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Record W3116878160 · doi:10.46282/blr.2020.4.2.181

Interpreting Law Through International Judicial Dialogue by Polish Courts

2020· article· en· W3116878160 on OpenAlexfundno aff
Magdalena Matusiak-Frącczak

Bibliographic record

VenueBratislava Law Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsnot available
FundersEuropean CommissionUniversity of OxfordYork University
KeywordsInterpretation (philosophy)JurisprudenceReciprocity (cultural anthropology)LawPolitical scienceMeaning (existential)PopularityJudicial interpretationInternational lawJudicial opinionLaw and economicsSociologyEpistemologyPhilosophyLinguisticsSocial science

Abstract

fetched live from OpenAlex

International judicial dialogue is a new method of law interpretation that gains popularity in analyses of legal scholars and still raises a lot of doubts both on its existence as well as its definition. This paper will deal with the application of this technique by Polish courts. In the first place, it will be explained what international judicial dialogue actually means. Afterwards, the paper will in detail discuss problems connected to the use of this method on the basis of decisions of Polish courts, first, by presenting examples of a proper, decorative and failed dialogue, and then by emphasizing complications caused by this method in the Polish jurisprudence. It will be also explored whether there exists a real dialogue, meaning that not only Polish courts receptively refer to judgments of international and foreign courts, but there is also some level of reciprocity in those references. At the end of the paper, the advantages and disadvantages of this method will be deliberated. In this part, I will suggest some solutions permitting mitigation of some adverse effects s of this technique.

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)0.020
metaresearch head score (Gemma)0.022
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 score0.020
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.009
Scholarly communication0.0160.010
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.041
GPT teacher head0.335
Teacher spread0.294 · 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
Published2020
Admission routes1
Has abstractyes

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