Reading the Perplexing Figure of the "Bandit Queen": Interpellation, Resistance and Opacity
Bibliographic record
Abstract
Through an examination of some of the stories that textually produced and constructed Phoolan as the iconic of the I argue that a range of representations including the biopic, Bandit Queen, functioned to impose a form of transparency on the marginalized. Such texts aim to tell the truth and to transparently reveal the subaltern woman specifically Phoolan Devi and the savagery that surrounded her. I will argue that this imposition of transparency is achieved through interpellation hailing Phoolan as the Queen or as the Kali figure an unsophisticated woman who was brutalized and sought revenge. This process of interpellation reveals neoliberal ideologyA¢â¬â¢s attempt to manage the burgeoning political power of lower caste and dalit groups through the body of the gendered subaltern in postcolonial India. I will also argue that despite these attempts to reveal the truth about Phoolan Devi, ambivalences remain. I will show that such ambivalences can be productive mainly because they resist the imposition of transparency on the subaltern. More specifically, I will argue that one must read and represent the subject through the contradictions and the paradoxes that she appears to embody and that the autobiographical text I, Phoolan Devi in particular offers us this opportunity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".