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Record W3121427529 · doi:10.5089/9781498303286.001

NAFTA to USMCA: What is Gained?

2019· article· en· W3121427529 on OpenAlex
Mary E. Burfisher, Frédéric Lambert, Troy Matheson

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIMF Working Paper · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsEconomicsBusinessInternational economics

Abstract

fetched live from OpenAlex

The United States – Mexico – Canada Agreement (USMCA) was signed on November 30, 2018 and aims to replace and modernize the North-American Free Trade Agreement (NAFTA). This paper uses a global, multisector, computable-general-equilibrium model to provide an analytical assessment of five key provisions in the new agreement, including tighter rules of origin in the automotive, textiles and apparel sectors, more liberalized agricultural trade, and other trade facilitation measures. The results show that together these provisions would adversely affect trade in the automotive, textiles and apparel sectors, while generating modest aggregate gains in terms of welfare, mostly driven by improved goods market access, with a negligible effect on real GDP. The welfare benefits from USMCA would be greatly enhanced with the elimination of U.S. tariffs on steel and aluminum imports from Canada and Mexico and the elimination of the Canadian and Mexican import surtaxes imposed after the U.S. tariffs were put in place.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.028

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 head0.052
GPT teacher head0.214
Teacher spread0.162 · 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