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Record W2059577525 · doi:10.1108/13595474200100034

Improving Service Quality through Linked Services Development

2001· article· en· W2059577525 on OpenAlexfundno aff
Jill Bradshaw

Bibliographic record

VenueTizard Learning Disability Review · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
FundersMcGill University
KeywordsGeneral partnershipService providerService (business)BusinessWork (physics)Quality (philosophy)Public relationsCommunity serviceMarketingEngineeringPolitical scienceFinance

Abstract

fetched live from OpenAlex

The University Affiliated Programme (UAP) aims to improve service quality by working in partnership with local services. This article Reports on the establishment and development of linked services: three services for people with learning disabilities, living in small community houses that opened in late 1999 and early 2000. The focus of resources on a small number of linked services was designed to maximise the effectiveness of the involvement of the Tizard Centre, along with the Subscriber Network. It was intended that work in the linked services would be disseminated through this network. The UAP has worked with service users and providers since 1996, during which time users have moved from a long‐stay NHS hospital to community services. The service provider is also now a private organisation. The article outlines some of the projects which have been introduced or developed in these linked services and discusses some of the issues that have arisen while working in partnership with them. The benefits of working through a UAP will also be identified.

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)0.024
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.009
Science and technology studies0.0020.001
Scholarly communication0.0070.006
Open science0.0020.010
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.144
GPT teacher head0.439
Teacher spread0.296 · 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 designNot applicable
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
Published2001
Admission routes1
Has abstractyes

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