The Link Between Financial Insecurity and Crime: Would a UBI Help?
Bibliographic record
Abstract
In the United States, sky-high incarceration rates disproportionately impact marginalized low-income communities and particularly communities of color. Without a financial security net, people are more exposed to food insecurity, stress, school incompletion and other factors associated with crime. While the current welfare system provides some assistance, its limitations hinder individuals' economic autonomy and fall short of fully addressing the root causes of poverty. In order to understand whether a universal basic income (UBI) would be more effective in reducing crime, this research analyzes the impact of Latin American conditional cash transfer programs, Alaska’s Permanent Fund Dividend, and the Canadian Mincome experiment on crime rates. It is then considered how the demonstrated link between increased anti-poverty spending and decreased crime might apply to a basic income in the US. Evidence suggests that the cost of a UBI might be offset by resulting decreases in policing, incarceration, and other costs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".