Is Canada Ready for Real Poverty Reduction through a Universal Guaranteed Basic Income? A Rejoinder to Kesselman’s “Can ‘Self-Financing’ Redeem the Basic Income Guarantee? Disincentives, Efficiency Costs, Tax Burdens, and Attitudes”
Bibliographic record
Abstract
Rhys Kesselman’s thought-provoking response is part of an important and timely conversation about poverty reduction policy through some form of guaranteed basic income. Our rejoinder first addresses his general concerns about a basic income, which reflect an enduring policy debate over the past half century that has included social experimentation to examine work disincentives and other issues. We then respond to his specific concerns about our proposal for a Universal Guaranteed Basic Income (UGBI) through tax reforms that would convert existing nonrefundable tax credits to refundable credits. We illustrate how our proposed design balances low tax rates that are in line with the rates applied to current credits, prior social experimentation, and policy discussion with effective new income support that eradicates measured poverty for all family groups except non-elderly singles. In this regard, we provide new estimates to show the redistributive effect of our UGBI across family income deciles. Finally, we appraise his alternative proposals for a multifaceted approach to poverty reduction and find these established prescriptions for anti-poverty strategy wanting. We also point out that our UGBI can be implemented gradually by focusing on tax credit refundability in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".