Radical Incrementalism and Trust in the Citizen: Income Security in Canada in the Time of COVID-19
Bibliographic record
Abstract
This article documents Canada's main public policy responses to promote income security among working-age adults during the coronavirus disease 2019 (COVID-19) crisis between March and early June 2020. This period of rapid policy change unfolded broadly in three phases, starting with minor adjustments to existing policy instruments, followed by larger amendments to a wider range of programs, and finally ending with the creation of new and quite generous benefits. The pathway of policy change is best described as incremental, but it resulted in a more radical shift to "trust but verify" to administer benefits rather than the pre-COVID-19 practice of verifying eligibility before paying benefits. The reasons and precedents for this decision are discussed. I conclude with some observations on the applicability and limitations of trust but verify for income security policy in the post-COVID-19 period.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".