Bibliographic record
Abstract
This paper explores the cinematic meta-theme of the “death of cinema” through the lens of Taiwanese director, Tsai Ming-liang’s 2003 film, Goodbye, Dragon Inn. In the film, the final screening of the wuxia pian classic, Dragon Inn, directed by King Hu, provides a focal point for the exploration of the diminished experience of institutional cinema in the post-cinematic age. Using the concept of “dissipation” in conjunction with a reappraisal of the turn to affect theory, this paper explores the kinds of subjective experiences that cinema can offer, and the affective experience of cinema-going itself, as portrayed in Goodbye, Dragon Inn. More specifically, in theorizing the role of dissipation in cinema-going, this paper explores the deployment of time and space in Goodbye, Dragon Inn and how it directs attention to the bodily action of cinema-going itself. The result is a critique of the possibilities of post-cinematic affects, rooted in an understanding of the way that late-capitalism continues to dominate and shape the range of experiences in the contemporary moment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".