Competing interests: Toronto's Chinese immigrant associations and the politics of multiculturalism
Bibliographic record
Abstract
Abstract Social service agencies and advocacy groups have played an integral role in mediating between the Asian ethnic populations. In the Canadian institutional setting, associations become a means of political expression. Canada incorporates new immigrants into its national institutions. However, these neo‐liberal institutions and policies have not redressed major problems arising in the settlement process. Under Canada's discourse of enlightened multiculturalism, social service agencies are funded to help to integrate diverse peoples. The policy of multiculturalism meshes well with the liberal ideology underlying loose coupling, encouraging people to retain their cultural identities while settling and participating in national processes. These policies are designed to be sensitive to clients' cultural backgrounds; however, there are unforeseen consequences. In this system, different groups are granted different amounts of social, cultural and economic capital along with differential access to this capital, which affects their position and potential for action in other arenas. In particular, we find that the social service approach treats new Chinese immigrants as similar, thereby fostering competition between subgroups over leadership, funds and representation. Our data come from interviews with key figures in the Chinese‐Canadian community and associations, and reviews of press and other media. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 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".