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Record W4417102099 · doi:10.1093/publius/pjaf078

Trade Attitudes and Federalism: A Study of Provincial Public Opinion toward Canada–US Trade

2025· article· en· W4417102099 on OpenAlexafffundabout
Diya Jiang

Bibliographic record

VenuePublius The Journal of Federalism · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIdeologyAutonomyPublic opinionSocioeconomic statusFree tradeTrade barrierVariation (astronomy)

Abstract

fetched live from OpenAlex

Abstract Despite federal leadership on international trade policy, growing sub-federal involvement raises important questions about regional variation in public attitudes. This article explores whether Canadians’ trade preferences vary across provinces and are shaped by subnational contexts. Using 2022 Environics survey data and socioeconomic indicators from Statistics Canada, it tests competing post-functionalist and rationalist explanations. The results show a largely uniform support for free trade with the United States across provinces, with only Quebec showing a marginally more favorable baseline. Economic and ideological variables shape preferences in statistically significant ways but do not operate differently across regions. The findings support the rationalist framework, highlighting the role of income, education, and local trade exposure. However, the article finds little evidence of regional politicization of trade, suggesting that observed provincial trade involvement may reflect structural economic interests or institutional autonomy rather than public contestation, although recent US–Canada trade tensions may change this dynamic.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.305
Teacher spread0.273 · 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 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
Published2025
Admission routes3
Has abstractyes

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