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Record W2011429617 · doi:10.1353/cja.2005.0002

Observations on Institutional Long-Term Care in Ontario: 1996–2002

2005· article· en· W2011429617 on OpenAlexaffabout
Whitney Berta, Audrey Laporte, Vivian Valdmanis

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStaffingLong-term careBusinessProfit (economics)Government (linguistics)Nursing homesFor profitDescriptive statisticsFinanceNursingMedicineEconomicsStatistics

Abstract

fetched live from OpenAlex

We provide descriptive statistics for data collected via the Residential Care Facilities Survey (RCFS), from long-term care (LTC) facilities operating in Ontario between 1996 and 2002. The LTC sector in Ontario is dominated by large, proprietary for-profit facilities. The proportion of residents receiving extended care has increased from 53 per cent in 1996 to over 61 per cent in 2002. Government-owned facilities are significantly larger than both for-profit proprietary facilities and lay non-profit facilities. Religious and lay non-profit facilities provide care to more residents 85 years of age and older than do for-profit and government-owned facilities, while government-owned facilities provide care to a greater proportion of higher needs residents. Government-owned facilities have higher nursing intensity levels and higher direct care staffing levels than other ownership types, while for-profit facilities have significantly lower levels than other facility types. Non-profit operators have higher ratios of administrative to care staff than proprietary and government-owned facilities.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.008
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.288
Teacher spread0.255 · 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 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

Citations50
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicGeriatric Care and Nursing HomesFrench-language works237,207