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Record W1998527010 · doi:10.1002/psp.615

Social networks and selectivity in Brazilian migration to Japan and the United States

2010· article· en· W1998527010 on OpenAlex
Sarah Zell, Emily Skop

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePopulation Space and Place · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of British Columbia
FundersTinker Foundation
KeywordsDemographicsContext (archaeology)Ethnic compositionDemographic economicsComposition (language)Social network (sociolinguistics)Ethnic groupEconomic geographyAffect (linguistics)GeographyDevelopment economicsPolitical scienceSociologyEconomicsDemographyLaw

Abstract

fetched live from OpenAlex

Abstract This research analyses the composition of Brazilian migrants in two case studies, comparing the demographics of first‐time migrants over time in the network between Maringá, Brazil and Japan with that between Criciúma, Brazil and the US. Couched primarily within migrant social network theory, the research explores how the legal framework operating in each case influences the level and composition of Brazilian migration over time. Brazilian migration to Japan generally occurs within the context of a legally regulated ‘ethnic‐return’ guest worker program, whereas Brazilian migration to the US is largely unauthorised. The research shows that social networks do operate to diversify the migrant demographic composition over time in both migration flows. However, the development of and dependence on social networks appears stronger in migration to the US (at least initially), which suggests a relation between the legal context of the migration flow and the form and strength of its social networks. Copyright © 2010 John Wiley & Sons, Ltd.

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.

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 score0.733
Threshold uncertainty score0.983

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.288
Teacher spread0.280 · 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