Photographic retouching: the press picture editor's "invisible" tool 1930-1939 : a study of retouched press prints from the Art Gallery of Ontario's British Press Agencies Collection
Bibliographic record
Abstract
Photographic Retouching investigates the mediatory work of the news picture editor during the 1930s. It considers what retouched press photographs add to the history of modern photojournalism, and offers a re-examination of the historiography of 1930s press photography. A descriptive analysis of sixteen representative, retouched photographs from the Art Gallery Of Ontario (AGO) British Press Agencies Collection (BPAC) and ten corresponding newspaper and magazine page spreads from the Daily Mirror, the Sunday Dispatch and Life is carried out in conjecture with press photography manuals published between the years 1930 and 1939. A literature survey, methodology section and description of the BPAC provide introductory contextual and historical information. Chapters 4 and 5, the main analytical sections, focus on two aspects of retouching: the technical difficulties that afflicted press photography during the 1930s and how retouching was employed as a corrective tool; and the ways in which retouching was utilized to strengthen and improve upon the photograph’s ability to consistently convey a clear and visually efficient narrative for use by the press.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".