Clothing the “Chinese Lady” in “Her New English Garb”: Thomas Percy’s <i>Hau Kiou Choaan</i> (1761) and the Naturalization of Chinese Fiction in Eighteenth-Century Britain
Bibliographic record
Abstract
Hau Kiou Choaan, an English translation of the seventeenth-century Chinese fiction Haoqiu Zhuan, attained recognition from publishers after Thomas Percy made substantial alterations. Percy and his fellow writers referred to this process as “naturalization.” This article explores Percy’s translation and editing practices within the context of the eighteenth-century debates on naturalization acts. The naturalization of Chinese fiction, as embodied in alterations, annotations, and character adjustments, mirrors the complexities inherent in the struggles of naturalizing foreigners in Britain. Percy’s editorial endeavours also reflect his desire to regulate and reshape both the Chinese literary genre and its Chinese characters. Instances of mistranslation and additional cultural footnotes in Percy’s English version further underscore the Chinese text’s resistance to complete naturalization and the difficulties involved. Percy and his publishers’ treatment of this Chinese work reveals the intricate dynamics of debates over citizenship, belonging, and the reception of foreign literature featuring non-British characters.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".