Legislature Size and Non-Elite Populations Theory and Corroborating Evidence
Bibliographic record
Abstract
<p>This research tests the association between legislature size and the size of ‘non-elite’ populations in the American states. The theoretical assumption is that larger legislatures will be populated by a more diverse group of members, who will better represent and advocate for non-elites. Data are drawn from three time periods, which captures considerable variation in important variables, and provides a robust test of association between the size of state legislatures and certain sub-populations. The research demonstrates that larger Lower Chambers are marginally associated with a lower percentage of adults without a high school diploma, easily associated with a larger percentage of the states’ poor receiving Medicaid, and also related to smaller state prison populations. This is the case after controlling for demographic and economic factors that also predict the size of these sub-populations. The findings suggest legislature size plays a role in dominant contemporary policy arenas and that there may be societal benefits associated with larger—more diverse—assemblies.</p>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".