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Record W2051412411 · doi:10.1177/0021909613493601

Globalization and Sustainability of Japan’s Internal Labor Markets: Foreign Direct Investment (FDI) and Wages at Japanese Manufacturing Firms

2013· article· en· W2051412411 on OpenAlexaff
Masao Nakamura

Bibliographic record

VenueJournal of Asian and African Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Industrial and Economic Development
Canadian institutionsUniversity of British Columbia
FundersUniversity of TokyoJohns Hopkins University
KeywordsForeign direct investmentWageLabour economicsGlobalizationBusinessSustainabilityEconomicsInvestment (military)Value (mathematics)Market economy

Abstract

fetched live from OpenAlex

Both inward and outward foreign direct investment (FDI) have implications for the wage rates of home-country workers. Such implications have been particularly noteworthy in Japan where the traditional internal labor-market practices, which value long-term sustainability of employment and wages, collide with the pressure for change in the globalizing Japanese economy on many fronts. In this paper we estimate the impacts of FDI on workers’ wages in Japanese manufacturing industries. We find that Japanese employees benefit, in the form of wage gains, from their employers’ association with both inward and outward FDI operations. These wage effects differ systematically depending on gender and worker ranks within their employer firms and are likely to weaken the mechanisms underlying the sustainability of Japanese firms’ traditional internal labor markets. The presence of FDI effects on worker wages also implies an increasing disparity between the incomes of workers who work for successfully globalizing firms and workers who do not, jeopardizing Japan’s traditional policy objective to sustain harmonious economic growth across all economic sectors. This would also deepen the structural divide including the wage gap of the Japanese economy that exists between large firms and small- and medium-size enterprises (SMEs) since firms which get involved in FDIs are mostly large firms.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.263
Teacher spread0.246 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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