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Record W3006558745 · doi:10.1080/01419870.2020.1713391

The complementarity of multiculturalism and interculturalism: theory backed by Australian evidence

2020· article· en· W3006558745 on OpenAlexaboutno aff
Fethi Mansouri, Tariq Modood

Bibliographic record

VenueEthnic and Racial Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsInterculturalismMulticulturalismComplementarity (molecular biology)Diversity (politics)NormativeSociologyPoliticsGender studiesPluralism (philosophy)Political sciencePolitical economyEpistemologyLawAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

The decline of multiculturalism as a public discourse has been caused by various socio-political factors – such as 9/11 and its aftermath and the growth in migration – and new pro- and anti-diversity isms have been offered instead. One such pro-diversity discourse is interculturalism. Whilst some of its advocates, especially in Quebec and Europe, have seen it as a replacement of multiculturalism, a closer examination shows a high degree of complementarity. We demonstrate this by a theoretical-normative unpacking of multiculturalism and of the claims of interculturalism, and by evidence that Australian publics see multiculturalism as supportive of interculturalism, perceived as a renewal of multiculturalism. We express the hope that the sometimes oppositional debate between these two isms may now move forward into a phase of complementarity.

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)0.030
metaresearch head score (Gemma)0.069
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.069
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.008
Science and technology studies0.0050.023
Scholarly communication0.0080.011
Open science0.0020.011
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.000

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 head0.432
GPT teacher head0.566
Teacher spread0.134 · 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 designNot applicable
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

Citations67
Published2020
Admission routes1
Has abstractyes

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