Bibliographic record
Abstract
Abstract. Confucius Institutes (CIs), modelled on similar European organizations, promote China’s official national language and culture abroad. Unlike their European counterparts, however, the interactions between CIs and Canadian audiences are haunted by complex histories of a racialized “Oriental Other” in Canada and “Western Other” in China. Through ethnographic research on the Confucius Institute in Edmonton and the CI Headquarters in Beijing, this paper explores racialized representations of China and Chinese culture, as well as racialized understandings of the desired Western audience, in both locations. I argue that representations of Chinese culture are caught between two competing logics which I term reorientalism and reorientality. Reorientalism attempts to reclaim definitions of Chineseness and redress misunderstandings about China while simultaneously making China comprehensible and ultimately marketable through reorientality, or a use of familiar Orientalist tropes. Canadians (most often imagined and represented as white) are encouraged to engage with this reorientality through their own performance and embodiment of Chinese culture (a conceptually distinct process I call re-orientality) as a means of understanding the project of reorientalism. However, the spectacle of Chinese culture through CIs resonates with Canadian multiculturalism in ways that may unintentionally reproduce a social landscape that normalizes whiteness and the consumption of ethnicized Otherness.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".