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Trajectories of Multiculturalism in Germany, the Netherlands and Canada: In Search of Common Patterns

2010· article· en· W2001585585 on OpenAlexaboutno aff
Elke Winter

Bibliographic record

VenueGovernment and Opposition · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismImmigrationPolitical scienceDiversity (politics)NormativeScholarshipGender studiesEthnic groupSociologyCultural diversityPolitical economyLaw

Abstract

fetched live from OpenAlex

Abstract In the mid-1990s, Canadian scholarship introduced an important distinction between historically incorporated national minorities and ethnic groups emerging from recent immigration. While the former may be accommodated through federal or multinational arrangements, multiculturalism has come to describe a normative framework of immigrant integration. The distinction between these analytically different types of movements is crucial for Taylor's and Kymlicka's influential theories, but the relations between different types of national and ethnic struggles for rights and recognition have remained unexplored in much of the subsequent scholarly literature. This article starts from a theoretical position where different types of diversity are viewed as highly interdependent in practice. Tracing the trajectories of multiculturalism in three different countries, the article aims to identify common patterns of how changing relations between traditionally incorporated groups affect public perceptions of and state responses to more recent immigration-induced diversity. More specifically, it asks the following question: to what extent does the absence (in Germany), discontinuation (in the Netherlands) and exacerbation (in Canada) of claims on ethnocultural grounds by traditionally incorporated groups influence the willingness of the national majority/ies to grant multicultural rights to immigrants?

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0070.005
Scholarly communication0.0070.003
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations25
Published2010
Admission routes1
Has abstractyes

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