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Debating Multiculturalism

2022· book· en· W4220893245 on OpenAlexaff
Patti Tamara Lenard, Péter Bálint

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMulticulturalismMinority rightsReasonable accommodationNeutralityAccommodationPoliticsDemocracyInclusion (mineral)Context (archaeology)Political scienceLaw and economicsLawSociologyPrivilege (computing)Political economyGender studiesPsychologyHistory

Abstract

fetched live from OpenAlex

Abstract Multiculturalism has been subject to backlashes across democratic states. These voices argue that after years of accommodation, minorities have failed to integrate and ought to be encouraged more forcefully to abandon norms and values that are in tension with those of their broader society. In this context, Debating Multiculturalism brings together two prominent scholars of the political theory of multiculturalism. Both agree with the need for minority accommodation in liberal democracies, but disagree on the pathway forward. Patti Tamara Lenard argues that multiculturalism must be robustly defended. Lenard argues that the accommodation of cultural and religious practices is key to achieving substantive political inclusion in democratic states. Rather than generating segregation and separation, the accommodation of such practices ensures that minorities can participate across multiple domains of politics as equal citizens. She examines claims for cultural preservation, too, and argues that an emphasis on political inclusion can explain why preservationist claims should be respected. In contrast, Peter Balint argues against the need for minority rights in multicultural contexts. Balint defends a radical form of neutrality, “active indifference,” which can achieve the accommodation of minority ways of life, without recourse to minority rights. He argues that if the problem arises because of a favoring of majority ways of life, then rather than add minority rights as a solution, majority privilege should simply be removed. This solution is not only fairer, but avoids many of the problems that have plagued minority rights. The book concludes with both authors critiquing each other’s positions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.130
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0340.001

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 head0.033
GPT teacher head0.341
Teacher spread0.308 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2022
Admission routes1
Has abstractyes

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