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The Impact of the NAFTA over the Canadian Automotive Industry throughout 20 Years

2016· article· en· W2561416620 on OpenAlexaboutno aff
Francisco Ernesto Navarrete

Bibliographic record

VenueAmericanae (AECID Library) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsAutomotive industryFree trade agreementChinaInternational tradeProduction (economics)Value (mathematics)Order (exchange)Economic impact analysisManufacturingBusinessEconomicsEconomyFree tradePolitical scienceEngineeringMarketingFinance

Abstract

fetched live from OpenAlex

Esta pesquisa tem por objetivo explicar o impacto que o Acordo de Livre Comércio Norte Americano (North American Free Trade Agreeent- NAFTA) teve sobre a indústria automotiva canadense desde que foi assinado em 1994. Ela mostra o desenvolvimento da produção canadense durante estes vinte anos, desde o início, no século XX, até hoje, comparado com a produção dos Estados Unidos e do México. O trabalho também inclui uma explanação do comércio com o mercado dos Estados Unidos, seu valor agregado, a evolução dos negócios e como os países do NAFTA enfrentaram a nova ordem mundial, focada na produção de alto valor agregado; adicionalmente, a pesquisa faz uma análise detalhada das principais conquistas canadenses alcançadas por este setor e os desafios enfrentados pelo Canadá como nação e como região. Finalmente, o resultado é comparado com o crescimento da produção chinesa e o fator mão de obra nestes últimos 20 anos.

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)0.006
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: none
Teacher disagreement score0.082
Threshold uncertainty score0.593

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.009
Science and technology studies0.0060.002
Scholarly communication0.0060.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.219
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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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