Ensuring Equity: Investigation Of The Impact Of A Guaranteed Annual Income On The Homeless Population Of Binghamton
Bibliographic record
Abstract
The homeless population of Broome County has grown by 50% from 2020 to 2022. While traditional social programs to address homelessness have emphasized shelters, rehabilitation programs, and supportive housing, a growing body of evidence suggests that direct cash transfers to the homeless carry substantial benefits. A study in Vancouver found that cash aid recipients significantly reduced nights spent outdoors and in shelters; advocates also argue that cash is empowering and less paternalistic than in-kind benefits. This project asks how direct cash transfers, in the form of a guaranteed annual income (GAI), would affect Binghamton’s homeless population. Using demographic statistics, pilot program data, a review of public policy scholarship, and interviews conducted with local organizations, this research explores the potential impact of a GAI on the local homeless community. The benefits include reduction in healthcare spending, increased health, better social relations, increased savings, increased housing stability, and ability to meet basic needs.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".