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Record W1986051883 · doi:10.1111/0022-4537.00231

A Psychology of Immigration

2001· article· en· W1986051883 on OpenAlexaff
John W. Berry

Bibliographic record

VenueJournal of Social Issues · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsAcculturationMulticulturalismImmigrationSociologySettlement (finance)Social psychologyIntersection (aeronautics)Cultural psychologyRelation (database)Intercultural relationsFace (sociological concept)Social scienceEpistemologyPsychologyPolitical scienceAnthropologyLawGeography

Abstract

fetched live from OpenAlex

The discipline of psychology has much to contribute to our understanding of immigrants and the process of immigration. A framework is proposed that lays out two complementary domains of psychological research, both rooted in contextual factors, and both leading to policy and program development. The first (acculturation) stems from research in anthropology and is now a central part of cross‐ cultural psychology; the second (intergroup relations) stems from sociology and is now a core feature of social psychology. Both domains are concerned with two fundamental issues that face immigrants and the society of settlement: maintenance of group characteristics and contact between groups. The intersection of these issues creates an intercultural space, within which members of both groups develop their cultural boundaries and social relationships. A case is made for the benefits of integration as a strategy for immigrants and for multiculturalism as a policy for the larger society. The articles in this issue are then discussed in relation to these conceptual frameworks and empirical findings.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.021
Scholarly communication0.0050.005
Open science0.0000.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.069
GPT teacher head0.499
Teacher spread0.430 · 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 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

Citations1,574
Published2001
Admission routes1
Has abstractyes

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