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Record W3213204932 · doi:10.1504/ijatm.2022.10042830

New Trade Rules, Technological Disruption and COVID-19: Prospects for Ontario in the Cross-Border Great Lakes Automotive Industry

2021· article· en· W3213204932 on OpenAlexaffabout
John Holmes

Bibliographic record

VenueInternational Journal of Automotive Technology and Management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsQueen's University
Fundersnot available
KeywordsAutomotive industryProduction (economics)BusinessIndustrial organizationState (computer science)EngineeringEconomicsComputer science

Abstract

fetched live from OpenAlex

Canada has been characterised as a 'semi-peripheral' automotive-producing nation. This paper argues that to frame Canada only as a singular 'national' automotive industry is ill-conceived. Overwhelmingly concentrated in Ontario, Canadian automotive production forms an integral and important part of the cross-border Great Lakes automotive production region. The fortunes of automotive production in Canada are reliant, therefore, not only on 'national' policies but also on the continued vitality of the industry in this broader region and must be analysed as such. An analysis of the state of the industry in Canada stressing its integration within the Great Lakes automotive region is followed by an assessment of how the industry in the region, and especially in Ontario, might be impacted by impending challenges. These include supply chain weaknesses exposed by COVID-19, the more complex and stringent USMCA automotive rules of origin, and technological disruption associated with the transition to electric vehicles.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.450

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.317
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2021
Admission routes2
Has abstractyes

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