Bibliographic record
Abstract
British royal tours to the empire’s settler dominions of Canada, South Africa, Australia, and New Zealand reached their zenith in the early- to mid-twentieth century during a period of wilful amnesia and lack of engagement with the legacies of violence and dispossession brought about by colonial rule. This afterword considers royal tours in the light of the systemic racial inequality inherent within settler colonialism and its narrative of nationhood and British loyalism. The discussion draws on the articles in this special issue, but also on new examples: Mark Twain, the American author and anti-imperialist, demonstrates a different type of touring celebrity to visiting royals and their role as defenders of empire, with Twain critical of empire in his literary works and travels; Sol Plaatje, the black South African journalist, politician and one-time translator to the Duke of Connaught, reveals the ineffectiveness––and reticence to intervene––of touring royals as mediators between settlers and colonial subjects robbed of their land and liberties. The article concludes by noting improvements in the speed of travel and telecommunications as crucial for the increase in royal tours to settler dominions, an increase that proved critical in facilitating the affective power of royal performance for the solidifying of settler nationalisms reliant upon loyalism to the Crown.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".