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Record W4405691809 · doi:10.1017/s1474746424000551

“I Was Trusted for Once”: Imagining More Humane Income Supports Through the Ontario Basic Income Pilot

2024· article· en· W4405691809 on OpenAlexafffundabout
Kendal David, Beth Martin, Tom McDowell, Mohammad Ferdosi, Rebekah Ederer, Amy Ma

Bibliographic record

VenueSocial Policy and Society · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsToronto Metropolitan UniversityMcMaster UniversityCarleton University
FundersSocial Sciences and Humanities Research Council of CanadaMcMaster University
KeywordsBasic incomeLow incomePsychologyBusinessDemographic economicsSociologyEconomicsMarket economy

Abstract

fetched live from OpenAlex

Current social assistance programmes in Canada and beyond have been criticised for normalising the dehumanisation of recipients through policy design and implementation. In this article we look at how exposure to a form of basic income through the Ontario Basic Income Pilot (OBIP) allowed recipients to imagine a different kind of support. We report on the findings from a study in OBIP from Hamilton, Canada, thematically analysing a subset of interviews with forty OBIP participants. We find that the higher levels of support, fewer behavioural conditions compared to social assistance, and reduced surveillance under OBIP-nurtured feelings of trust and confidence. Participants felt rehumanised as full members of society in reciprocal relationships with community and government that had been strained under previous forms of social assistance. We consider how the OBIP model provided a transformative framework for participants’ expectations for income support programmes and discuss implications for future research.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.376
Teacher spread0.327 · 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 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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