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Record W3031818827 · doi:10.1177/2333393620913269

Ethics of Finitude: Nursing and the Palliative Approach in Geriatric and Forensic Psychiatry

2020· article· en· W3031818827 on OpenAlexaffabout
Elise Skinner, Jean Daniel Jacob, Brandi Vanderspank‐Wright, David Wright

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2020
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPalliative careNursingForensic psychiatryPsychologyEthical issuesMedicinePerspective (graphical)Health carePsychiatryEngineering ethicsPolitical science

Abstract

fetched live from OpenAlex

There is a called-for shift to an upstream provision of palliative care as an overall care approach within a health equity perspective. Our research explored how nurses in psychiatry engage with aging patients and mortality to discern enactment of ethical dimensions of care. Drawing from tenets of interpretative phenomenological analysis, forensic and geriatric psychiatry registered nurses working at a mental health facility in eastern Ontario completed interviews for analysis. Nurses engaged with mortality through a process of recognition and through the affirmation of their values. The affirmed values are aligned with the palliative care approach and within an ethics of finitude lens in that their enactment is partly premised on the recognition of patients' accumulated losses related to human facticities (social, temporal, mortal). This research underscores preliminary insights on a process identifying care practices aligned with the palliative approach and possibilities for expanding upon an ethics of finitude lens.

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)0.028
metaresearch head score (Gemma)0.024
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 score0.028
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.102
Scholarly communication0.0090.009
Open science0.0010.012
Research integrity0.0030.005
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 head0.260
GPT teacher head0.561
Teacher spread0.301 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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