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Record W3207980529 · doi:10.1177/23333936211051702

Visitor Restrictions, Palliative Care, and Epistemic Agency: A Qualitative Study of Nurses’ Relational Practice During the Coronavirus Pandemic

2021· article· en· W3207980529 on OpenAlexaffabout
Kim McMillan, David Wright, Christine McPherson, Kristina Ma, Vasiliki Bitzas

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversity of Ottawa
Fundersnot available
KeywordsPalliative careAgency (philosophy)PandemicHumanityVisitor patternNursingHealth careMoral agencyAction (physics)PsychologyCoronavirus disease 2019 (COVID-19)Qualitative researchSociologyMedicinePolitical scienceSocial psychologyLawSocial scienceDisease

Abstract

fetched live from OpenAlex

Efforts to curb spread of COVID-19 has led to restrictive visitor policies in healthcare, which disrupt social connection between patients and their families at end of life. We interviewed 17 Canadian nurses providing palliative care, to solicit their descriptions of, and responses to, ethical issues experienced as a result of COVID-19 related circumstances. Our analysis was inductive and scaffolded on notions of nurses' moral agency, palliative care values, and our clinical practice in end-of-life care. Our findings reveal that while participants appreciated the need for pandemic measures, they found blanket policies separating patients and families to be antithetical to their philosophy of palliative care. In navigating this tension, nurses drew on the foundational values of their practice, engaging in ethical reasoning and action to integrate safety and humanity into their work. These findings underscore the epistemic agency of nurses and highlight the limits of a purely biomedical logic for guiding the nursing ethics of the pandemic response.

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)0.025
metaresearch head score (Gemma)0.113
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.113
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0040.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.007
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 head0.389
GPT teacher head0.682
Teacher spread0.293 · 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 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

Citations33
Published2021
Admission routes2
Has abstractyes

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