MétaCan
Menu
Back to cohort
Record W3036690486 · doi:10.1080/01436597.2020.1761252

Automotive global value chains in Mexico: a mirage of development?

2020· article· en· W3036690486 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThird World Quarterly · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBackwardnessAutomotive industryDeindustrializationCapital (architecture)EconomicsArgument (complex analysis)Value (mathematics)EconomyInternational tradeBusinessEconomic growthGeographyEngineering

Abstract

fetched live from OpenAlex

International monetary organisations argue the ‘developing countries’ should foster linkages to the world economy as a means to overcome backwardness. In this article we refute the narrative that Mexico has experienced industrial upgrading. Rather, industrial growth in Mexico over the last 40 years has been shaped by neoliberal economic policies which have turned the Mexican economy into an export-led manufacturing platform designed to supply the North American market, sustained by a precarious labour market. As a result, Mexico occupies the most labour-intensive and low value-added segments of regional production chains. To make this argument, we perform an in-depth analysis of the Mexican automotive industry, demonstrating that instead of being an engine for domestic industrial development, the auto industry has become a dominant economic sector through productive hyper-specialisation concentrated in the northern Mexican border states, a reliance on transnational capital, particularly from the United States, a disconnect with domestic markets, and the super-exploitation of labour.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.261
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.253
Teacher spread0.234 · 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