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BERTSIO LINGUISTIKO KONTRAJARRIAK EUSKAL AUTONOMIA ERKIDEGOKO LEGEETAN

2019· article· es· W2950932243 on OpenAlexaboutno aff
DAVID ROSALES REGUERA

Bibliographic record

VenueRevista Vasca de Administración Pública / Herri-Arduralaritzarako Euskal Aldizkaria · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicLegal processes and jurisprudence
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

«¿Y si la ley en castellano dice lo contrario?». Esta es la pregunta que surge cuando, después de analizar la ley en euskera, se procede a examinar el texto de esa misma ley en castellano, y encontramos divergencias entre ellas. Aunque esta situación no se dé con mucha frecuencia, hay veces que existen divergencias lingüísticas entre los textos legales oficiales. Puede estar motivado, bien porque el euskera y el castellano sean lenguas sin parentesco, hecho que dificulta la equivalencia entre ambos textos, o bien porque a veces existen fallos de traducción. En estos casos, se ponen en evidencia los límites de la cooficialidad del euskera, ya que puede estar en juego la seguridad jurídica en la Comunidad Autónoma del País Vasco. El objeto de este estudio es investigar cómo se debe actuar cuando las versiones en euskera y en castellano de una misma ley no son equivalentes. Para ello, además de profundizar en la doctrina del Tribunal Constitucional, también ha sido objeto de estudio la trayectoria que la Jurilingüística ha realizado en la interpretación de textos legales multilingües, tanto en el Derecho Internacional, como en el Derecho de la Unión Europea, así como en los sistemas bilingües de países como Canadá o Bélgica. «Eta legeak gaztelaniaz kontrakoa badio?». Horixe bera da, hain zuzen ere, legea euskaraz aztertu, gaztelaniazko testua irakurri, eta biak bat ez datozela ohartzean sortzen den galdera. Sarritan gertatzen ez bada ere, batzuetan bertsio linguistiko kontrajarriak azaltzen dira lege-testu ofizialetan, izan euskara eta gaztelania linguistikoki urrun egoteak zaildu egiten duelako bi testuen arteko baliokidetasuna, izan, besterik gabe, zenbaitetan itzulpen-akatsak daudelako. Eta horrelako kasuetan, euskararen benetako koofizialtasunaren mugak agerian jartzen dira, segurtasun juridikoa jokoan egon daitekeelako Euskal Autonomia Erkidegoan. Bada, ikerlan honen helburua da aztertzea nola jardun behar den lege bereko euskarazko eta gaztelaniazko bertsioak bat ez datozenean. Horretarako, Konstituzio Auzitegiaren doktrinan sakontzeaz gain, aztergai izan da Jurilinguistikaren alorrak lege-testu eleanitzen interpretazioan egin duen ibilbidea, bai Nazioarteko Zuzenbidean, bai Europar Batasuneko Zuzenbidean, baita Kanada edo Belgika bezalako sistema elebidunetan ere. «What if the Spanish version of the act says the contrary?». That is the question that arises when, after reading the act in Basque language, the Spanish text is examined, and there are some divergences. Although it does not happen very often, there are sometimes problems of linguistic divergences between official legal texts. This may be motivated by the difficulty of drafting equivalent versions, given the linguistic difference between Basque and Spanish, or even by occasional errors in translation. In such cases, the limits of the coofficiality status of Basque are revealed, as legal certainty can be at risk in the Autonomous Community of the Basque Country. The purpose of the present study is to research how to proceed when the Basque and Spanish versions of the same act are not equivalent. This involves carrying out an in-depth study of the case-law of the Spanish Constitutional Court, as well as the experience of Jurilinguistics in interpretation of multilingual legislative texts in International Law, European Union Law, and in bilingual systems such as Canada or Belgium.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.009
GPT teacher head0.307
Teacher spread0.298 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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