CANZUK, the Anglosphere(s) and Transnational War Commemoration: The Centenary of the First World War
Bibliographic record
Abstract
This chapter examines commemoration across the Anglosphere of the centenary of the First World War, which has drawn attention to the critical ordering and articulation of shared transnational collective memories and historical narratives. Tensions between national and transnational manifestations of war commemoration reveal the legacies of the British Empire, revealing the intersections between post-imperial and post-colonial constructions of history and memory across the Anglosphere and Commonwealth. The chapter argues that although Anglospheric war commemoration is located in remembrance of past conflicts, it is intimately connected with the present and future, thus meaning its context and meaning are prone to periodic reinvention in response to contemporary geopolitical circumstances. Commemoration of the First World War across the Anglosphere highlights the layered, hybridised, porous, and contested boundaries of the so-called ‘CANZUK’ union of Australia, Canada, New Zealand, and the UK, the ‘core’ Anglosphere which includes the United States, a less well defined Anglosphere, and the Commonwealth. It concludes that a ‘politics of war commemoration’ both binds and divides the Anglosphere and other parts of the former British Empire, highlighting the contentious and contested nature of transnational historical narratives and memory cultures informing diverse national commemorations of the First World War centenary.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.016 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".