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Record W2933281898 · doi:10.21039/rsj.139

Views Across the Decks of HMS Ophir: Revisiting the 1901 Imperial Royal Tour

2018· article· en· W2933281898 on OpenAlexaboutno aff
Cindy McCreery

Bibliographic record

VenueRoyal Studies Journal · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsDominionQueen (butterfly)George (robot)OfficerHistoryPort (circuit theory)Media studiesSociologyArt historyArchaeologyEngineering

Abstract

fetched live from OpenAlex

This article takes a fresh look at the 1901 royal tour of the British Empire by the future George V and Queen Mary on HMS Ophir. This tour has been examined by several scholars, who have tended to concentrate on a single individual dominion, i.e., Australia, Canada, New Zealand, or South Africa. Discussion has focused on local responses to the tour, and in particular to the royal couple. This article, in contrast, considers the tour as a single, global voyage, which involved more sea days than port days. It also moves beyond the royal couple to include the passengers and crew of both HMS Ophir and the accompanying British warships. By exploring a variety of individual shipboard accounts, in particular the illustrated journal of Petty Officer Harry Price and the published tour volume of Assistant Press Secretary Donald McKenzie Wallace, along with the personal diaries of the royal couple and an accompanying journalist’s description, the article explores the various, overlapping meanings of the tour for its diverse participants. In turn, it helps to clarify the class, gender, and imperial dimensions of both the royal tour and the British world c.1901.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.421

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0160.020
Scholarly communication0.0090.005
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.057
GPT teacher head0.317
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2018
Admission routes1
Has abstractyes

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