Bibliographic record
Abstract
This article explores two recent documentary films, one of which may not be a documentary, the other of which may not be a film. Although starkly different in their subject matter and political stakes, both Catfish (Ariel Schulman and Henry Joost, 2010) and This Is Not a Film (Jafar Panahi and Mojtaba Mirtahmasb, 2011) point to underappreciated dimensions of filmic realism, in particular its propensity to evoke what I will call Real-ism—i.e. hints of the Real that emerge precisely when the symbolic framework governing reality becomes imperiled. Drawing upon Jacques Lacan’s notion of the Real and Jacques Rancière’s concept of the “aesthetic regime,” I will suggest that elements of conventional filmic realism have the potential to produce a politically destabilizing Real-ism which, rather than involving the representation of reality in any recognizable form, calls forth that which is necessarily excluded/repressed from the symbolic framework.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".