Book Review: Containing Diversity: Canada and the Politics of Immigration in the 21st Century
Bibliographic record
Abstract
As a country that has historically used immigration as part of its nation-building and demographic growth strategies, Canada has never been immune to shifting trends in the international migration landscape.In recent years, a global pandemic, wars, economic crises, climate change, a growing number of asylum seekers, and a global "race for talent" have proven that defining immigration according to "national" policy parameters is not realistic.In the context of these complex phenomena, immigration policies in Canada are marked by two major trends: humanitarian and economic.The former requires as much openness and inclusion as countries can offer, whereas the latter focuses on selection and filtering of immigrants based on talent.Following these two trends, the shifts in Canada's policies that determine who is a member of Canada and how this membership is defined reflect the interplay between inclusion and exclusion in a liberal democratic context.Is it possible to be an inclusive nation with policies that promote liberal values, such as pluralism and human rights, while also implementing mechanisms to control mobility and membership?Containing Diversity: Canada and the Politics of Immigration in the Twenty-First Century is about this struggle between "embracing" and "containing" diversity in Canada.It is "a tale of two Canadas," where an emphasis on liberal democratic values co-exists with market-oriented neo-liberalism.It focuses on the challenge Canada faces in trying to balance two clashing tendencies within neo-liberalism: the logic of open global markets that encourages free movement of both goods and humans, and the logic of control that promotes security measures and the criminalization of movement.The authors, Yasmeen Abu-Laban, Ethel Tungohan, and Christina Gabriel, three prominent migration scholars, contrast the internationally renowned and positive image of Canada as a country that facilitates immigration and values diversity with an alternative portrait of Canada with deliberate policies and mechanisms in place to select "desired citizens" and leave out the "less-desired" ones.In this portrait, the former includes those who are educated, highly skilled, and economically independent, and the latter consists of others with a high potential of becoming a "burden" for the welfare state.The changes in Canadian policies and politics reflect the efforts to limit inclusion to those who, Canada claims, deserve to be included.This limited inclusion that creates a hierarchy of immigrants is what the authors call "containing diversity."In eight chapters, the authors explore how this novel concept works in the Canadian immigration context.In Part I, consisting of two chapters, the authors offer a rich
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.034 | 0.014 |
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".