Fictionalizing Realities Against the Supremacist Global Order: Roy and Adiga’s Literary Counter to Neo-Imperialism
Bibliographic record
Abstract
In an era when old empires resurface under new guises, neo-imperialism shapes global geopolitics through overt aggression, economic control, and cultural erasure. Russia’s invasion of Ukraine, Western debates over strategic territories like Greenland, and Canada’s resource disputes with Indigenous communities reveal that imperial ambitions still exist, cloaked in modern rhetoric. Operating through economic dependency, digital dominance, and ecological exploitation, today’s empires marginalize subaltern voices while perpetuating systemic inequities. Against this scenario, contemporary Indian novels emerge as potent forms of resistance. Authors like Arundhati Roy and Aravind Adiga reveal the human cost of global capitalism using stories of migration, urban relocation, caste persecution, and neoliberal disillusionment. Roy’s poetic activism and Adiga’s keen sarcasm formulate a counter-narrative that questions the ideological foundations of neo-imperialism. Their literature questions the global system while also envisioning multiple, equitable futures. In their hands, the narrative transforms into a courageous indirect political act.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.043 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".