MétaCan
Menu
Back to cohort
Record W3200395595 · doi:10.1177/08404704211037794

The promise of transformed long-term care homes: Evidence from the pandemic

2021· review· en· W3200395595 on OpenAlexaffabout
G. Power, Jennifer Carson

Bibliographic record

VenueHealthcare Management Forum · 2021
Typereview
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsResearch Institute for AgingUniversity of Waterloo
Fundersnot available
KeywordsPandemicTollGlobeLivelihoodHealth careCoronavirus disease 2019 (COVID-19)BusinessControl (management)MedicinePublic healthEconomic growthEnvironmental healthNursingDiseaseGeographyEconomicsInfectious disease (medical specialty)Agriculture

Abstract

fetched live from OpenAlex

A combination of factors during the SARS-CoV-2 pandemic led to a disproportionately high mortality rate among residents of long-term care homes in Canada and around the globe. Retrospectively, some of these factors could have been avoided or minimized. Many infection control approaches recommended by public health experts and regulators, while well intended to keep people safe from disease exposure, threatened other vital aspects of health and well-being. Furthermore, focusing narrowly on infection control practices does not address long-standing operational and infrastructural factors that contributed significantly to the pandemic toll. In this article, we review traditional (ie. institutional) long-term care practices that were associated with increased risk during the pandemic and highlight one transformational model (the Green House Project) that worked well to protect the lives and livelihood of people within congregate care settings. Drawing on this evidence, we identify specific strategies for necessary and overdue improvements in long-term care 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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.127
GPT teacher head0.464
Teacher spread0.338 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations10
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueHealthcare Management ForumSame topicGeriatric Care and Nursing HomesFrench-language works237,207