The disastrous business of presidential campaigns: The effect of disaster declarations on presidential elections in FEMA Region 3
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
The issuance of disaster declarations has become a politicized matter. Prior research has demonstrated that presidents are more generous in awarding disaster relief in federal election years, and that there is a prevalence to award governors from the opposing political party. Additionally, voters tend to reward presidents seeking re-election to a greater degree for disaster response assistance rather than funding preparedness. The original research for this paper explores the impact of natural disasters on re-election rates and analyzes voter trends during presidential election years in Federal Emergency Management Agency (FEMA) Region 3 states for congruence with existing literature covering a national scope. Evaluations of the behaviors and (re)election margins of Presidents Bush and Obama are explored, and implications for President Trump's re-election effort are based on quantitative data and qualitative comparisons.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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