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Record W4297514202 · doi:10.3138/cpp.2022-029

Addressing the Capital Requirement: Perspectives on the Need for More Long-Term-Care Beds in Ontario

2022· article· en· W4297514202 on OpenAlexaffvenueabout
Blair Roblin, Raisa Deber, Andrea Baumann

Bibliographic record

VenueCanadian Public Policy · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsBusinessRedevelopmentCapital (architecture)Long-term careFinancePrivate capitalTerm (time)Capital expenditurePublic economicsEconomic growthEconomicsGeographyNursingMedicineEngineeringProduction (economics)

Abstract

fetched live from OpenAlex

Ontario has an immediate need for 70,000 long-term-care (LTC) beds—38,000 to address current waitlists and a further 32,000 in need of replacement, which together will cost more than $20 billion. This study examines funding sources and requirements and ownership structures in the LTC homes sector in Ontario. Semi-structured interviews were used to understand the ability, challenges, and willingness of LTC home owners to undertake the needed construction. Respondents identified poor access to capital funding, inadequate returns on private capital, differences in funding by ownership model, differing costs by region, and regulatory obstacles. Policy options are identified to overcome constraints and spur construction and redevelopment of LTC homes.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.696

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.006
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.133
GPT teacher head0.397
Teacher spread0.264 · 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 designQualitative
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

Citations13
Published2022
Admission routes3
Has abstractyes

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