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Record W4313570431 · doi:10.1111/imig.13111

Multiple routes to immigration scepticism: The association between individual grievances and anti‐immigrant attitudes in Canada, Germany and the <scp>USA</scp>

2023· article· en· W4313570431 on OpenAlexaffabout
Daniel Stockemer, Daphne Halikiopoulou

Bibliographic record

VenueInternational Migration · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Ottawa
FundersKonrad-Adenauer-Stiftung
KeywordsImmigrationSkepticismPoliticsSurvey data collectionValue (mathematics)Association (psychology)World Values SurveySociologyDemographic economicsSocial psychologyPolitical sciencePsychologyEconomicsLawEpistemology

Abstract

fetched live from OpenAlex

Abstract This article theorizes and tests the association between the ego‐tropic and socio‐tropic dimensions of three sets of grievances, that is, economic, value‐based and security‐related, and anti‐immigrant attitudes using data from an original survey fielded in Canada, Germany and the USA. Our analysis confirms the presence of multiple paths towards anti‐immigration attitudes. Our contribution is threefold. First, we offer a nuanced understanding of the complexity of immigration scepticism and shed light on its different dimensions, including the under‐researched personal value‐based and collective security‐related. Second, we make an empirical contribution by confirming the multi‐faceted nature of anti‐immigrant attitudes using data from an original survey tailored specifically to our research questions. This allows us to examine each set of grievances independently of each other and independently of anti‐immigrant attitudes. Third, our survey enables us to identify country‐specific dynamics by testing the relationship between individual grievances and anti‐immigrant attitudes in diverse political settings.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.283
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.274
Teacher spread0.259 · 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 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

Citations9
Published2023
Admission routes2
Has abstractyes

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