How Citizen Representatives Address the Epistemic Challenges of Democratic Citizenship
Bibliographic record
Abstract
In this essay, we take a closer look at the kinds of trust judgments citizens need to be able to make in epistemic divisions of labour in democratic self-government. We distinguish kinds of political trust judgments, with a focus on the epistemic demands they place on citizens, as well sources of institutional support for citizen trust judgments, such as professional certifications and ethics. Though trust judgments have always been functionally necessary for representative democracies, the institutional conditions of trustee representation have always been weak, and the rise of the sceptical citizen has eroded the bases of deferential forms of trust. We propose that well-designed minipublics have the characteristics necessary to serve as institutional supports for citizens’ trust judgments. In particular, we review two cases in which minipublics have, in fact, functioned as trustee representatives: the British Columbia Citizens’ Assembly and the Oregon Citizens’ Initiative Review. These new forms of trustee representation cannot close the gap between complex societies and democratic citizenship, but they may very well narrow it.
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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 | 0.043 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.024 | 0.026 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".