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Record W4200408068 · doi:10.1111/jcms.13287

Explaining Sub‐Federal Variation in Trade Agreement Negotiations: The Case of CETA

2021· article· en· W4200408068 on OpenAlexaffabout
Jörg Broschek, Patricia Goff

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsNegotiationEconomic integrationEuropean unionBureaucracyInternational tradeLiberalizationPolitical scienceCustoms unionPoliticsFree tradeTrade barrierEconomicsInternational economicsLaw

Abstract

fetched live from OpenAlex

Abstract Sub‐federal units have emerged as increasingly important actors in international trade policy. This is puzzling as they usually have no formal competencies in this area. Using the Comprehensive Economic and Trade Agreement (CETA) between Canada and the European Union as a case study, this article examines one key driver behind this development ‐ the provisions in new free trade agreements. The article conceptualizes such provisions as instances of negative and positive integration. We show that while the Canadian provinces largely supported both types of provisions, sub‐federal units in Belgium, Germany and Austria resisted unfettered liberalization through negative integration and market‐creating positive integration. At the same time, they demanded stronger market‐correcting positive integration measures. Three categories of sub‐federal interests explain these differences in motivation. The Canadian province's engagement was motivated by (regional) economic interests, whereas bureaucratic self‐interest and political interests mobilized sub‐federal units in the European federations.

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)0.011
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0100.005
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.058
GPT teacher head0.354
Teacher spread0.295 · 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 designQualitative
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

Citations11
Published2021
Admission routes2
Has abstractyes

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Same venueJCMS Journal of Common Market StudiesSame topicEuropean Union Policy and GovernanceFrench-language works237,207