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Record W2133823756 · doi:10.12927/hcpol.2009.20936

Three Policy Issues in Deciding the Cost of Nursing Home Care: Provincial Differences and How They Influence Elderly Couples' Experiences

2009· article· en· W2133823756 on OpenAlexafffundvenueabout
Robin Stadnyk

Bibliographic record

VenueHealthcare policy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsDalhousie University
FundersUniversity of Toronto
KeywordsNursing homesNursingPsychologyGerontologyMedicine

Abstract

fetched live from OpenAlex

Nursing home care is subsidized in all Canadian provinces, but residents must personally contribute to the cost. This paper explores policy issues that have led to differences in costs of nursing home care among provinces, and how policy and cost differences influence the experiences of married couples when one spouse requires nursing home care. The paper is based on a multiple-case study of three Canadian provinces, each of which had a different system for determining personal contributions to the cost of care. Cross-case analysis of payment systems showed that provinces addressed three main policy issues in determining the cost of care: (a) what costs should be the responsibility of nursing home residents, (b) how subsidies should be determined and (c) how community-dwelling spouses of nursing home residents should be assured of an adequate income. In provinces with policies that resulted in higher care costs to couples and lower amounts of income and assets available to the community-dwelling spouses, study participants described reduced discretionary spending, increased financial concerns and perceptions of system unfairness. This paper discusses the implications of these three policy issues and recent related changes to provincial policies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.028
GPT teacher head0.367
Teacher spread0.339 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2009
Admission routes4
Has abstractyes

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