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Record W3091338617 · doi:10.1177/0733464820961257

A Survey of the Characteristics and Administrator Perceptions of Family Councils in a Western Canadian Province

2020· article· en· W3091338617 on OpenAlexaffabout
Jennifer Baumbusch, Isabel Sloan Yip, Sharon Koehn, R. Colin Reid, Preet Gandhi

Bibliographic record

VenueJournal of Applied Gerontology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsAccreditationLong-term carePerceptionFocus groupPsychologyMedicineNursingBusinessMedical educationMarketing

Abstract

fetched live from OpenAlex

Family Councils are independent, self-determining groups composed of family members (inclusive of friends) who have assembled with the main purpose of protecting and improving the quality of life of those living in long-term care (LTC) homes. This study aimed to describe the prevalence and characteristics of Family Councils in British Columbia, Canada. We conducted a cross-sectional survey with administrators of 259 homes and received 222 usable surveys. Of the 151 LTC homes that had Family Councils, it was most common for the homes to be larger (>50 residents), accredited, privately owned, and located in urban areas. Perceived barriers to Family Councils included lack of interest, tendency to focus on individual complaints, and the transitory nature of families. Perceived benefits of Family Councils included enhanced communication between staff and families, peer support, and collective advocacy. Recommendations focus on enhancing accessibility, information sharing, and meaningfulness of Family Councils to improve family engagement.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.096
GPT teacher head0.363
Teacher spread0.267 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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