The Impacts of the Ontario Basic Income Pilot: A Comparative Analysis of the Findings from the Hamilton Region
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
Abstract This article provides the findings of a quantitative and qualitative study of participants from the prematurely cancelled Ontario Basic Income Pilot in the Hamilton region. We compare our evidence with those of other large-scale experiments from the high-income countries between 1968 and 2019 to place OBIP’s findings in the context of evidence from randomized control experiments with similar policy conditions to Ontario’s. Our study identified a small decline in labour market participation, but improvements on a variety of quality-of-life measurements. We hypothesize that OBIPs comparatively positive results on general well-being can be attributed to its: i) generous benefit rates relative to social assistance rates; ii) 50 percent take back rate; and iii) unconditionality; iv) broad well-being/welfare design.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it