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Record W2102257070 · doi:10.12968/bjnn.2005.1.3.18610

The value of working with charities and voluntary agencies

2005· article· en· W2102257070 on OpenAlexaboutno aff
Wendy Kent

Bibliographic record

VenueBritish Journal of Neuroscience Nursing · 2005
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsAllianceQuarter (Canadian coin)Service (business)Affect (linguistics)Value (mathematics)TurnoverPublic relationsQuality (philosophy)MedicineBusinessHealth careNursingPsychologyMarketingPolitical scienceManagement

Abstract

fetched live from OpenAlex

Individuals with neurological conditions have particularly complex and diverse needs, and diagnosis often results in profound life changes which can affect an individual's relationships, career prospects and expectations for the future. The recently published National Service Framework (NSF) for Long-Term Conditions (Department of Health, 2005) states that good communication and the provision of appropriate information are essential features of a quality care service; however, information continues to be given a low priority in the NHS. This is evident from the survey conducted by the Neurological Alliance (2001). Less than a quarter of respondents were happy with the information they received about their conditions from the NHS and felt that voluntary organizations provided the best support. However, it must be recognized that individuals often do not absorb all of the information they are given at time of diagnosis and, therefore, the NHS should not be held solely responsible for the provision of health information. Patients should be given the opportunity to discuss their diagnosis at a time that is convenient to them and from a source that they choose, for example, a specialist health organization.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.232
GPT teacher head0.389
Teacher spread0.158 · 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.

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

Citations0
Published2005
Admission routes1
Has abstractyes

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