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Record W2088937512 · doi:10.1188/07.cjon.259-263

Building Comfort With Ambiguity in Nursing Practice

2007· article· en· W2088937512 on OpenAlexaff
Kalli Stilos, Shari Moura, Frances Flint

Bibliographic record

VenueClinical journal of oncology nursing · 2007
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsAmbiguityFeelingWitnessNursingNursing theoryHonorMedicineNursing carePsychologyMEDLINESocial psychologyComputer science

Abstract

fetched live from OpenAlex

Current nursing literature recognizes the need to honor the concept of ambiguity. Nurses experience uncertainty with handling or honoring complexity and ambiguity when confronted with times of struggle. Traditional models of care fall short as patients and families define their expectations of the healthcare system. Nurses bear witness to the discomfort caused by the unknown in their daily practice. They are challenged to address their feelings, unsure of what to anticipate, what to say, or how to respond to their patients. Uncertainty diminishes the opportunity for meaningful dialogue between nurses and other people. Nurses attempting to ease the discomfort of ambiguity by providing patients or families with reassurance, offering advice on how to fix problems, or avoiding talking about situations often express dissatisfaction. Nurses should be invited to explore ambiguity and seek understanding through dialogue and nursing knowledge. Encouraging nurses to define the meaningfulness in nursing practice that embraces human science theory will help relieve some of the ambiguity that exists in current practice. This article will explore the concept of ambiguity, highlight how nursing theory based on human science can support practice, and propose recommendations for practice.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.527
Teacher spread0.462 · 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 designOther design
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

Citations17
Published2007
Admission routes1
Has abstractyes

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