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Record W1560605888

Trade Liberalization and Industrial Pollution in Mexico: Lessons for the FTAA"

2001· article· en· W1560605888 on OpenAlexaboutno aff
Kevin P. Gallagher

Bibliographic record

VenueInternational Trade · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsFree tradeEnforcementEconomicsLiberalizationLatin AmericansInternational tradeDeveloping countryInternational economicsTertiary sector of the economyTrade diversionInternational free trade agreementEconomyEconomic growthMarket economyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

As the barriers to hemispheric trade and integration are lowered, it will be asked whether we will we hear the "giant sucking sound " of poorer nations luring U.S. and Canadian firms south to take advantage of low wages and lax environmental regulations? Or, will Latin American nations passively accept this problematical specialization in doing the world's cheap and dirty work? Mexico is the ideal laboratory for such research. Though NAFTA took effect in 1994, trade liberalization in Mexico began long before that. From 1982 to 1996 Mexico transformed itself from one of the most closed to one of the most open economies in the world. As a first step in such efforts, this paper looks at the relationship between industrial pollution and economic activity in Mexico, compares those results to the United States, and draws out implications for the FTAA. The study finds that many of the industries deemed the dirtiest in the world economy are actually cleaner in Mexico than in the US, and the industries labeled the cleanest are dirtier in Mexico. To generalize, this exhibits that trade liberalization can have both

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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.076
GPT teacher head0.255
Teacher spread0.179 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations7
Published2001
Admission routes1
Has abstractyes

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