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Record W2923670873 · doi:10.21039/rsj.143

Ceremony, Conquest, and Conciliation: An Afterword

2018· article· en· W2923670873 on OpenAlexaboutno aff
Chris Holdridge

Bibliographic record

VenueRoyal Studies Journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Literature and Humor Studies
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismEmpireCeremonyHistoryPower (physics)British EmpireNarrativeIndigenousAncient historyLiteratureArtArchaeology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.053
GPT teacher head0.299
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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