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Record W2416111942 · doi:10.12927/hcq.2015.24247

Reforming Long-Term Care Funding in Alberta.

2015· article· en· W2416111942 on OpenAlexaffabout
Trafford Crump, Nadya Repin, Jason M. Sutherland

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsVancouver Coastal Health
Fundersnot available
KeywordsGovernment (linguistics)Term (time)Strengths and weaknessesLong-term careBusinessPaymentBest practiceNursingMedicinePolitical scienceFinancePsychology

Abstract

fetched live from OpenAlex

Like many provinces across Canada, Alberta is facing growing demand for long-term care. Issues with the mixed funding model used to pay long-term care providers had Alberta Health Services concerned that it was not efficiently meeting the demand for long-term care. Consequently, in 2010, Alberta Health Services introduced the patient/care-based funding (PCBF) model. PCBF is similar to activity-based funding in that it directly ties the complexity and care needs of long-term care residents to the payment received by long-term care providers. This review describes PCBF and discusses some of its strengths and weaknesses. In doing so, this review is intended to inform other provinces faced with similar long-term care challenges and contemplating their own funding reforms.

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)0.005
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.518

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0030.002
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.166
GPT teacher head0.374
Teacher spread0.208 · 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
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

Citations3
Published2015
Admission routes2
Has abstractyes

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