The space between photography and film : an object study from the Warner Bros.-First National Keybook collection
Bibliographic record
Abstract
Historically and conceptually, film stills occupy a precarious position between two academic disciplines: cinema studies and the history of photography. They are overshadowed in collections by more prominent and "valuable" cinematic or photographic objects competing for the same space and money; and they have received relatively little attention in scholarship, exhibitions and publications. The film still is a unique and distinctive genre of object, possessing its own history, physicality, and aesthetic. After establishing a historical and descriptive context for understanding the film still as an object with multiple incarnations - commercial, nostalgic, historical, educational, artistic - this thesis transitions into an analysis of actual stills. By examining the physical and aesthetic characteristics of a small selection of stills from George Eastman House's "Warner Bros.-First National Keybook Collection," drawn from the keybooks of Other Women's Husbands (1926), Lights of New York, and 42nd Street, an argument emerges for the establishment of the film still as a genre of photographic object distinguishable by its physical and aesthetic characteristics as much as by its origin.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".