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Record W2983023303 · doi:10.1111/nup.12289

Exploring a hermeneutic perspective of nursing through revisiting nursing health history

2019· article· en· W2983023303 on OpenAlexaff
Julie Fréchette, Franco A. Carnevale

Bibliographic record

VenueNursing Philosophy · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsShriners Hospitals for Children - CanadaMontreal Children's HospitalDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsPerspective (graphical)AttunementNarrativeNursingHermeneuticsOrientation (vector space)SociologyNursing researchEpistemologyPsychologyMedicinePhilosophyAlternative medicine

Abstract

fetched live from OpenAlex

In this article, the nursing health history is revisited with a hermeneutic lens to uncover means by which this tool can better serve nursing practice. It is argued that further distanciation from the developmental and medical model is necessary to accurately uncover health and history in the nurse-client encounter. Based on the works of prominent hermeneutic philosophers, such as Heidegger, Gadamer, Merleau-Ponty, Ricoeur, and Taylor, four orientations to health history and nursing are explored: orientation to caring, orientation to narrative, orientation to time, and orientation to the body. The nursing health history is used as a vehicle for illuminating the usefulness of a hermeneutic perspective in everyday nursing practice. This article reveals views of health, history, and health history that are already known to nurses and the nursing milieu but are concealed by more dominant outlooks. The hermeneutical perspective presented in this article can help to reveal the important dimensions of everyday nursing practice and foster a richer attunement with the complex health experiences of individuals.

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)0.008
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 score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0080.059
Scholarly communication0.0100.011
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.262
GPT teacher head0.334
Teacher spread0.072 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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