Testing Time: Uncovering Potential Impacts of Project Duration in Basic Income Pilots
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
In recent years, basic income – sometimes referred to as universal basic income, or, guaranteed annual income – has resurfaced as a mainstream policy proposal. Basic income, in its simplest form, is an unconditional cash transfer from government to individuals or families that provides more dignity to recipients when compared to existing social assistance programs. \n \nThere is a growing appetite in Canada to develop more effective poverty reduction strategies, and Ontario has recently taken the lead with a newly deployed Basic Income Pilot Project. This pilot, and others alike, are testing how recipients will use basic income, and whether such a policy would be an innovative replacement for the complicated, contentious, and costly systems currently in place. \n \nThe research question in this Major Research Project (MRP) investigates the potential behavioural differences between short-term basic income pilot projects, and permanent policies. With a permanent basic income yet to be implemented, an experimental method was developed to better understand these potential differences. \n \nUsing ‘Structured Scenario Interviews’, the research found significant differences in the ways participants allocated basic income across two hypothetical time-based scenarios: a one-year basic income pilot; and a permanent policy. This method can be used as a complementary tool to adjust policies in existing pilot projects, allowing research teams to better understand expected behaviours under shorter time horizons. The method is applicable to basic income pilot projects in any jurisdiction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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 it