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A focus for nursing intervention: Realistic acceptance or helping illusions?

2004· article· en· W2129616055 on OpenAlexafffund
José Côté, Carolyn Pepler

Bibliographic record

VenueInternational Journal of Nursing Practice · 2004
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsMcGill UniversityUniversité de Montréal
FundersCanadian Nurses Foundation
KeywordsGriefIllusionIntervention (counseling)LimitingNursingPsychologyReflection (computer programming)MedicineWork (physics)PsychotherapistComputer scienceCognitive psychology

Abstract

fetched live from OpenAlex

Despite having a life-threatening disease, some people decide to live every remaining moment with intensity. Although they have accepted that their deaths might be imminent, they do not dwell on the possibility. They choose life and are sustained by vivid thoughts and inspirations. What can a nurse do to nourish such thoughts? Traditional theories of grief and loss maintain that one way to adjust to advanced stages of progressive disease is to accept death and prepare for it. Is it possible that these theories are simplistic and limiting in their assumptions about the way people "work through" the stage of adjusting to loss? This article is a critical reflection of the process.

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)0.010
metaresearch head score (Gemma)0.031
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0030.011
Scholarly communication0.0040.012
Open science0.0020.006
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0060.001

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 head0.465
Teacher spread0.399 · 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

Citations7
Published2004
Admission routes2
Has abstractyes

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