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Record W3036353936 · doi:10.3138/cpp.2020-080

Radical Incrementalism and Trust in the Citizen: Income Security in Canada in the Time of COVID-19

2020· article· en· W3036353936 on OpenAlexaffvenueabout
Jennifer Robson

Bibliographic record

VenueCanadian Public Policy · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Incrementalism2019-20 coronavirus outbreakPeriod (music)Minor (academic)Security policyEconomicsPublic economicsPublic administrationPolitical scienceBusinessLawComputer security

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.944

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0100.009
Scholarly communication0.0090.002
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.039
GPT teacher head0.232
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2020
Admission routes3
Has abstractyes

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