Elections for direction, sortition for judgment: a new model of bicameral democracy
Bibliographic record
Abstract
This article proposes a new model of bicameral sortition democracy that rethinks the division of labor between elected and randomly selected bodies. Existing bicameral proposals either give sortition chambers weak or co-equal authority, limiting their ability to realize the epistemic promise of deliberative democracy. By contrast, I propose a model in which an elected chamber sets the legislative agenda and oversees deliberative fairness, while a sortition chamber holds exclusive authority to deliberate and decide policy. This design preserves the communicative and authorization functions of elections, while securing the epistemic advantages of cognitively diverse citizen deliberation. I evaluate this model against three alternatives, pure sortition, co-equal bicameralism, and subordinate sortition bicameralism, along four normative dimensions: resistance to elite capture, representation and inclusion, epistemic quality, and legitimacy and accountability. I argue that only a model that empowers citizens in their ‘post-learning’ capacity, while grounding decisions in a democratically visible and contestable process, can deliver a political system that is both legitimate and epistemically robust.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".