Bibliographic record
Abstract
BOUNDARY CROSSING AND THE CONSTRUCTION OF CINEMATIC GENRE: FILM NOIR AS "DEFERRED ACTION" The Frame-Up: Theoretical ConsiderationsIn recent years, critical consensus in cinema studies has begun to coalesce around the idea that, in a sense, there never was such a thing as film noir. Thomas Elsaesser, for example, comes to this conclusion after examining what might be called one of the foundational myths of film noir, the "connection between German Expressionist cinema and American film noir" (Elsaesser: 420). (1) Ever since this story about noir's origins has solidified into one of the "commonplaces of film history," Elsaesser argues, it has become difficult to see film noir for what it really is, "an imaginary entity whose meaning resides in a set of shifting signifiers" (Elsaesser: 420). Following a critical rather than a cinematic tradition, he traces the consolidation of the genre's identity back to the intervention of German exiles like...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.047 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".