a qualitative study and through content analysis, it finds convergences and divergences between a Latin American and a Pakistani dictator novel. A special emphasis of the study is on power, dictator portrayal, torture, resistance, retelling/rewriting history, and representation. The study concludes that where Llosa presents the detailed description of events related to the atrocious regime of Trujillo, Hanif presents a partial and not the whole view of Zia’s dictatorship. Llosa misses no opportunity to create the sentiments of detestation and wrath against the despotic rule and his language throbs with bitterness and becomes satiric while unveiling the dark aspects of the Trujillo regime. However, Hanif, instead of giving a detailed and direct portrayal of certain dark aspects and brutalities, gives just oblique references to them and even the events which he brings to the forefront are presented in a very light and humorous vein which fail to arouse the emotions of abhorrence and denouncement against the despotic rule.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".