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Record W2223482880

Dilemmas of Evaluation, Accountability and Politics: Contracting Out Social Services in Ontario

2003· article· en· W2223482880 on OpenAlexaffabout
Lorne Sossin

Bibliographic record

VenueSSRN Electronic Journal · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsYork University
Fundersnot available
KeywordsAccountabilityBusinessLegislationGovernment (linguistics)Equity (law)Service delivery frameworkSocial WelfarePublic relationsPublic administrationPoliticsPublic sectorService (business)Political scienceMarketingLaw
DOInot available

Abstract

fetched live from OpenAlex

The context of social services raises a host of daunting and crucial questions for the role of government. First, should social services be delivered directly by government or contracted out to private service providers? If contracting out, ought government to distinguish between for-profit institutions and non-profit institutions, and if so, why? On what standards or criteria should government measure the success of contracting out in the social services settings, and how should government ensure accountability of service providers in accordance with public standards and the protection of vulnerable individuals? Finally, what is the public interest in social service delivery and how can government best discharge its duties and obligations in that regard? As I hope to demonstrate through the analysis below, the appropriate role of government relates not to the delivery of social services but to ensuring and enhancing the quality, safety, fairness, accessibility, responsiveness, efficiency, equity and effectiveness of those services. This set of responsibilities entails the capacity of government (whether through legislation, regulation, policy or contract), to develop and implement standards of evaluation and accountability.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2003
Admission routes2
Has abstractyes

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