Approaching war: Australian and Canadian children’s culture and the first world war
Bibliographic record
Abstract
© Oxbow Books Ltd and the Society for the Study of Childhood in the Past 2014. In 2010, the Leverhulme Trust partially funded three ‘Approaching War’ international conferences (Australia in 2011, Canada in 2012 and the UK in 2013) to explore the impact of the First World War on children and childhood culture from three different geographical and cultural perspectives: the Global South, the Americas and Europe. As our article provides the first analysis of the perspectives gathered from those conferences, we address the seismic historical reinterpretation of the war over the century. In the immediate aftermath, Australia and Canada both cited the First World War as the moment when they emerged from their colonial status into independent countries with distinct national myths characterised by courage and sacrifice. The children’s books of the period, particularly Ethel Turner’s (1915) The Cub in Australia and L. M. Montgomery’s (1921) Rilla of Ingleside in Canada, defined national identities, and marked Germans as the enemy. As the political landscape changed dramatically over the century, so has children’s literature, focusing on the personal tragedies across border lines, as in Michael Morpurgo’s (1982) War Horse. A century on, archival research has also turned up the actual words and images of children – on both sides of the conflict. We track the changes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.032 | 0.017 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".