Bringing It All Together: Leveraging Social Movements and the Courts to Advance Substantive Human Rights and Climate Justice
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.058 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".