Are Americans Stuck in Uncompetitive Enclaves? An Appraisal of U.S. Electoral Competition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Most elections in the United States are not close, which has raised concerns among social scientists and reform advocates about the vibrancy of American democracy. In this paper, we demonstrate that while individual elections are often uncompetitive, hierarchical, temporal, and geographic variation in the locus of competition results in most of the country regularly experiencing close elections. In the four-cycle period between 2006 and 2012, 89% of Americans were in a highly competitive jurisdiction for at least one office. Since 1914, about half the states have never gone more than four election cycles without a close statewide contest. More Americans witness competition than citizens of Canada or the UK, other nations with SMSP-based systems. The dispersed competition we find also results in nearly all Americans being represented by both political parties for different offices.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it