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Record W2256342424

Transformative Multiculturalism: Irish Minorities and National Identity in Hard Times

2010· article· en· W2256342424 on OpenAlexaff
Catherine Frost

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMulticulturalismSolidaritySociologyRedistribution (election)IrishLaw and economicsDilemmaEpistemologyPolitical economyPolitical scienceLawPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

One of the objections to multiculturalism is the idea that it undermines social solidarity and thereby makes redistribution and social justice more difficult to achieve. The argument holds that the overarching union behind the multicultural project is over-taxed by the very project it is asked to support and that to counteract its effects there must be an enhanced focus on “civic integration” (Joppke, 2004, 243). David Goodhart coined the term the “progressive’s dilemma” to describe this effect which says that circumstances force us to choose between a multiculturalist approach that divides us and a national unity approach that binds us together behind a common good (Goodhart 2005, 156; Kymlicka and Banting 2006, 283-9).1 If such an effect exists, it means that multiculturalist states will struggle when it comes to coping with “hard times” especially in the form of economic challenges. This paper argues that this is an unduly pessimistic view. While social solidarity is critical to redistribution during hard times, and while multiculturalism does introduce changes to these relations, the critique is based on a view of multiculturalism as cultivating cultural silos, based on essentialised ideal of a culture (Modood 2007, 97). But this does not adequately capture how multiculturalism works in practice.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.297
Teacher spread0.287 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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