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Record W2166394654 · doi:10.1080/14616696.2011.597869

DISCRIMINATION, EXCLUSION AND IMMIGRANTS' CONFIDENCE IN PUBLIC INSTITUTIONS IN EUROPE

2011· article· en· W2166394654 on OpenAlexaff
Antje Röder, Peter Mühlau

Bibliographic record

VenueEuropean Societies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsTrinity College
Fundersnot available
KeywordsImmigrationAcculturationEuropean Social SurveySocial exclusionEthnic groupDemographic economicsPublic institutionPolitical scienceQuality (philosophy)Survey data collectionSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

ABSTRACT What determines the confidence of immigrants in public institutions? Using pooled data from the European Social Survey of 26 countries, the study examines whether processes of social exclusion and discrimination can account for migrants’ confidence in public institutions. Specifically, it examines the role of the quality of public institutions and of the migrant integration policies of the host country and how they interact with migrant status and proxies for experienced or potential discrimination in shaping institutional trust. Results show that the performance of public institutions matters less for the confidence of immigrants than that of natives, in particular for those who see themselves as an ethnic minority or members of a group that has faced discrimination. Second-generation migrants exhibit less trust than first-generation migrants. However, discriminatory processes appear to be of less importance than the expectations carried from the home country or acculturation processes.

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)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.300
Teacher spread0.205 · 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 designObservational
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

Citations82
Published2011
Admission routes1
Has abstractyes

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