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Record W2763912037 · doi:10.1136/bmj.j4762

CQC is urged to speed up publication of inspection reports

2017· article· en· W2763912037 on OpenAlexaboutno aff
Anne Gulland

Bibliographic record

VenueBMJ · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Services Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPublicationQuarter (Canadian coin)PublishingCommissionGovernment (linguistics)Social careAuditBusinessQuality (philosophy)Health careAnnual reportPolitical scienceMedicinePublic administrationAccountingAdvertisingNursingFinanceLawHistory

Abstract

fetched live from OpenAlex

Inspectors are taking too long to publish their reports of inspections of health and social care providers in England, the government’s spending watchdog has found.1 In a review of the performance of the Care Quality Commission, the National Audit Office found that delays in publishing inspection reports “mean that information is not provided to the public in a timely way.” During 2016-17 and the first quarter of 2017-18 the CQC consistently missed its own target for publishing reports, the NAO found. The CQC pledged to publish 90% of reports within 50 days, or 65 days for hospitals with three or more core services. However, in the first quarter of 2017-18 …

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)0.436
metaresearch head score (Gemma)0.753
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.436
Threshold uncertainty score0.696

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4360.753
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0270.018
Science and technology studies0.0120.012
Scholarly communication0.0380.028
Open science0.0150.028
Research integrity0.0390.048
Insufficient payload (model declined to judge)0.0490.039

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 head0.175
GPT teacher head0.544
Teacher spread0.369 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2017
Admission routes1
Has abstractyes

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