Cities in Shade: Urban Geography and the Uses of Noir
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper historicizes American cities after the Second World War through the rich motif of noir literature and film. But, in doing so, the paper is also a critical consideration of noir's work in urban studies. Noir has been drawn, often usefully but also unfortunately, away from its referents, from the terrain that it most directly summons but also from the spaces in which its contradictions are most apparent. Moving from a discussion of the distractions of Chinatown to contextual themes such as mobility and ruin, the paper links noir criticism and noir texts with broader debates in postwar urbanism and modernism. As just part of these discourses, noir not only is irreducible to certain essences, but can potentially perform the opposite role, challenging conventions of urban understanding and practice. The result would be a more detailed and subtle account of modernism's American geographies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it