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Record W2898836316 · doi:10.2478/slgr-2018-0009

Louisiana and Quebec Terminology as a Tool in Polish-English Legal Translation

2018· article· en· W2898836316 on OpenAlexaboutno aff
Przemysław Kusik

Bibliographic record

VenueStudies in Logic Grammar and Rhetoric · 2018
Typearticle
Languageen
FieldArts and Humanities
Topiclinguistics and terminology studies
Canadian institutionsnot available
Fundersnot available
KeywordsTerminologyCivil codeLegal translationCivil law (Civil law)LawPolitical scienceCommon lawEnglish lawLinguisticsCommercial lawPhilosophy

Abstract

fetched live from OpenAlex

Abstract While in the majority of English-speaking territories the dominant legal tradition is common law , in Louisiana and Quebec the native language is English and the legal system stems from continental civil law . Both the Louisiana Civil Code and the Civil Code of Quebec take root in the European codification movement, following Code Napoleon. Bearing in mind the link between law and language, these jurisdictions provide a unique source of English civil law terminology with well-founded conceptual background. The civil codes of Louisiana and Quebec seem to be potentially useful for the translation of Polish private law into English. Yet there are some reservations which should be considered. By comparing two different translations of Article 292 of the Polish Civil Code, this paper is intended to contribute to the debate on the use of Quebec and Louisiana terminology in Polish-English legal translation.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.434
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0050.006
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
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 head0.074
GPT teacher head0.309
Teacher spread0.235 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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