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The role of charitable funding in the provision of public services: the case of the English and Welsh National Health Service

2023· article· en· W4323922440 on OpenAlexfundno aff
Helen Abnett, James Bowles, John Mohan

Bibliographic record

VenuePolicy & Politics · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
FundersEconomic and Social Research CouncilQueen's UniversityWellcome Trust
KeywordsWelshOptimal distinctiveness theoryGovernment (linguistics)Public relationsPluralism (philosophy)Public administrationService (business)Political scienceBusinessMarketingPsychologySocial psychology

Abstract

fetched live from OpenAlex

The role of charity in the provision of public services is of substantial academic and practitioner interest, and charitable initiative within the English and Welsh National Health Service (NHS) has recently received considerable attention. This study provides rich insights into the role that NHS-linked charities present themselves as playing within the NHS. The dataset analysed is a novel construction of 3,250 detailed expenditure lines from 676 sets of charity accounts. Qualitative content analysis of itemised descriptions of expenditure allows us to explore how these charities portray their activities. We distinguish between expenditures that can be framed as supplementary to government funding (such as amenities and comforts) and items that suggest charitable effort is substituting for government support (such as funding for clinical equipment). We also consider the claims being made through these representations, and suggest that the distinctiveness of the charity and NHS spheres are currently under question. We argue that, through their representational practices, charities are both shaping and blurring the expected roles of government and charity. Acceptance of the benefits that charitable initiative does provide, in terms of innovation, pluralism and participation, must be tempered with the realisation that charitable funds are playing a role in service provision that is not guided by clear policy, and that this has the potential to widen existing inequalities within a key public service.

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)0.020
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.190
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0180.019
Scholarly communication0.0120.007
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.083
GPT teacher head0.451
Teacher spread0.368 · 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 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

Citations12
Published2023
Admission routes1
Has abstractyes

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