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Record W2886159603

Brexit, Democracy, and Human Rights: The Law Between Secession and Treaty Withdrawal

2017· article· en· W2886159603 on OpenAlexaboutno aff
Jure Vidmar

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBrexitPolitical scienceTreatyLawEuropean unionReferendumTreaty of LisbonHuman rightsDemocracyLegal certaintyEuropean Union lawLaw and economicsSociologyEconomicsPoliticsInternational trade
DOInot available

Abstract

fetched live from OpenAlex

The United Kingdom (UK) has triggered the mechanism to exit the European Union (EU). Such a decision was taken at a referendum held in 2016. The referendum was, however, not legally binding, and only England and Wales, but not Scotland or Northern Ireland, endorsed the option to exit the EU. UK’s EU exit can be seen as the UK’s withdrawal from the Treaty on European Union (TEU) and the Treaty on the Functioning of European Union (TFEU) pursuant to Article 50 TEU. But the TEU and TFEU are not ordinary treaties of public international law. They are constitutional instruments of a complex supra-national polity—the EU. Brexit is thus in many respects more than just an ordinary treaty withdrawal; it can be seen as the UK’s functional secession from the EU. This creates tensions between the rules of treaty withdrawal and tenets of democratic decision-making on territorial matters in a constitutional democracy. This article analyzes such tensions and contrasts Brexit with the reasoning of the Supreme Court of Canada in the Quebec case, holding that democracy was not a simple majority rule. Yet, it is questionable whether the treaty-law logic of Article 50 allows for accommodation of the Quebec principles. The article also demonstrates how the European Convention of Human Rights could step in to protect certain already-acquired rights of EU citizens after Brexit. Given the complexity and diversity of rights stemming from EU citizenship, however, there is no complete legal certainty without either an agreement between the EU and the UK to this effect, or further development of the existing case law on the matter.

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)0.010
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0110.075
Scholarly communication0.0170.014
Open science0.0020.009
Research integrity0.0120.013
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.307
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 designNot applicable
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

Citations4
Published2017
Admission routes1
Has abstractyes

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