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Las transgresiones respetuosas de la enseñanza del common law y el derecho civil en Quebec: lecciones del método transistémico de educación jurídica

2023· article· es· W4389135802 on OpenAlexaboutno aff
Álvaro Flores

Bibliographic record

VenueDerecho PUCP · 2023
Typearticle
Languagees
FieldSocial Sciences
TopicComparative and International Law Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesDerechoContext (archaeology)Political sciencePhilosophyGeography

Abstract

fetched live from OpenAlex

Este artículo explora cómo se enseña el derecho en el orden bijurídico de Quebec, donde coexisten la tradición del derecho civil y el common law. Se centra particularmente en el desarrollo y la implementación del método transistémico de educación jurídica desarrollado en la Facultad de Derecho de la Universidad McGill, en Canadá. Este método consiste, en esencia, en enseñar ambas tradiciones jurídicas simultánea y comparativamente. Tiene por objetivo que sus egresados puedan navegar las diferentes tensiones políticas y culturales existentes en Canadá, entablar diálogos jurídicos interculturales y ejercer en dos sistemas jurídicos. Esta metodología, en la que se enfatiza la convivencia de dos sistemas jurídicos, ha implicado también repensar la noción del derecho, alejándose de miradas legalistas y abrazando nociones cercanas al pluralismo jurídico. El artículo se estructura explicando las diferentes capas contextuales que han rodeado el surgimiento y desarrollo de este método transistémico. Se explica el contexto macroinstitucional presentando las tensiones entre anglo-Canadá y la provincia de Quebec; el contexto mesoinstitucional, que explica las discusiones surgidas al interior de la provincia y la Facultad de Derecho; mientras que el contexto microinstitucional presenta cómo se enseñan los cursos de obligaciones/contratos y responsabilidad extracontractual/torts.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.031
GPT teacher head0.375
Teacher spread0.344 · 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.

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
Published2023
Admission routes1
Has abstractyes

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