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Record W3030112684 · doi:10.13162/hro-ors.v8i1.4154

Advancing Direct Payment Reforms in Ontario and Scotland

2020· article· fr· W3030112684 on OpenAlexaffvenueabout
Sarah Carbone, Sara Allin

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPaymentDirect PaymentsBusinessPolitical scienceFinance

Abstract

fetched live from OpenAlex

Over the last several decades, there has been an increased interest in cash-for-care programs internationally. Important among these reforms has been the emergence of direct payments (DPs), which are cash payments given directly to individuals so that they can purchase their own community care services. In the mid-1990s, both Ontario and Scotland implemented early direct payment programs with the explicit goals of providing greater choice and control over social services to adults with disabilities. Since then, however, the programs have diverged considerably. In Scotland, negative public perceptions resulted in DPs conversion into a program option embedded within the Self-Directed Support program. In Ontario, DPs have never been required by law and have instead expanded through multiple distinct programs funded through different government ministries. This paper compares the evolution of DPs in these two jurisdictions in order to better understand the actors and mechanisms that contributed to this divergence. Using the 3-I framework, we explore the ideas, interests and institutions that have shaped these reforms into their current structures. Our analysis offers several insights for other jurisdictions considering expanding direct payment reforms. These include recognizing: 1) policy conversion as a tool for managing negative perceptions of a reform, 2) policy levers for encouraging compliance among administering authorities, 3) divisions between health and social care as limiting possible expansion of the reform, and 4) program evaluations as justification for the reform's expansion.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0010.001
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 head0.089
GPT teacher head0.345
Teacher spread0.256 · 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 designObservational
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

Citations1
Published2020
Admission routes3
Has abstractyes

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