Bibliographic record
Abstract
Located at the intersections of international porn studies, celebrity studies, gender, sex and globalization, this article looks at the recent and unusual case of Sunny Leone, an Indo-Canadian bisexual pornographic actress who successfully crossed over to Bollywood. By examining her many lives and avatars – as an international porn star, a reality TV contestant, a Bollywood celebrity and now a show host on MTV India, who maintains an active presence on social and digital media – I suggest that the unprecedented situation Sunny Leone has engendered in India presents us with a form of transnational onscenity: in other words, it brings to the fore the centrality of porn in the economies of global cross-cultural exchange and forces us to rethink previous paradigms of both ‘pornography’ and stardom, two domains that have more or less remained mutually exclusive of each other in the sub-continent. Leone’s case brings to the fore economic, social and cultural exchanges between two mammoth entertainment industries, Bollywood and American pornography, which had not encountered each other in these ways before. The capital gains from these exchanges seem to overshadow concerns about preserving the nation’s ‘moral’ fabric and have concurrently given way to newer spaces for accommodating a celebrity like Leone. Given that her crossover from porn presents an absolute rupture from all previous paradigms of female stardom in the Indian context, I place the discourses surrounding her within the tangible anxieties and fantasies of both desire and control over her ‘Indian but foreign’ and ‘pornographic’ body. Highlighting Leone’s agency through the entire process, which is unique in many regards, this article attempts to further rethink and complicate overarching notions of ‘objectification’ that often dominate the field.
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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 | 0.026 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".