MétaCan
Menu
Back to cohort
Record W3106530059 · doi:10.2478/cl-2020-0006

Therapeutic Jurisprudence and Linguistic Rights: Beyond Access to Care

2020· article· en· W3106530059 on OpenAlexaff
Nicholas Léger-Riopel

Bibliographic record

VenueComparative Legilinguistics · 2020
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsNormativeTherapeutic jurisprudenceJurisprudenceLawMental healthProcess (computing)Promotion (chess)PopulationHealth careSociologyPsychologyPolitical scienceComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Abstract Therapeutic jurisprudence is an interdisciplinary examination on the effect of the law on the mental and emotional health of those implicated in the judicial process. It concentrates primarily on the psychological impact of legal rules and procedures, as well as on the behaviour of legal players. TJ is a tool not often used in the promotion of linguistic rights. Endowed with a double mission, both normative and descriptive, TJ makes it possible to measure the impact of health incidences. In providing legal reformers with more precise tools to assess the health impacts of new linguistic rights standards TJ offers such a path of implementation of linguistic rights – not only from the formal point of view, but by keeping in mind their actual effectiveness – integrating law and languages in a way to mitigate their consequences on a population’s health.

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)0.016
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.097
Scholarly communication0.0130.011
Open science0.0020.011
Research integrity0.0070.007
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 head0.214
GPT teacher head0.519
Teacher spread0.306 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueComparative LegilinguisticsSame topicInterpreting and Communication in HealthcareFrench-language works237,207