“Whiteness,” Prejudice, and the Consolidation of an Anglo-American Elite in Nineteenth-Century Hong Kong
Bibliographic record
Abstract
Abstract Americans living in nineteenth-century Hong Kong and China's treaty ports encountered a contradiction. The British dominated elite foreign society, their political, social, and cultural agendas often setting the pace for life within the community. But as citizens of a country that had recently wrested its independence from its one-time imperial overlord, Americans arriving in China were ostensibly averse to imperialism and the culture of empire. They maintained a belief that theirs was a benevolent republic that championed international amity and self-determination. Still, as Elisa Tamarkin notes, if Americans were wary of the British Empire, many found the spectacle of it appealing—a tendency evident in Hong Kong and the foreign enclaves along China's coast. Americans eager to enter elite foreign society proclaimed newfound sympathies for British belligerence in China, in turn developing increasingly prejudiced opinions about their Chinese neighbours and staff. Their derisive expressions of racial difference reinforced efforts to reconcile Anglo-American cultural incongruities. Such sentiments reflect the entangled processes through which extraimperial groups such as Americans fashioned themselves as members of the colonial elite. I argue that through such processes, the British and Americans subordinated national rivalry in the interest of entrenching racial divisions between white and non-white communities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".