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Record W3137409732 · doi:10.1139/facets-2021-0015

The need for a federal Basic Income feature within any coherent post-COVID-19 economic recovery plan

2021· article· en· W3137409732 on OpenAlexaffvenueabout
Hugh Segal, Keith Banting, Evelyn L. Forget

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of ManitobaQueen's University
Fundersnot available
KeywordsPovertyGovernment (linguistics)PopulationEconomic growthBasic needsWelfareBusinessEconomicsMedicineEnvironmental health

Abstract

fetched live from OpenAlex

COVID-19 has shone a harsh light on the extent of poverty in Canada. When normal economic activity was interrupted by the exigencies of public health driven lockdowns, the shutdown disproportionately affected people who, before the pandemic, were living on incomes beneath the poverty line or dependent upon low-paying hourly remunerated jobs, usually part time and without appropriate benefits. Those living beneath the poverty line in Canada, three million of welfare poor and working poor, include a disproportionately large population of Black and Indigenous people and people of colour. This paper addresses the challenge of inclusive economic recovery. In particular, we propose that the federal government introduce a Basic Income guarantee for all residents of Canada as part of a comprehensive social safety net that includes access to housing, child care, mental and physical health care, disability supports, education, and the many other public services essential to life in a high-income country. Residents with no other income would receive the full benefit that would be sufficient to ensure that no one lives in poverty, while those with low incomes would receive a reduced amount.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.380
Teacher spread0.325 · 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 teacher head, not a consensus.

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

Citations6
Published2021
Admission routes3
Has abstractyes

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