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Record W2543669779 · doi:10.1163/15718093-12341419

Cross-border Movement of Patients in the eu: A Re-Appraisal

2016· article· en· W2543669779 on OpenAlexfundno aff
Clemens Rieder

Bibliographic record

VenueEuropean Journal of Health Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsnot available
FundersQueen's UniversityQueen's University BelfastEuropean Commission
KeywordsLegislatorPolitical scienceLawLegitimacyTreatyHealth lawEconomic JusticeEuropean court of justiceEuropean Union lawHealth careEuropean unionHealth policyInternational healthEconomicsInternational trade

Abstract

fetched live from OpenAlex

Abstract The national welfare state, so it seems, has come under attack by European integration. This article focuses on one facet of the welfare state, that is, healthcare and on one specific dimension, that is, cross-border movement of patients. The institution which has played a pivotal role in the development of the framework regulating the migration of patients is the European Court of Justice ( ecj ). The Court’s activity in this sensitive area has not remained without critics. This was even more so since the Court invoked Treaty (primary) law which not only has made it difficult to overturn case law but also has left the legislator with very little room for manoeuvre in relation to any future (secondary) eu law. What is therefore of special interest in terms of legitimacy is the legal reasoning by which the Court has made its contribution to the development of this framework. This article is a re-appraisal of the legal development in this field.

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)0.075
metaresearch head score (Gemma)0.102
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 score0.075
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.007
Science and technology studies0.0040.014
Scholarly communication0.0170.016
Open science0.0060.012
Research integrity0.0190.013
Insufficient payload (model declined to judge)0.0080.001

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 head0.036
GPT teacher head0.419
Teacher spread0.383 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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