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Record W2468315166 · doi:10.1002/ijop.12290

Mediating and moderating processes in the relationship between multicultural ideology and attitudes towards immigrants in emerging adults

2016· article· en· W2468315166 on OpenAlexaff
Pasquale Musso, Cristiano Inguglia, Alida Lo Coco, Paolo Albiero, John W. Berry

Bibliographic record

VenueInternational Journal of Psychology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsQueen's University
Fundersnot available
KeywordsMulticulturalismImmigrationIdeologyContext (archaeology)PsychologySocial psychologyStructural equation modelingPoliticsSociologyPolitical scienceGeographyPedagogy

Abstract

fetched live from OpenAlex

Few studies examine intercultural relations in emerging adulthood. Framed from the perspective of the Mutual Intercultural Relations in Plural Societies (MIRIPS) project, the current paper examined the mediating role of tolerance and perceived consequences of immigration in the relationship between multicultural ideology and attitudes towards immigrants. Additionally, the moderating role of context was analysed. A two-group structural equation modelling was performed on data collected from 305 Italian emerging adults living both in northern and in southern Italy with different socio-political climates towards immigrants. In both groups, tolerance and perceived consequences of immigration mediated the relationship between multicultural ideology and attitudes towards immigrants. Also, this indirect relationship was significantly higher for the northern than southern Italians. These findings provide provisional evidence of mediating and moderating processes in the relationship between multicultural ideology and attitudes towards immigrants and suggest important implications for practitioners interested in promoting intercultural relations among emerging adults.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.079
GPT teacher head0.438
Teacher spread0.359 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

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