Visualising emptiness: the landscape of the Western Front and Australian and English children’s picture books
Bibliographic record
Abstract
Although the Great War made extraordinarily complex demands on the nations involved, it is the landscape of the battlefield which has continued to dominate contemporary perceptions of the conflict. Australian and English children’s picture book authors and illustrators have adopted a similar focus, particularly regarding the Western Front. It is the illustrators, however, who have the more complex task, for they have inherited an aesthetic issue that has challenged artists since 1914. Like the British, Australian, Canadian, and New Zealand official war artists of the time, they are confronted, at every turn, by the challenge of depicting a surreally empty landscape. It was not so much a landscape as the artists understood it before the war, but rather an anti-landscape, as though the war had annihilated Nature. What was left was a dystopian wilderness that bore witness to the destructive power of industrialised warfare. This article will explore how a selection of Australian and English children’s picture book illustrators respond to the emptiness of the battlefield landscape, or as Becca Weir so evocatively characterises it, the paradox of measurable nothingness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".