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The Impact of the State on Workers' Conditions—Comparing Taiwanese Factories in China and Vietnam

2004· article· en· W2232486850 on OpenAlexvenueno aff
Alexsia T. Chan, Wang Hz

Bibliographic record

VenuePacific Affairs · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Industrial and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsNewly industrialized countryChinaBusinessInternational tradeState (computer science)ScrutinyFinished goodReputationProduction (economics)Developing countryEconomic growthEconomicsPolitical science

Abstract

fetched live from OpenAlex

As Asia has become the fastest industrializing region in the world and as labour rights have become a controversial issue in the world’s trade agenda, the industrial relations of Asian factories that produce labourintensive goods for the global export market have come under scrutiny. Many of these factories have Taiwanese, Korean and Hong Kong owners, who hail from the so-called Newly Industrializing Countries (NICs). Today, these firms occupy a special place in the global production chain. Unlike many transnational corporations of the developed world that no longer manufacture goods but instead buy from offshore suppliers, these Asian corporations are the front-line producers in poorer foreign countries. Korean and Taiwanese managers are particularly known for their disciplinarian1 approach in their offshore factories, which have gained a reputation for harsh working conditions not only in Asia but also elsewhere

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 score0.150
Threshold uncertainty score0.299

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.269
Teacher spread0.253 · 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

Citations50
Published2004
Admission routes1
Has abstractyes

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