MétaCan
Menu
Back to cohort
Record W7029820161

La legitimación activa en los casos de protección de la naturaleza en el continente americano (Tema Central)

2023· article· es· W7029820161 on OpenAlexaboutno aff

Bibliographic record

VenueUASB-DIGITAL Categories (Universidad Andina Simón Bolívar) · 2023
Typearticle
Languagees
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsDerechoContext (archaeology)Work (physics)Free access
DOInot available

Abstract

fetched live from OpenAlex

El presente artículo se enfoca en el desarrollo del derecho climático a través del análisis de casos judiciales en distintas regiones de América. Comenzando con la opinión consultiva de la Corte Interamericana de Derechos Humanos, se exploran casos emblemáticos en tres países de América del Norte (Estados Unidos, Canadá y México) y uno de América del Sur (Colombia). Se muestra así cómo los jóvenes, principalmente menores de edad, se han convertido en los representantes de la naturaleza, debido quizás al forzoso requerimiento de la legitimación activa. Entre los casos expuestos se encuentran Juliana vs. Estados Unidos de América, Held vs. Montana, Mathur et al. vs. Su Majestad la Reina por derecho de Ontario, Generaciones futuras vs. Minambiente, y Jóvenes vs. Gobierno de México. Posteriormente se expone de qué modo el sistema jurídico ecuatoriano permite a cualquier persona, tenga interés personal o no, participar en los juicios de derecho ambiental representando a la naturaleza. Finalmente, se concluye que, si bien los jóvenes se encuentran haciendo aportes a nivel mundial para esta novedosa área del derecho, también es necesaria la participación de toda la sociedad en los litigios climáticos, por lo cual emular el sistema ecuatoriano podría beneficiar al mundo entero.

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)0.008
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: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.289
Teacher spread0.284 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueUASB-DIGITAL Categories (Universidad Andina Simón Bolívar)Same topicEnvironmental law and policyFrench-language works237,207