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Record W2616136528 · doi:10.1177/0022022117709983

Understanding the Relation Between Participating in the New Culture and Identification: Two Studies With Latin American Immigrants

2017· article· en· W2616136528 on OpenAlexaff
Diana Cárdenas, Roxane de la Sablonnière

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2017
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIdentification (biology)ImmigrationAcculturationRelation (database)Scope (computer science)SociologyLatin AmericansPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

Participation in a new culture and identification with a new culture are important issues faced by millions of immigrants today. Literature describes three possible relations between participation and identification. First, some researchers postulate that they are part of the basic acculturation phenomenon and hence equivalent (Model 1). Others postulate that either identification with a new culture encourages participation in it (Model 2) or participation helps identification with a new culture (Model 3). The goal of the present article was to determine which model best describes the relation between participating in a new culture and identification with it. In Study 1, Latin American immigrants ( N = 146) answered a questionnaire, and the fit of each of the three models was compared using path analyses. Results showed that the best fitting model was one where participation in the new culture positively predicted identification with it. These results were confirmed in Study 2, where semistructured interviews of 15 immigrants were analyzed. The two studies in the present article help us understand the relation between participation in the new culture and identification as well as the scope of the changes brought on by immigration.

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)0.001
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 score0.051
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.446
GPT teacher head0.555
Teacher spread0.109 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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