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Record W2335099622 · doi:10.1080/1683478x.2015.1115580

When a man flies overseas: corporate nationalism, gendered happiness and young Japanese male migrants in Canada and Australia

2015· article· en· W2335099622 on OpenAlexaboutno aff
Etsuko Kato

Bibliographic record

VenueAsian Anthropology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsHappinessNationalismGender studiesProject commissioningSociologyPublishingPolitical sciencePsychologySocial psychologyPoliticsLaw

Abstract

fetched live from OpenAlex

For more than 10 years, the number of Japanese women who live or emigrate overseas has been surpassing that of Japanese men. On the other hand, corporate workers who have been relocated overseas for shorter periods by their companies are predominantly Japanese men. What this means is that Japanese men are more bound to their homeland and, in this sense, more domestic than Japanese women. Especially since 2010, the state-driven development of “Global Human Resources” (GHR) has been intensifying the familiar associations between men, corporations, and going overseas, which re-impose the nationalistic, corporate-centric masculine norm on young men’s minds. This does not mean, however, that all men in Japan fit the corporate worker model, or that they are all content with Japanese society. Based on interview data of Japanese temporary residents in their 20s, 30s, and 40s in Canada and Australia, with special focus on the narratives of men, this paper elucidates how the meaning of going/being overseas for personal happiness is both gendered and classed.

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 score0.092
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0170.006
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.080
GPT teacher head0.331
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 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

Citations8
Published2015
Admission routes1
Has abstractyes

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