Beyond the ‘Taking of Vimy Ridge:’ The War Photographs of William Ivor Castle
Bibliographic record
Abstract
Historians who study Canadian First World War photography often do so within the framework of commonwealth photographic programs, including the British and Australian wartime systems of information. Examples of this include Jane Carmichael's First World War Photographers (1989) and Hilary Roberts and Mark Holborn's The Great War: A Photographic Narrative (2014). One of the more frequently analyzed images of the First World War is William Ivor Castle's The Taking of Vimy Ridge. This paper proposes to contribute to that historiography by illustrating the larger implications of this manipulated image--that photography projects of the Canadian War Records Office must be analyzed separately from those of the British Ministry of Information. Additionally, this paper will examine some of Ivor Castle's other images made during the battle to argue that historians can move beyond The Taking of Vimy Ridge, to understand his photographic style as he attempted to visually capture the war.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".