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Record W4412225155

Betragtninger om lovvalg i EU's direktivforslag om virksomhedernes due diligence i forbindelse med bæredygtighed

2023· article· da· W4412225155 on OpenAlexaff
Sylvie Cécile Cavaleri

Bibliographic record

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2023
Typearticle
Languageda
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsDue diligenceBusinessBusiness administrationFinance
DOInot available

Abstract

fetched live from OpenAlex

EU-Parlamentet vedtog primo juni 2023 forslaget til et direktiv om virksomhedernes due diligence i forbindelse med bæredygtighed (herefter: Direktivforslaget). Den 14. december 2023 nåede Det Europæiske Råd og Europa-Parlamentet en foreløbig aftale om due diligence-direktivet. Den aftalte tekst er i skrivende stund endnu ikke offentligt tilgængelig og følgende artikel forholder sig derfor til det oprindelige direktivforslag. Direktivforslaget indfører navnlig en privatretlig regulering af civilretligt erstatningsansvar for skader, der opstår som følge af manglende opfyldelse af de due diligence-forpligtelser, der pålægges visses virksomheder i Direktivforslaget. På trods af at effektiviteten af dette civilretlige ansvar i vidt omfang afhænger af, at et erstatningssøgsmål med grundlag i Direktivforslaget afgøres efter loven i et EU-land, er det langtfra sikkert, at dette resultat kan opnås. Denne artikel diskuterer de lovvalgsspørgsmål, der knytter sig til det civilretlige ansvar indført i Direktivforslaget, nemlig hvilken national lovgivning en ret i et EU-land vil anvende til at løse tvisten, og hvis de relevante lovvalgsregler fører til anvendelse af loven i et land uden for EU, hvad er så betydningen af art. 22 stk. 5 i Direktivforslaget, hvorefter EU-medlemsstaterne skal sikre, at bestemmelser i national ret til gennemførelse af det ved Direktivforslaget indførte civilretlige ansvar finder overordnet præceptiv anvendelse i tilfælde, hvor den lov, der finder anvendelse på krav med henblik herpå, ikke er lovgivningen i en medlemsstat.

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)0.004
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.290
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0100.003
Open science0.0010.006
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.2900.162

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 head0.097
GPT teacher head0.330
Teacher spread0.233 · 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
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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