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Record W2024911500 · doi:10.1300/j027v25n03_05

About the Culture of In-Home Nursing

2006· article· en· W2024911500 on OpenAlexaff
Janet Hall, Carol L. Mc William

Bibliographic record

VenueHome Health Care Services Quarterly · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsWestern University
Fundersnot available
KeywordsNursingContext (archaeology)MultitudeEthnographyMedicineTeam nursingNursing homesService (business)Health careNurse educationPsychologySociologyBusinessPolitical science

Abstract

fetched live from OpenAlex

As nurses assume a multitude of roles in health care, public and professional perspectives of nursing vary and, consequently, both clients and providers, including nurses themselves, do not fully appreciate the nature of in-home nursing. In this study ethnographic methods were used to capture participants' perspectives of the actions, practices, values, and beliefs that collectively comprise the culture of nursing in the context of home nursing services in rural Australia. Findings reveal how nurses' and clients' experiences of in-home nursing differ from the textbook picture, and how interactions between nurses' practice approaches and care recipients' enactment of the client role create a cultural context affecting clients' health and well-being. Given similar findings in other countries, the insights gained merit consideration by all professionals concerned about refining home care service approaches in keeping with currently espoused valuing of client-centered, empowering care partnerships.

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)0.007
metaresearch head score (Gemma)0.010
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 score0.015
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.032
Scholarly communication0.0100.006
Open science0.0010.006
Research integrity0.0020.006
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 head0.012
GPT teacher head0.356
Teacher spread0.344 · 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
Published2006
Admission routes1
Has abstractyes

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