Green parties and environmental activism
Bibliographic record
Abstract
For this edition on environmental activism and the law, we examined how contemporary green political parties construe their role and relevance when many environmentalists including the Extinction Rebellion (XR) movement are bypassing parliamentary processes by taking to the streets as well as by proposing alternate forms of political engagement such as convening national citizens’ assemblies. This report features interviews conducted in early 2020 with Paul Manly (MP, House of Commons, Green Party of Canada); Chlöe Swarbrick (MP, New Zealand Parliament, Green Party of Aotearoa New Zealand); and Jonathan Bartley (Co-leader of the Green Party of England and Wales, and councillor on Lambeth Council, London). Each interviewee responded to the same questions, which are detailed below. The interviews were conducted by Emma Thomas, XR Vancouver (interviewed Paul Manly); Trevor Daya-Winterbottom, FRGS, Associate Professor in Law, University of Waikato, and Deputy Chair of the IUCN Academy of Environmental Law (interviewed Chlöe Swarbrick); and Benjamin J Richardson, Professor of Environmental Law, University of Tasmania (interviewed Jonathan Bartley).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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".