An ‘imperial hangover’? Royal Honours in Australia, Canada and New Zealand, 1917–2009
Bibliographic record
Abstract
New Zealand ceased to award the titles of ‘Sir’ and ‘Dame’ in 2000, joining Australia and Canada in what looked like the end of a process of change that all three countries had been implementing in their honours systems over the twentieth century, albeit at varying speeds. In each case, imperial British honours had been gradually discarded in favour of homegrown national ones, and the practice of conferring knighthoods and damehoods had ceased. In 2009, however, New Zealand's newly elected National government announced that titles were to be reinstated. While not a restoration of imperial honours in place of the country's relatively young national ones, the move put New Zealand out of step with Australia and Canada in terms of honours. This article traces the shifting relationships that Australia, New Zealand and Canada had with imperial honours over the twentieth century, and the steps by which each moved away from British honours towards their own national systems. In all three settings, changes were accompanied by debates over nationalism, independence and the endurance of historic ties to Britain. Through the case study of honours, this article offers a contribution to scholarly consideration of the process of de-dominionisation and the end of empire in the British World, and of the new nationalism that arose alongside and as part of that process.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".