Bibliographic record
Abstract
Abstract Climate action stands as a paramount challenge in contemporary society, but solutions are often impeded by vested interests tied to electoral democracies. As a result, the past decade has witnessed a renewed interest in the practice of sortition—a variety of democracy that is not electoral but lottocratic—in Ireland, the United States, and in other venues from Belgium to Canada to India and South Korea. Recent scholarly literature, including the five-installment Common Knowledge symposium “Antipolitics,” to which this article is a contribution, argues that citizens’ juries and other such deliberative forums can clear a path for climate action. This essay examines one of the first assemblies chosen by lottery to attend purely to climate change and describes in detail how the assembly came about, how it operated, how it successfully influenced Irish government policy, and the possible applications beyond Ireland of lessons that have been learned from the experience.
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 | 0.021 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.037 |
| Scholarly communication | 0.025 | 0.010 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".