Bibliographic record
Abstract
This paper estimates the political and economic effects of the 19th century disenfranchisement of black citizens in the U.S. South. Using adjacent county-pairs that straddle state boundaries, I examine the effect of voting restrictions on political competition, public goods, and factor markets. I find that poll taxes and literacy tests each lowered overall electoral turnout by 8-22% and increased the Democratic vote share in elections by 1-7%. Employing newly collected data on schooling inputs, I show that disenfranchisement reduced the teacher-child ratio in black schools by 10-23%, with no significant effects on white teacher-child ratios. I develop a model of suffrage restriction and redistribution in a 2-factor economy with migration and agricultural production to generate sufficient statistics for welfare analysis of the incidence of black disenfranchisement. Consistent with the model, disenfranchised counties experienced a 3.5% increase in farm values per acre, despite a 4% fall in the black population. The estimated factor market responses suggest that black labor bore a collective loss from disenfranchisement equivalent to at least 15% of annual income, with landowners experiencing a 12% gain.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".