Bollywood Makes Men: Gender, Globalization, and Nation in India
Bibliographic record
Abstract
In a globalizing India, the male body has become a signifier of India’s self-confidence on the world stage. Hindu nationalism and a nationalist triumphalism linked to an assertive global middle class form the material context of this signification. Muscular nationalism, defined in my works as an intersection of armed masculinity with the political doctrine of nationalism, enables a theoretical frame to analyze this version of an imagined India. This talk will draw on Bollywood film, which is an important vehicle for disseminating dominant imaginings of nation in India, to demonstrate the popular circulation of this interpretation of nation. About the Lecturer: Sikata Banerjee is Professor of Gender Studies at the University of Victoria, Canada. Her work focuses on gender and nationalism in India. She is the author of Warriors in Politics: Hinduism, Nationalism, Violence, and the Shiv Sena in India (Westview 2000); Make Me a Man! Masculinity, Hinduism, and Nationalism in India (SUNY 2005); Muscular Nationalism: Gender, Violence, and Empire in Ireland (NYU 2012); and Globalizing Muscular Nationalism: Gender, Nation and Popular Film in India (Routledge 2016).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".