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Record W595072097

Shaping the future of care together

2009· book· en· W595072097 on OpenAlexaboutno aff
Building Britain's future, Care Support Independence

Bibliographic record

VenueTSO eBooks · 2009
Typebook
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)General partnershipGovernment (linguistics)Service (business)BusinessWork (physics)Activity-based costingPublic relationsPublic economicsFinancePolitical scienceMarketingEconomicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

This Green Paper, Shaping the Future of Care Together (Cm. 7673), sets out the Government's proposals for reforming the care and support system for adults in England and to establish a National Care Service. Care and support help people stay as independent, active, safe and well as possible, and to participate in and contribute to society throughout the different stages of their lives. Need for care and support can increase as a result of accidents, long-term illnesses, disability and growing older. The proposed National Care Service will provide six basic services: prevention; assessment; a joined-up service; information and advice; personalised care and support; and, fair funding. The Green paper explores ways in which different services can work together, a wider range of services can be developed, and better quality and innovation be achieved. The choices around funding are crucial to the reforms. The cost of care and support is high (a 65-year-old man can expect to need care costing GBP 30,000 during retirement). The Government has ruled out people paying for all of the costs or use of a tax-funded scheme (deemed unfair on those of working age). The options for funding being proposed are: partnership, where the state would pay, for those who qualified for support, a quarter to a third of the basic care and support, with extra help for the less well-off; insurance (either private or a state scheme) to cover costs above the quarter to a third met by the state; and, comprehensive, where everyone over retirement age who could afford it would be required to pay into a state insurance scheme.

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)0.035
metaresearch head score (Gemma)0.026
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: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0330.047
Scholarly communication0.0330.048
Open science0.0040.050
Research integrity0.0310.038
Insufficient payload (model declined to judge)0.0260.006

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 head0.066
GPT teacher head0.358
Teacher spread0.292 · 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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