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Record W2771565940 · doi:10.17428/rfn.v5i10.1558

Nafta and the future of Mexico-U.S. border environmental management

2017· article· en· W2771565940 on OpenAlexaboutno aff
Stephen P. Mumme

Bibliographic record

VenueFrontera Norte · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMexican Socioeconomic and Environmental Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyPhilosophy

Abstract

fetched live from OpenAlex

Con el anuncio reciente de que los gobiernos de Canada, Mexico y Estados Unidos habian llegado a un consenso sobre los acuerdos suplementarios al TLC sobre el medio ambiente, se hizo evidente que el TLC formara parte de un regimen trinacional para el manejo del medio ambiente. Ya que el congreso estadounidense esta en proceso de implementar el TLC, nos conviene preguntar, ?que implica el TLC para el futuro del manejo del medio ambiente en la frontera mexico-estadounidense? Aunque la respuesta puede ser especulativa, esta puede buscarse en el texto del mismo TLC, incluyendo sus acuerdos suplementarios: ?como se puede adaptar al regimen existente en el medio ambiente fronterizo, y que capacidad tiene este regimen para acomodar tendencias ambientales ya presentes en la region? El articulo analiza como cada uno de estos elementos contribuye a las interrogantes planteadas anteriormente. ABSTRACT With the recent announcement of agreement on supplemental environmental accords by the governments of Canada, Mexico, and the United States, it now appears NAFTA may indeed become part of the trinational environmental management regime. As the United States Congress moves to authorize NAFTA's implementation, it is fruitful to ask what it means for the future of environmental management along the Mexico-United States border. While speculative, the answer may be sought in the text of the NAFTA agreement, including the supplemental accords, its fit to the extant environmental regime for the border area, and the capacity of that regime to accommodate environmental trends now in place in the region. The remainder of this essay analyzes each of these elements as they shape an answer to the stated question.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.289
Threshold uncertainty score0.576

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.003
GPT teacher head0.198
Teacher spread0.195 · 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 designNot applicable
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

Citations1
Published2017
Admission routes1
Has abstractyes

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