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Record W3213786568 · doi:10.1017/ipo.2021.50

When politicization meets ideology: the European Parliament and free trade agreements

2021· article· en· W3213786568 on OpenAlexaboutno aff
Marta Migliorati, Valerio Vignoli

Bibliographic record

VenueItalian Political Science Review/Rivista Italiana di Scienza Politica · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsnot available
FundersUniversity of Cambridge
KeywordsEuropean unionFree tradeContext (archaeology)International tradePolitical scienceCommercial policyParliamentTransatlantic Trade and Investment PartnershipEconomic integrationIdeologyInternational economicsEconomicsPoliticsLawGeography

Abstract

fetched live from OpenAlex

Abstract Since the Lisbon Treaty, the European Parliament (EP) has considerably increased its competencies in European Union (EU) trade policy. At the same time, a ‘new generation’ of free trade agreements (FTAs), including the Transatlantic Trade and Investment Partnership (TTIP) with the United States, Comprehensive Economic and Trade Agreement (CETA) with Canada, and the agreement with Japan, have been negotiated by the European Commission. Although existing literature has tackled the process of the EP's institutional self-empowerment in this policy area, there is no systematic research investigating the lines of conflict within the EP over FTAs. Through a newly collected dataset of all EP plenary debates between 2009 and 2019 on six relevant FTAs, we extract EP Members’ (MEPs) preferences by means of a manual textual analysis. We then test the explanatory power of the two traditional lines of cleavages within the EP over MEPs stated preferences: position on the left-right axis and support for EU integration. We find that both these dimensions fundamentally shape the conflict in the EP over FTAs. The impact of these two ideological cleavages is magnified in the context of politicized FTAs, namely the TTIP and CETA. Through these findings, the paper significantly contributes to the research on competition in the EP and, more broadly, to the understanding of EU trade policy and its emerging politicization dynamics.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.006
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.034
GPT teacher head0.278
Teacher spread0.244 · 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.

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

Citations10
Published2021
Admission routes1
Has abstractyes

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