The Human Right to Science and Its Relationship to International Environmental Law
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.
Bibliographic record
Abstract
Abstract This article explores the potential contribution of international human rights law – specifically, the oft-neglected ‘right to science’ – to the interpretation, operation and progressive development of international environmental law. Science and its applications play a critical role in environmental protection. At the same time, society faces persistent controversies at this interface. Environmental regimes may lack sufficient norms and tools for regulating upstream science and innovation processes because they tend to focus narrowly on physical harms to the environment and may not address the wider ethical, legal, social and political concerns. The human right to science, which is codified in various international and regional human rights instruments, may serve to augment international environmental law and contribute to more effective, equitable and democratically legitimate and accountable processes and outcomes in relation to the application of science and technology in environmental regimes. The article begins by outlining the scope and contents of, as well as the limitations on, the right to science, focusing on Article 15(1)(b) of the International Covenant on Economic, Social and Cultural Rights (ICESCR) and its overlaps with the norms of international environmental law.1 It then analyses the ways in which the right to science may influence the development of international environmental law by elucidating mechanisms for the integration of a human rights perspective in science and technology and by outlining its potential substantive contributions to the development of international environmental law.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it