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Record W3122860694

International Law in Domestic Courts: A Conflict of Laws Approach

2009· article· en· W3122860694 on OpenAlexaff
Ralf Michaels, Karen Knop, Annelise Riles

Bibliographic record

VenueeYLS (Yale Law School) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicConflict of Laws and Jurisdiction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConflict of lawsLawPolitical scienceLaw and economicsEconomics
DOInot available

Abstract

fetched live from OpenAlex

The relationship between international law and domestic law is rarely understood as a conflict of laws. Understanding it in this way opens up a parallel with the field of conflict of laws: the field for which the relationship between legal systems, especially the role of another system's jurisdiction, laws, and judgments vis-à-vis the domestic legal system, are exactly the bread-and-butter issues. We argue for such an approach to international law in domestic courts: an approach that we elaborate as "theory through technique."\nIn our view, conflicts should be seen broadly as the discipline that developed to deal with conflicts between laws, without necessarily being committed to any one method or policy. Surprisingly, we demonstrate that it is precisely the seemingly negative features of conflicts - the field's high degree of technicality disparaged as a "conflict-of-laws machine" and the multitude of theories famously deemed a "dismal swamp" - that figure among the advantages of a conflict-of-laws approach to international law in domestic courts.\nA conflict-of-laws approach offers ways to respect the nature of international law as law, without simplifying that nature by characterizing it exactly as domestic law. In addition, seeing the parallel with conflict of laws brings a wealth of experience that can enrich and refine the debate on international law in domestic courts. Finally, the parallel with conflicts changes international law in domestic courts from a specific problem addressed by international and constitutional lawyers into a general problem of relativism - which, we argue, conflict of laws is uniquely positioned to address.

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)0.009
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.013
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0070.031
Scholarly communication0.0130.018
Open science0.0030.007
Research integrity0.0090.011
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 head0.025
GPT teacher head0.309
Teacher spread0.284 · 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 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

Citations8
Published2009
Admission routes1
Has abstractyes

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