Bibliographic record
Abstract
As the COVID-19 pandemic continues to violently underscore the pre-eminence and precariousness of corporeality, the audiences’ bodily engagement with the screens on which they watch cinema is apt to undergo a range of shifts. When India implemented one of the strictest shutdowns in the world to control the spread of COVID-19, a population renowned for its fervent film fanbase, was forced away from film theatres. A privileged minority, however, was able to continue their pursuit of cinema by turning to the screens within their possession. This study engages with Indian women who have access to digital screens to watch Indian films. Based on in-depth interviews conducted with over forty women from predominantly urban India over the course of three months, this study observes how these reconfigurations primarily proceed along three axes: shifts in the linguistic and ideological rubric where the body’s investment in the digital screen becomes emplaced, the emergence of new constellations of women’s communities centered around cinema, the increased introspection among women about the genre of cinema watched on digital screens, and the subsequent impact on their gendered identity.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.388 | 0.235 |
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".