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Record W3212834593 · doi:10.1093/sf/soab125

Legal Cynicism and System Avoidance: Roma Marginality in Central and Eastern Europe

2021· article· en· W3212834593 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

VenueSocial Forces · 2021
Typearticle
Languageen
FieldHealth Professions
TopicRomani and Gypsy Studies
Canadian institutionsUniversity of Toronto
FundersWeatherhead Center for International Affairs, Harvard UniversityUniversity of TorontoHarvard University
KeywordsCynicismDisadvantageInequalityFace (sociological concept)SociologyPolitical scienceSocial psychologyCriminologyPsychologyLawSocial sciencePolitics

Abstract

fetched live from OpenAlex

Abstract The Roma are Europe’s largest minority group and face extensive discrimination across the continent. Drawing on a survey of Roma and non-Roma households in twelve Central and Eastern European countries, we analyze the extent to which legal cynicism, as a cognitive frame, is connected to the avoidance of helpful social institutions. We thus expand existing research on legal cynicism to focus on individuals’ contacts with potentially helpful institutions that can buffer inequality. We conclude that the interplay of legal cynicism and system avoidance, which have provided deep insights into the reproduction of structural disadvantage in American cities, also provide us with international insights into the causes of inequality and minority disadvantage across hundreds of towns in Central and Eastern Europe. In this way, legal cynicism and system avoidance work to reproduce durable inequality.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.595

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)0.0000.000

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 head0.039
GPT teacher head0.367
Teacher spread0.328 · 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