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Record W4402895271 · doi:10.1111/glob.12510

Navigating Stepwise Lifestyle Mobilities via the Global South: Japanese Migrant Families’ Negotiation of Educational and Lifestyle Aspirations in Malaysia

2024· article· en· W4402895271 on OpenAlexfundno aff
Hiroki Igarashi

Bibliographic record

VenueGlobal Networks · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceUniversité Laval
KeywordsMobilitiesNegotiationMigrant workersSociologyGender studiesGeographyEconomic growthAnthropologySocial science

Abstract

fetched live from OpenAlex

ABSTRACT Studies of the transnational migration of East Asian families have examined how they enhance their status and well‐being by moving their children to schools in Western anglophone countries. Although recent studies have identified Southeast Asia as a new, affordable destination for less affluent families, we do not know their future transnational trajectories. To fill this gap, this study employed interview data from 46 Japanese families who had migrated to Malaysia with their children and investigated how they navigated their transnational mobilities from Malaysia. To explain their pattern, I introduce the concept of ‘stepwise lifestyle mobilities’, transnational mobility pathways adopted by relatively affluent people from developed countries, who may face constraints due to factors such as race, ethnicity, limited global experience or financial limitations but a desire for an international experience. They start from a low‐cost, low‐risk country like Malaysia and seek staged lifestyle migration regionally and/or globally.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.283
Teacher spread0.272 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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