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Record W4410907526 · doi:10.1111/nana.13137

Perceptions of Diversity: “Multicultural Values” and Living Well Together

2025· article· en· W4410907526 on OpenAlexafffundabout
Lori G. Beaman

Bibliographic record

VenueNations and Nationalism · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Ottawa
KeywordsMulticulturalismDiversity (politics)PerceptionSociologyCultural diversityPolitical sciencePsychologyAnthropologyPedagogy

Abstract

fetched live from OpenAlex

ABSTRACT Situated in the institutional support for Canadian multiculturalism and the academic tensions over the alleged decline of multiculturalism, this paper considers the use of multiculturalism and its associated values in everyday life. In the Canadian context, there has been an expansion of multiculturalism beyond “ Charter values” towards “multicultural values” which shapes social relations and informs the ways that some Canadians see themselves, the conduct of good citizens, and the national imaginary. These values are articulated as equality (or equity), diversity and inclusion, and they have at least partially rescued multiculturalism from some of its alleged failings. Drawing on interview data from Toronto collected as part of the “A Transcultural Approach to Belonging and Engagement among Migrant Youth”, the paper explores perceptions and use of multiculturalism and its associated values.

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)0.005
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0170.022
Scholarly communication0.0090.003
Open science0.0010.011
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.308
Teacher spread0.293 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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