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Record W4232122389 · doi:10.1108/oxan-db224842

US proposals threaten NAFTA’s regional auto sector

2017· other· en· W4232122389 on OpenAlexaboutno aff

Bibliographic record

VenueEmerald expert briefings · 2017
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsAutomotive industryInternational tradeChinaFree trade agreementValue (mathematics)Rules of originBusinessEconomicsInternational economicsFree tradeEconomyGeographyEngineering

Abstract

fetched live from OpenAlex

Subject The North American auto sector. Significance The third round of talks over the renegotiation of the North American Free Trade Agreement (NAFTA) ended in Ottawa on September 26, following relatively unproductive and tense rounds in Washington and Mexico City. A point of particular contention is Washington’s proposal to tighten rules of origin (RoO) for the automotive sector and potentially to introduce national content requirements for cars to enter the US market duty-free. Impacts Disrupting NAFTA automotive value chains would ultimately benefit lower-cost auto parts producers in China and South-east Asia. Greater auto sector trade between China and Mexico would encourage closer bilateral ties. Carmakers will respond to any need to increase value-added in the United States by ramping up automation, minimising gains for US workers.

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)0.007
metaresearch head score (Gemma)0.014
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.078
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0120.004
Open science0.0020.003
Research integrity0.0170.007
Insufficient payload (model declined to judge)0.0580.025

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 head0.089
GPT teacher head0.245
Teacher spread0.156 · 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
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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