Bibliographic record
Abstract
Caroline Lucas MP has advocated creating an 'Environmental Rights Commission' (ERC). She envisages an ERC operating as a non-departmental public body on a statutory basis with sufficient resources to advance test-case litigation which supports and develops environmental rights and sustainability, and to promote a sustainability perspective in policy and legislation development.This article discusses whether the UK should create an ERC. It first explores four institutions which are broadly similar to Lucas' envisaged ERC: the Australian network of Environmental Defenders Offices, the Ontario Environmental Commissioner, the New Zealand Parliamentary Commissioner for the Environment and the UK Equality and Human Rights Commission. It examines the reasons for their creation, their roles and powers, and determines what lessons can be gleaned from their operation. Using this comparative information it then explores the arguments surrounding the case for and against creating a UK ERC.It concludes that the case for the UK to create an ERC is a strong one. A well designed ERC could help to embed sustainability and environmental rights within the UK, develop UK environmental law, support the implementation of the Aarhus Convention and provide a respected 'voice for the environment.'
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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 | 0.015 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.025 | 0.010 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".