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Record W2801660484 · doi:10.1080/01419870.2018.1444190

Beyond multiculturalism: interculturalism, diversity and urban governance

2018· article· en· W2801660484 on OpenAlexaff
Nergis Canefe

Bibliographic record

VenueEthnic and Racial Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Social Issues and Migration
Canadian institutionsYork University
Fundersnot available
KeywordsInterculturalismMulticulturalismDiversity (politics)Inclusion (mineral)Context (archaeology)SociologyCorporate governanceArgument (complex analysis)Gender studiesRefugeePolitical scienceAffirmative actionPublic administrationLawAnthropologyGeographyManagement

Abstract

fetched live from OpenAlex

This review article discusses the volume by Giovanna Marconi and Elena Ostanel, eds. The Intercultural City: Migration, Minorities and the Management of Diversity, I.B. Tauris, 2016, in the larger context of studies on inclusion of migrants in cities. It evaluates the merits of interculturalism argument presented by the editors and contributing authors as it is applied to the migrants’ and refugees’ needs and demands from the city and public at large, and the transformation of identities of public spaces challenging assumptions of cultural uniformity at the national level. The issue of the viability of equitable and normatively justifiable governance of difference above and beyond multiculturalism is a very important one, especially so in an era where Deferred Action for Childhood Arrivals and expulsions of the Dreamers from the American cities have become part of our daily reality.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0030.019
Scholarly communication0.0110.006
Open science0.0010.006
Research integrity0.0020.003
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 head0.072
GPT teacher head0.375
Teacher spread0.303 · 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 designTheoretical or conceptual
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

Citations2
Published2018
Admission routes1
Has abstractyes

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