MétaCan
Menu
Back to cohort
Record W2982445815 · doi:10.14746/cl.2019.37.1

Jurilinguistic Analysis in Translation, Comparative Law Practice. Translate the Letter or “The Spirit of the Laws”? The Case of the Code Napoléon

2019· article· en· W2982445815 on OpenAlexaff
Jean-Claude Gémar

Bibliographic record

VenueComparative Legilinguistics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsLawMerge (version control)Legal translationLegal cultureComputer scienceLegal professionComparative lawPolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract Translated texts sometimes reflect the targeted legal system’s conventional manner of writing law; however, the equivalence of the legal message must be realized. Translating law into another legal culture goes through a comparative analysis of the laws involved, the command of which is needed to achieve legal equivalence. The form of the target text must nevertheless correspond to its legal culture. Legal translation is then the meeting point of languages, cultures and laws. To succeed, this meeting must be based on an ad hoc knowledge of both laws. Then comparative law enters into play as the legal translator’s “fellow traveler”, whom it equips for the exchange. To realize it, “two intersecting receptions will suffice” (Carbonnier). This operation is successful when concepts and notions overlap and the letter of the law (the substance) and the law’s expression (the form) merge, demonstrating “the spirit of the laws”. Benchmarking is the way to reach this goal. It is conducted here under the light of jurilinguistics via the analysis of terms and concepts presenting various translation difficulties, which demonstrate the necessity of comparative law (I). A comparison of translations of the Napoleonic Code and other civil codes will complete the quest for the spirit of the laws by the way in which the letter or the spirit of the text to be translated is rendered (II). The lessons to be learned are aimed at language professionals, who will find in jurilinguistic comparative analysis a way to perfecting their work and, in the translations of the civil codes, a basis of reflection on the role and functions of 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 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 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 score0.962
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.138
GPT teacher head0.373
Teacher spread0.236 · 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.

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueComparative LegilinguisticsSame topicTranslation Studies and PracticesFrench-language works237,207