The Transcultural Streams of Chinese Canadian Identities
Bibliographic record
Abstract
Highlighting the geopolitical and economic circumstances that have prompted migration from Hong Kong and mainland China to Canada, The Transcultural Streams of Chinese Canadian Identities examines the Chinese Canadian community as a simultaneously transcultural, transnational, and domestic social and cultural formation. Essays in this volume argue that Chinese Canadians, a population that has produced significant cultural imprints on Canadian society, must create and constantly redefine their identities as manifested in social science, literary, and historical spheres. These perpetual negotiations reflect social and cultural ideologies and practices and demonstrate Chinese Canadians' recreations of their self-perception, self-expression, and self-projection in relation to others. Contextualized within larger debates on multicultural society and specific Chinese Canadian cultural experiences, this book considers diverse cultural presentations of literary expression, the “model minority” and the influence of gender and profession on success and failure, the gendered dynamics of migration and the growth of transnational (“astronaut”) families in the 1980s, and inter-ethnic boundary crossing. Taking an innovative approach to the ways in which Chinese Canadians adapt to and construct the Canadian multicultural mosaic, The Transcultural Streams of Chinese Canadian Identities explores various patterns of Chinese cultural interchanges in Canada and how they intertwine with the community's sense of disengagement and belonging. Contributors include Lily Cho (York), Elena Chou (York), Eric Fong (Chinese University of Hong Kong), Loretta Ho (Toronto), Jack Leong (Toronto), Jessica Tsui-yan Li (York), Lucia Lo (York), Guida Man (York), Kwok-kan Tam (Hang Seng Management College), Eleanor Ty (Wilfrid Laurier), and Henry Yu (British Columbia).
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.041 | 0.021 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".