Public Deliberation with Climate Change: Opening up or Closing down Policy Options?
Bibliographic record
Abstract
The principle of public participation is increasingly recognized as central for effective climate governance, although underpinning assumptions about what constitutes participation are not always clearly articulated. This article inquires into the challenges faced when lay citizens are asked to engage in deliberative ‘mini‐publics’ geared towards providing input into climate policy. While advocates claim that these innovative forums improve collective decision making by creating the conditions for a socially diverse constituency to learn about and deliberate on salient public issues, critics caution that the democratic potential of deliberative initiatives can be compromised from the outset by a deeper set of assumptions that position public meanings as the domain of expert institutions. Rather than opening up public issues to diverse meanings, mini‐publics can inadvertently close down public debate where only expert issue framings are considered valid, reasonable and credible. The admirable objective to include lay publics in climate policy can be limited in practice by a tendency to frame climate change as an inherently expert‐based issue. Defining the discussions as the exclusive preserve of experts can implicitly preclude wider public involvement, in turn limiting the knowledge and perspectives available for policy makers.
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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 | 0.052 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.047 |
| Scholarly communication | 0.019 | 0.028 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.018 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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".