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Living While Dying/Dying While Living

2008· article· en· W2124762344 on OpenAlexaff
Carol L. McWilliam, Catherine Ward‐Griffin, Abe Oudshoorn, Elizabeth Krestick

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsHome and Community Care Support ServicesWestern University
Fundersnot available
KeywordsPalliative carePsychosocialContext (archaeology)NursingEnd-of-life careAssisted Living FacilityInterpersonal communicationGerontologyPsychologyAssisted livingMedicineSocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Palliative care involves dynamic relationships among clients, their families, and professionals, all with unique perceptions and approaches to the sociocultural construction of end-of-life care. In the home care context, this subculture may be particularly complex, because clients relate more readily as people than as patients, and professionals are not always prepared for this reality. This article presents ethnographic investigation of the culture of home-based palliative care as experienced by people older than 65 years who are dying of cancer. Through field visits to four client participants over 6 to 10 months, researchers conducted 16 interviews 1 to 2 hours long and participatory observation. Findings portray seniors' dynamic, constantly changing journey of "living while dying/dying while living." At one and the same time, seniors seized the opportunities and interpersonal relationships of "living while dying" and confronted the challenge of "dying while living" through the following: "celebrating life/grieving losses," "connecting with/detaching from others," "resigning to/accepting life circumstances," and "holding on to/moving beyond life in the present moment." The insights gained may inform nurses' provision of psychosocial end-of-life care but suggest that more education, time, and informed collegial and employer support would help to optimize their potential for this challenging role.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.072
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.144
GPT teacher head0.393
Teacher spread0.249 · 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.

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

Citations14
Published2008
Admission routes1
Has abstractyes

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