Racial Performance at Sea: Race, Region, and Empire on the Empress of Australia
Bibliographic record
Abstract
This article examines the 1928–1929 world cruise of the Empress of Australia, a ship owned by the Canadian Pacific Railway Company. Drawing upon concert programs, passenger accounts, Canadian Pacific official publications, and historical newspapers, it focuses on a concert that happened while the ship was at sea. It examines three songs—“Ol’ Man River,” “Hawaiian Memories,” and “Chu Chin Chow”—to show how nostalgia for the American South found purchase beyond US borders next to representations of a mysterious “Orient” and tropical Pacific. Situating this voyage within the larger context of Canadian nationhood and the Canadian Pacific’s investment in the British empire, I argue that the combination of these songs on a ship bound for sites of white empire did two things. One, it reassured white passengers that the racial order of the southern past would continue in the present. Second, it reinforced their experiences in China, Hawai'i, and other stops during the cruise. Through their depiction of Blacks and Asians as submissive and alien, these songs collectively romanticized and exoticized people of color and the places they inhabited—whether living in the wake of slavery in the American South or under US and British imperialism in the Pacific. Ultimately, this article demonstrates the importance of the transnational for understanding the export of nostalgic representations of the American South and how they adopted new meaning outside of a US context.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".