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Record W4288033990 · doi:10.1017/s0008423922000403

Nationalism, Membership and the Politics of Minority Claims-Making

2022· article· en· W4288033990 on OpenAlexafffund
Keith Banting, Allison Harell, Will Kymlicka

Bibliographic record

VenueCanadian Journal of Political Science · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversité du Québec à MontréalQueen's University
FundersCanadian Institute for Advanced Research
KeywordsPoliticsNationalismIndigenousImmigrationPolitical scienceMinority rightsSociologyPerceptionLawSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Abstract Previous research has shown that the public tends to see some groups as less deserving of social rights. Our focus in this article is whether they are also seen as less entitled to engage in political claims-making. Recent theorists of inclusive nationalism argue that whether minorities are seen as having the right to codetermine the future may depend on whether the majority believes minorities are morally committed to the nation. Drawing on a unique survey experiment, we test this intuition by analyzing how majority perceptions of a minority's commitment to the larger society influence support for claims-making by immigrants and national minorities. We show that immigrants, French-speaking Quebeckers, and Indigenous peoples are judged more harshly about their right to make claims and that this is in part explained by the majority's views that these groups are not, in fact, committed members of the larger political community.

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)0.006
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.009
Scholarly communication0.0050.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.039
GPT teacher head0.350
Teacher spread0.311 · 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

Citations15
Published2022
Admission routes2
Has abstractyes

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