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Record W2028999950 · doi:10.1080/09638190903217453

CUSFTA effects: A joint consideration of trade and multinational activities

2009· article· en· W2028999950 on OpenAlexaffabout
Pascal L. Ghazalian, William Hartley Furtan

Bibliographic record

VenueJournal of International Trade & Economic Development · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of SaskatchewanUniversity of Lethbridge
Fundersnot available
KeywordsMultinational corporationGravity model of tradeInternational tradeEconomicsInternational economicsBilateral tradePanel dataTrade barrierFree trade agreementBusinessFree tradeChinaEconometrics

Abstract

fetched live from OpenAlex

This paper estimates the effects of the Canada–US Free Trade Agreement (CUSFTA) on trade, sales of foreign affiliates of multinational enterprises, and total bilateral commerce (aggregate of both trade ands sales of foreign affiliates) in the manufacturing sector. The empirical investigation is carried out over a panel dataset covering the US bilateral transactions with the Organization for Economic Cooperation and Development (OECD) countries for the period 1983–1998. The empirical specification is guided by a gravity-based model that accounts for trade and the operation of foreign affiliates as alternative modes of accessing foreign markets. The results show that the CUSFTA induced an increase in inward and outward trade between the US and Canada, but also led to a significant reduction in sales of their foreign affiliates in the corresponding CUSFTA partner country. This outcome implies that the trade-generating effect of the CUSFTA is overstated.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.765
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.037
GPT teacher head0.226
Teacher spread0.189 · 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 designObservational
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
Published2009
Admission routes2
Has abstractyes

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