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‘Covering all the [welfare] basics’: a critical policy study of the Expert Panel on Basic Income report in British Columbia, Canada

2024· article· en· W4393074792 on OpenAlexafffundabout
Tracy Smith‐Carrier, Evelyn L. Forget, Elaine Power, Chloe Halpenny

Bibliographic record

VenueJournal of Poverty and Social Justice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsQueen's UniversityUniversity of ManitobaRoyal Roads University
FundersCanada Research Chairs
KeywordsWelfareBasic incomeEconomicsPolitical sciencePublic economicsLaw

Abstract

fetched live from OpenAlex

In 2018, British Columbia (BC), Canada’s third most populous province, announced the creation of an Expert Panel to explore the feasibility of introducing a basic income in BC. The Expert Panel on Basic Income prepared the policy report, Covering All the Basics: Reforms for a More Just Society, that responded to this task. Our research applies a critical policy studies approach to explore the ideologies, discursive strategies, and discourses embedded in and emanating from the report. In so doing, we find that the report reproduces problematic discourses about self-sufficiency, welfare dependency, and (poor) choice(s). Rather than discarding a basic income for the working-age population based on flawed assumptions and problematic beliefs, we invite policymakers to consider a more transformative vision that recognises the systemic roots of financial hardship, and embraces a basic income as a key building block of income security for BC and all of Canada.

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)0.052
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.762

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0720.034
Scholarly communication0.0230.005
Open science0.0040.007
Research integrity0.0080.013
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.336
Teacher spread0.302 · 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 designQualitative
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

Citations3
Published2024
Admission routes3
Has abstractyes

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