Bibliographic record
Abstract
<JATS1:p>Associations between the cheongsam dress and Chinese cultural identity are well known but what are the meanings of the cheongsam for members of the Chinese diaspora? In a study grounded in first-hand accounts of wearing, Cheryl Sim explores the practices and experiences of women in Canada, a major Chinese diaspora, and carries out the first in-depth study of the cheongsam from this critical point of view.</JATS1:p> <JATS1:p>Questions explored over the course of 20 interviews, as well as during personal reflections on the author’s own experiences of wearing, include: is there a desire to re-claim or appropriate the cheongsam? Does this desire risk perpetuating stereotypes of Asian women? Does it undermine one’s identification with one’s host country? Can erased heritage(s) be accessed through dress? And how does wearing the cheongsam interact with the male gaze? Revealing feelings of repulsion and attraction, Sim combines personal stories with an authoritative use of theoretical frameworks such as feminism, post-colonialism and autoethnography.</JATS1:p> <JATS1:p>Covering issues such as heritage, ethnic identity, authenticity, nationalism, patriarchy and assimilation, Sim demonstrates that the meanings of the cheongsam are multifarious. Readable but with strong academic underpinnings, this book is the entry point into discussions of Chinese dress and diaspora.</JATS1:p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".