Bibliographic record
Abstract
The politics of climate change In a world awash with strugglesand issues – from Ecuador to HongKong, Catalonia to Kashmir, austerityand war to racism and sexism, not tomention Brexit – the overarching globalissue is climate change. This questionand how we respond to it will determinethe future of humanity. In addition to thisobjective fact we are also witnessinga growing international climate actionmovement. The Fridays 4 Future andSchool student strikes on 20 and 27September were spectacular globally andin some places produced astonishinglevels of mobilisation eg half a millionin Montreal and about 170,000 in tinyNew Zealand (not to mention 30,000 orso in Dublin) . Then there was ExtinctionRebellion Week 2 which brought intoaction, including open civil disobedience,many thousands in London and manyhundreds in Dublin along with numerousother actions across the world.
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.
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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.021 | 0.018 |
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".