The Politics of Film Aesthetics: Filmososphy, Post-Theory, and Rancière
Bibliographic record
Abstract
The question of aesthetics in film-theoretical discourse today is split between, on the one hand, a film-phenomenological or “filmosophical” approach that values the putatively immanent relation between film and the mind and, on the other, the naturalizing epistemology of post-theory, which reduces the question of film aesthetics to one of poetics. What unites these otherwise disparate projects is the consideration of aesthetics divorced from the question of politics; in both cases, the social or political significance of the film–spectator relationship has been summarily purged. In this article, I will offer an alternative account of film aesthetics that draws on Jacques Rancière’s theory concerning the mutually determining relationship between aesthetics and politics. In particular, I will consider the relevance of Rancière’s thesis concerning what he calls the distribution of sensible to current accounts, as well as taking up his novel consideration of aesthetic distance and the “emancipated” spectator. With respect to film phenomenology, I will examine how its film-theoretical program rests on the flawed concept of a de-politicized spectator enchained by the film image. With respect to post-theory, I will examine how its appropriation from cognitive science of the rational agent model of meaning making inappropriately limits the political potential of film aesthetics.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.060 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| 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".