The Rule of Ordinary People: The Case for a Sortition-Based Democracy without Elections
Bibliographic record
Abstract
In this dissertation, I challenge the orthodox position that elections are the democratic method for selecting political representatives. I reconstruct the concept of democracy shared broadly by democratic theorists to demonstrate that assemblies of randomly selected citizens are more democratic, as representatives of the public, than elected politicians. The primary arguments against randomly selecting legislators focus on the idea that the random selection of legislators is not democratic. Having argued that random selection is more democratic, I divide these criticisms into three different interpretations of why it is normatively significant that the members of the mini-public are not chosen by those whom the mini-public represents, and rebut each of them. In addition to defending the use of legislative mini-publics, I propose and defend institutional blueprints for a political executive and judiciary which put ultimate authority in the hands of randomly selected officials. In doing so I demonstrate that a representative democracy without elections is possible, and that because it would be more democratic, it is the model of democracy which we ought to strive for.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".