Fearsome Acts of Interpretation: Audiovisual Historiography, Film Theory and<i>Gangs of New York</i>
Bibliographic record
Abstract
This article revisits Jean-Louis Comolli's “Historical Fiction: A Body Too Much” (1978) in the spirit of film-philosophy's various efforts to reassess the field's seminal texts, and it recasts Comolli's attentive analyses of film acting in terms of the original interpretations they produce. In short, I look to “A Body Too Much’ for its subtle disclosure of an underappreciated substratum of hermeneutics in so called “1970s film theory.” Comolli's study of the discord between actor and referent, I argue, is surprisingly consistent with Paul Ricoeur's pioneering contemporaneous work on metaphor and interpretation, and it leads him to understand the meaningful deployment of film actors in very particular ways. I provide an extended analysis of Martin Scorsese's Gangs of New York (2002) to further demonstrate how the distinctive utilization of actors constitutes both a redescription of the historical past and a spur to interpretation. When critically apprehended as a solution to the broadly construed problems of creating historical fictions (pragmatic filmmaking problems, but also the significant matter of making meaning), the calculated deployment of film actors can reveal a manner of thinking about the historical past – simply put, it can tell us what a film is thinking and how it regards its historical characters and events. In the final analysis, I claim, our attention to – and critical interpretation of – the embodiment of such filmic thinking permits us to grasp the imaginative form of historical knowledge on view in such films.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".