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Record W2904486776 · doi:10.4324/9781315537276-9

Migration, immigration, and settlement within the Pacific Basin

2017· book-chapter· en· W2904486776 on OpenAlexaboutno aff
Sarah England, Michael Weiner

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)ImmigrationPacific basinGeographyStructural basinOceanographyGeologyArchaeologyBusinessGeomorphology

Abstract

fetched live from OpenAlex

Migration between Asia and the Americas has involved movement from Asia to North America and Latin America, and more recently from Latin America to Asia. This chapter provides a framework for understanding the role of migration in the evolution of the Pacific Basin. By the end of the century the emergence of Japan and the US as colonial powers generated new migrations throughout the Pacific Basin. During and after World War II, the US introduced legislation that permitted naturalization for Chinese, Filipino, and Asian Indian residents. This was followed by the Immigration Act of 1965 which ended policies that had privileged migration from European countries. The countries of the Americas were created through migration of peoples from Europe, Africa, and Asia and thus have national narratives that emphasize settlement and assimilation. While much migration to the Americas initially came from overseas, today the dominant trend is migration from Latin America to the US and Canada.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.267
Teacher spread0.251 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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