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Record W7049126602

New Frontiers of Consumer Protection: The Interplay Between Private and Public Enforcement

2009· book· en· W7049126602 on OpenAlexaboutno aff

Bibliographic record

VenueCadmus - EUI Research Repository (European University Institute) · 2009
Typebook
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementRedressDamagesNegotiationDimension (graph theory)TortClass actionEuropean unionPrivate law
DOInot available

Abstract

fetched live from OpenAlex

Collective redress has gained momentum in Europe and North America. Legal reforms are driven by different institutional conditions but show a limited degree of convergence. The seventeen contributions from the US, Canada and from the Member States of the European Union (East and West) put the interplay of public enforcement and private collective judicial enforcement into perspective. The parameters of analysis are the constitutional dimension (i.e. three multi-level systems compared US, EC and Canada, vertically: allocation of powers between levels and distinction between regulation and private law and administrative control versus judicial control, horizontally: degree of harmonisation, transborder litigation, choice of law), the institutional dimension (the players, regulatory and judges, private organisation and lawyers) and the substantive dimension (regulation through administrative law versus regulation through tort or contract law, standard setting (strict liability versus negligence), remedies (injunctions and damages)). These three parameters are then broken down into five sections: general comparison, the public/private enforcement divide, remedies concerning the distinction between injunction and damages as well as between class actions and group actions, negotiation and adjudication, transborder litigation and international private law. The final chapter develops prospects to indicate the way ahead.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.045
GPT teacher head0.276
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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