Towards a Multilingual National Literature: The Tung Wah Times and the origins of Chinese Australian Writing
Bibliographic record
Abstract
Australian literature has over the last 50 years witnessed the gradual inclusion of writers and texts formerly considered marginal: from a predominantly white, Anglo canon it has come to incorporate more women writers, writers of popular genres, Indigenous writers, and migrant, multicultural or diasporic writers. However, one large and important body of Australian writing has remained excluded from histories and anthologies: literature in languages other than English. Is this the last literary margin? How might it be incorporated into the national canon, and how might it enhance our understanding of the cross-cultural traffic that feeds into the literature of a migrant nation? These are the questions explored in a project entitled ‘New transnationalisms: Australia’s multilingual literary heritage.’ The specific aim of the project is to trace the history of Australian writing in Chinese, Vietnamese, Arabic and Spanish (and to encourage and support other scholars to produce similar histories for other language traditions); beyond that, we want to chart new directions for thinking about the relationship between local and global cultural production, shaping while at the same time interrogating the category of the national.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".