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Record W2079167989 · doi:10.2190/il.20.3.c

Narratives of Neonatal Intensive Care Unit Nurses: Experience with End-of-Life Care

2012· article· en· W2079167989 on OpenAlexaff
Gail Lindsay, Nadine Cross, Lori Ives-Baine

Bibliographic record

VenueIllness Crisis & Loss · 2012
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsHospital for Sick ChildrenYork UniversityOntario Tech University
Fundersnot available
KeywordsPraxisNarrativeNeonatal intensive care unitTransferabilityNursingEnd-of-life careIntensive carePsychologyThe artsLived experienceMedicinePalliative carePediatricsPsychotherapistPolitical science

Abstract

fetched live from OpenAlex

The purpose of this interpretive narrative research is to explore the experiences of Neonatal Intensive Care Unit (NICU) nurses with end-of-life care of infants and their families. Guided by Newman's Research-as-Praxis, we met with nurse participants from a tertiary care NICU twice in small groups and once on the telephone to share their stories. Patterns of relationship were discerned and shared with our participants for their affirmation, challenge, and elaboration. NICU nurses' end-of-life experiences include relationship patterns, knowledge construction, and tensions of temporal and spatial proximity of suffering and death. Arts-based forms of dissemination of our findings have been developed to invite readers into reconstruction of their experiences and to demonstrate the transferability of the method.

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)0.009
metaresearch head score (Gemma)0.026
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 score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.012
Scholarly communication0.0060.007
Open science0.0020.010
Research integrity0.0020.005
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 head0.066
GPT teacher head0.394
Teacher spread0.328 · 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

Citations28
Published2012
Admission routes1
Has abstractyes

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