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Record W2041629497 · doi:10.1017/s1478951507070058

Struggling in change at the end of life: A nursing inquiry

2007· article· en· W2041629497 on OpenAlexaff
Deanna Hutchings

Bibliographic record

VenuePalliative & Supportive Care · 2007
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMeaning (existential)Perspective (graphical)Exploratory researchExtant taxonFace (sociological concept)PsychologyHuman lifePalliative careSociologyNursingMedicinePsychotherapistSocial science

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this human science nursing inquiry is to explore the meaning of struggling in change for persons at the end of life. METHODS: Guided by Parse's theory of human becoming, a descriptive exploratory method was used to answer the research question: What is the meaning of the experience of struggling in change for persons at the end of life? Eight persons who were living with dying described experiences of struggling in change during face-to-face audiotaped interviews. RESULTS: A process of analysis-synthesis revealed three themes that are discussed in relation to extant related literature and interpreted in light of the human becoming perspective. SIGNIFICANCE OF RESULTS: Findings from the study contribute new knowledge about human experience at the end of life from a human science perspective and offer new insights on struggling in change as a rhythmical pattern of living and dying. Implications for palliative practice, research, and education are discussed.

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)0.011
metaresearch head score (Gemma)0.015
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 score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0090.017
Scholarly communication0.0060.005
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.211
GPT teacher head0.458
Teacher spread0.246 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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