Selling Diversity: Immigration, Multiculturalism, Employment Equity, and Globalization/The House of Difference: Cultural Politics and National Identity in Canada
Bibliographic record
Abstract
Yasmeen Abu-Laban and Christina Gabriel, Selling Diversity: Immigration, Multiculturalism, Employment Equity, and Globalization (Peterborough: Broadview Press, 2002), 202pp. Paper. £12.99. ISBN 1-5511-1398-8. Eva Mackey, The House of Difference: Cultural Politics and National Identity in Canada (Toronto: University of Toronto Press, 2002), xxii + 199pp. Paper. £14. ISBN 0-8020-8481-8. Canadian society has changed considerably in recent years, due most importantly to globalisation and neo-liberalism. The 2001 census revealed that Canada is one of the most racially and ethnically diverse countries in the world. This is partly due to the increased migration flows associated with globalisation, but also to state policies relating to diversity. Thus, while many argue that globalisation and neo-liberalism threaten Canadian sovereignty, ironically they might simultaneously be contributing to a more concrete understanding of, and sense of attachment to, the Canadian identity. As many now recognise and argue, diversity is at the core of this identity. Public opinion polls show that Canadians are proud of this sense of diversity, for it reflects admirable qualities: tolerant, accepting, and caring. They argue that Canadians have a long history of embracing diversity, from First Nations to francophone Canadians to the latest wave of 'new Canadians'. Members of the political class repeatedly refer to such values. Diversity is a key part of the federal government's articulation of 'Brand Canada' and 'the Canadian Way'. However, when you probe such attitudes and expressions, a growing sense of discomfort emerges. For example, despite the Prime Minister's proclamations, the Chretien government introduced radical changes to the Indian Act, changes rejected by most Aboriginal Canadians. Post-9/11 initiatives, such as a national identity card for landed immigrants, have also made many Canadians uncomfortable. There are ongoing concerns about institutional racism in the police and judicial systems, and there is considerable evidence that racial minorities suffer from what the Canadian Race Relations Foundation calls 'hidden discrimination' in employment and income, this despite the higher education levels of recent immigrants. Similarly, public opinion polls reveal considerable 'hard line' attitudes on a variety of issues: immigration (especially its racial and ethnic dimension), racial profiling, the rights of Aboriginal peoples, and official bilingualism. It is clear that the daily experiences of many Canadians do not reflect the hype, goodwill or pride articulated by Canadians and their governments. These two excellent books help us understand how diversity has become central to the rearticulation of Canadian nationalism and add to our understanding of these complex issues. As such, they are contributing to a new critical lens for understanding Canada. They tackle similar themes and issues, offering comprehensive overviews of how Canadians and their governments use diversity in the framing of Canadian nationalism and identity. Both books clearly show that the practice of diversity is not nearly as noble as the expression of the positive values linked with diversity. Mackey's examination of the construction of the Canadian national identity rests on what she calls 'the myth of tolerance'. …
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".