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Record W2560074616 · doi:10.1017/s135732171600012x

The future of social care funding: who pays?

2016· article· en· W2560074616 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBritish Actuarial Journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsBishop's University
Fundersnot available
KeywordsIncentivePublic economicsBusinessPopulation ageingGovernment (linguistics)CommissionPopulationEconomicsActuarial scienceFinanceMedicine

Abstract

fetched live from OpenAlex

Abstract With the UK population ageing, deciding upon a satisfactory and sustainable system for the funding of people’s long-term care ( LTC ) needs has long been a topic of political debate. Phase 1 of the Care Act 2014 (“the Act”) brought in some of the reforms recommended by the Dilnot Commission in 2011. However, the Government announced during 2015 that Phase 2 of “the Act” such as the introduction of a £72,000 cap on Local Authority care costs and a change in the means testing thresholds 1 would be deferred until 2020. In addition to this delay, the “ freedom and choice ” agenda for pensions has come into force. It is therefore timely that the potential market responses to help people pay for their care within the new pensions environment should be considered. In this paper, we analyse whether the proposed reforms meet the policy intention of protecting people from catastrophic care costs, whilst facilitating individual understanding of their potential care funding requirements. In particular, we review a number of financial products and ascertain the extent to which such products might help individuals to fund the LTC costs for which they would be responsible for meeting. We also produce case studies to demonstrate the complexities of the care funding system. Finally, we review the potential impact on incentives for individuals to save for care costs under the proposed new means testing thresholds and compare these with the current thresholds. We conclude that: ∙ Although it is still too early to understand exactly how individuals will respond to the pensions freedom and choice agenda, there are a number of financial products that might complement the new flexibilities and help people make provision for care costs. ∙ The new care funding system is complex making it difficult for people to understand their potential care costs. ∙ The current means testing system causes a disincentive to save. The new means testing thresholds provide a greater level of reward for savers than the existing thresholds and therefore may increase the level of saving for care; however, the new thresholds could still act as a barrier since disincentives still exist.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.999

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 head0.031
GPT teacher head0.336
Teacher spread0.305 · 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