What do we have in canon? : Chinese Canadian anthologies and the posit(ion)ing of an ethno-national literary canon and its contexts
Bibliographic record
Abstract
Chinese Canadian anthologies are sites for negotiating community boundaries, positing coalitions, deconstructing social and literary institutions, and asserting legitimacy. They pose the question, What do we have in canon?, by interrogating the representation of Chinese Canadian writers in the existing canon and by offering an alternative canon for consideration. I propose the term "ethno-national literature" to account for the ethno-racial and national distinctiveness of the literary category "Chinese Canadian." While recent scholarly work has been directed toward conceptualizing "Asian Canadian" and "Asian North American" as disciplinary areas of study within English, it does not address the issue that specific ethno-racial groups continue to identify themselves in categories such as "Chinese Canadian" or "Japanese Canadian." This thesis considers the theoretical potential of Chinese Canadian anthologies as texts which articulate rhetorical community. I examine five anthologies of Chinese Canadian literature, Inalienable Rice (a collaboration between Chinese and Japanese Canadian artist-activists, 1979), Many-Mouthed Birds (1991), Jin Guo (1992), Swallowing Clouds (1999) and Strike the Wok (2003), in comparison with three Oxford anthologies of Canadian literature to consider how Chinese Canadian anthologies act as culturally-resistant, canon-forming texts.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.042 | 0.027 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".