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Record W4410765074 · doi:10.1177/00104140251342924

Inclusive Redistribution and Perceptions of Membership: A Cross-National Comparison

2025· article· en· W4410765074 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComparative Political Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsQueen's UniversityUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institute for Advanced Research
KeywordsRedistribution (election)PerceptionPolitical scienceDemographic economicsPoliticsSocial psychologyPsychologyEconomicsLaw

Abstract

fetched live from OpenAlex

Immigrants tend to be seen as less deserving of welfare benefits than native-born citizens, but little consensus exists to explain this finding or how to build greater public support for more inclusive policies. Recent work suggests that support for redistribution may be tied to citizens' perceptions of the "membership commitment" of immigrants. This study provides the first systematic test of this hypothesis in the comparative setting using an original seven country survey conducted in 2021-2022. The survey explored perceptions of immigrants' membership commitment in the host society in seven liberal democracies and their effect on public support for the extension of social benefits to immigrants. The study shows that immigrants systematically suffer a "membership penalty" within host societies across a wide range of states with different citizenship and welfare regimes, with important consequences for welfare state support.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
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 score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.133
GPT teacher head0.541
Teacher spread0.408 · 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