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Ethnic, Linguistic, and Multicultural Diversity of Canada

2010· book-chapter· en· W2726001367 on OpenAlexaffabout
Will Kymlicka

Bibliographic record

VenueOxford University Press eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsQueen's University
Fundersnot available
KeywordsMulticulturalismEthnic groupDiversity (politics)Cultural diversityDemocracyPoliticsPolitical scienceGender studiesCitizenshipPessimismSociologyLaw

Abstract

fetched live from OpenAlex

Abstract In the past twenty years, there has been a growing pessimism on the effects of ethnic diversity. Studies are dominated by the assumption that ethnic diversity is a problem along multiple dimensions. Studies also suggest that countries marked with high levels of ethnic diversity are less peaceful, less democratic, underdeveloped, and negligent to the needs of the poor. In short, ethnic diversity is seen as a dysfunction for modern societies, and is moreover viewed as a threat to political systems, as ethnic minorities are now seeking public recognition in the form of multiculturalism and minority rights. This article discusses ethnic diversity in Canada. Against the background of the pessimistic view on diversity, Canada is an exception. It contains high levels of ethnic, linguistic, and religious diversity. Moreover, although Canada supports multiculturalism and minority rights, it remains peaceful and enjoys a prosperous democracy with a reasonably well-developed welfare state. The Canadian experience suggests that the effects of ethnic diversity and identity politics are not predetermined, and that a multicultural form of citizenship is possible. In the following discussions of the article, the basic features of the Canadian approach to ethnic diversity, including the controversies and challenges of Canadian diversity, are examined.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.992
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.251
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations15
Published2010
Admission routes2
Has abstractyes

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