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Record W2779658197

Beyond the ‘Taking of Vimy Ridge:’ The War Photographs of William Ivor Castle

2017· article· en· W2779658197 on OpenAlexvenueaboutno aff
Carla-Jean Stokes

Bibliographic record

VenueJournal of military and strategic studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
Fundersnot available
KeywordsHistoriographyPhotographyBattleCommonwealthRidgeNarrativeStyle (visual arts)HistoryFirst world warChristian ministrySpanish Civil WarWorld War IIArt historyVisual artsArtLawPolitical scienceAncient historyArchaeologyGeographyCartographyLiterature
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score0.779

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.010
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.103
GPT teacher head0.321
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes2
Has abstractyes

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