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Record W3137857459

Membership without Social Citizenship? Deservingness and Redistribution as Grounds for Equality

2019· article· en· W3137857459 on OpenAlexaff
Michèle Lamont, Irene Bloemraad, Will Kymlicka, Leanne S. Son Hing

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsUniversity of GuelphQueen's University
Fundersnot available
KeywordsSolidarityCitizenshipRedistribution (election)PoliticsNormativeSociologySocial identity theoryPolitical scienceDistributive justicePolitical economySocial psychologySocial groupGender studiesEconomic JusticeSocial scienceLawPsychology
DOInot available

Abstract

fetched live from OpenAlex

This paper explores processes by which a broadening of legal, social and cultural membership in Western societies appears to be accompanied by a reduction in the social rights of citizenship, in part due to harsher judgements concerning the deservingness of low-income populations. As more diverse groups are extended formal national membership, fewer individuals appear deserving of social rights such as welfare redistribution. Why is this the case? Some explain this decline in solidarity as a simple, even mechanical response to growing diversity. We offer alternative approaches to understanding these tensions, and pathways for promoting inclusive membership and broad social rights. We do so by drawing on the analytical tools of four distinct fields that are rarely in dialogue, proposing that positive social change may emerge from (1) solidarity, explored by normative political theorists; (2) group identity and distributive justice, a focus for social psychologists; (3) boundary drawing and destigmatization, as analyzed by cultural sociologists; and (4) contestation and social movements, studied by political sociologists and political scientists.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.130
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
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 integrity0.0000.001
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 head0.058
GPT teacher head0.365
Teacher spread0.307 · 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

Citations22
Published2019
Admission routes1
Has abstractyes

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