Beyond the Red Carpet: Unravelling the Socio-Cultural Significance of Film Festivals and its Evolution Post-Pandemic
Bibliographic record
Abstract
Beyond the Red Carpet: Unravelling the Socio-Cultural Significance of Film Festivals and its Evolution Post-Pandemic Author: Anju Maria Sebastian Film festivals are opportunities to celebrate, enjoy and appreciate the art of cinema. They provide a platform for diverse voices and stories from across countries, cultures, and perspectives. Festivals like the Cannes and Toronto International Film Festivals enable cultural exchange and help in a deeper appreciation and understanding of global cinema. However, the Covid pandemic brought a huge blow to the smooth functioning of film festivals all over the world. Festivals were either postponed or cancelled altogether, leaving the whole film ecosystem disrupted. They resorted to platforms like Google Meet and Zoom for online interaction and discussions. Online streaming platforms like Netflix, Amazon Prime Videos and Disney+ Hotstar also gained popularity. The hybrid mode of festivals was quickly adopted by the film fraternity as it helped the easy and convenient functioning of festivals without losing much of its essence. This paper is an analysis of the challenging times during COVID, how film festivals thrived, their evolution and what their future might look like. Keywords: Film festivals, cultural exchange, pandemic, online streaming, hybrid festivals Anju Maria SebastianAssistant ProfessorDepartment of English Rajagiri College of Management and Applied SciencesRajagiriPin: 682039IndiaPh +91 9746091454Email: anjumariasebastian@gmail.comORCID: 0009-0009-0307-0454
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".