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Record W4312000473 · doi:10.12927/hcq.2022.26979

Experiences of Essential Care Partners during the COVID-19 Pandemic

2022· article· en· W4312000473 on OpenAlexaffvenue
Pauline Johnston, Margaret Keatings, Allan Monk

Bibliographic record

VenueHealthcare Quarterly · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsDairy Farmers of Ontario
Fundersnot available
KeywordsPandemicPreparednessCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakNursingSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Long-term carePersonal protective equipmentBest practiceQuality (philosophy)MedicineBusinessPublic relationsPsychologyPolitical scienceVirology

Abstract

fetched live from OpenAlex

Visitor restrictions in long-term care (LTC) have had many consequences for residents, their families and care providers. The value of family presence in LTC was obscured during the COVID-19 pandemic until the designation of essential care partners (ECPs) was introduced to support the re-entry of family caregivers into LTC. Three ECPs share their personal experiences of caring for a loved one in LTC before and during the pandemic. Partnerships with LTC homes, residents, families and ECPs are identified as a unifying way forward to bolster future pandemic preparedness and ensure that current and future residents receive safe and high-quality care.

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)0.006
metaresearch head score (Gemma)0.012
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 score0.014
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0120.006
Scholarly communication0.0050.005
Open science0.0010.013
Research integrity0.0020.005
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 head0.062
GPT teacher head0.439
Teacher spread0.377 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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