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Record W2027186330 · doi:10.1068/c0434

Co-Opting Voluntarism? Exploring the Implications of Long-Term Care Reform for the Nonprofit Sector in Ontario

2005· article· en· W2027186330 on OpenAlexaffabout
Mark W. Skinner, Mark W. Rosenberg

Bibliographic record

VenueEnvironment and Planning C Government and Policy · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsQueen's University
Fundersnot available
KeywordsVoluntarism (philosophy)RestructuringPublic administrationPublic sectorHealth careGovernment (linguistics)BusinessPrivate sectorPublic relationsPolitical scienceEconomic growthEconomicsFinanceLaw

Abstract

fetched live from OpenAlex

Within public policy discourse on health care restructuring and voluntarism, the nonprofit sector is now expected to play an active and direct role in the provision of health care services. The viability of the nonprofit sector to take up this role, however, remains unclear. This paper explores the changing role of nonprofit organisations with respect to the provision of long-term care in Ontario, Canada, where extensive restructuring of public services occurred during the 1990s. Drawing on a critical review of legislation, government policies and documents, and stakeholder reports, the authors present a comparative study of two distinct long-term care reform models, featuring public and private provision, respectively, which were developed by ideologically opposed provincial governments. The results indicate that despite unanimous promotion of voluntarism (and the attendant ascendancy of the nonprofit sector) as a central feature of health care restructuring, the divergent reform models actually trap nonprofit organisations between direct incorporation within public provision on the one hand, and direct free-market competition on the other. The findings suggest that underscoring long-term care reform in Ontario, and elsewhere, is the co-option of the nonprofit sector, which resonates with concern for its ability to replace effectively the public provision of health care services. The results also point to the need to conceptualise the consequent actions taken by nonprofit organisations in order to inform current debates surrounding health care restructuring and voluntarism.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.948

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 studies0.0010.000
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 head0.046
GPT teacher head0.301
Teacher spread0.255 · 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

Citations39
Published2005
Admission routes2
Has abstractyes

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