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Record W4311209568 · doi:10.1007/s12142-022-00674-0

Bringing It All Together: Leveraging Social Movements and the Courts to Advance Substantive Human Rights and Climate Justice

2022· article· en· W4311209568 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHuman Rights Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsRoyal Roads University
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research ChairsGovernment of Canada
KeywordsJusticiabilityHuman rightsRight to foodPolitical scienceJurisprudenceSocial rightsPovertySocial movementFundamental rightsClimate justiceLaw and economicsLawSociologyClimate changeEnvironmental ethicsPoliticsFood securityGeography

Abstract

fetched live from OpenAlex

Although significant literature and jurisprudence has amassed on rights-based climate litigation over recent years, less research and case law has emerged on poverty-related court cases and the fulfilment of economic, social, and cultural rights (ESCR) in Canada. Fewer still are studies exploring the interlinkages between these areas of inquiry. The purpose of this paper is to explore, using Canada as a case study, rights-based developments in climate litigation cases and how these could impact the innovative advancement of ESCR (e.g. to food, housing and water). Typically, issues of justiciability and standing emerge, impeding the realization of such rights. Given the grave threats we now face, climate cases and social movements must be brought together to better hold state actors accountable for their rights obligations. We implore the legal community to explore ways to traverse juridical obstacles to realize the interdependencies of human rights and protect the planet from calamitous climate change.

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.

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 categoriesScience 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 score0.978
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.354
Teacher spread0.316 · 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