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SCHOLARLY PAPER: Defining the fundamentals of care

2010· article· en· W1579394414 on OpenAlexaff
Alison Kitson, Tiffany Conroy, Yvonne Wengström, Joanne Profetto‐McGrath, Suzanne Robertson-Malt

Bibliographic record

VenueInternational Journal of Nursing Practice · 2010
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNursing careHealth careArgument (complex analysis)NarrativeNursingQuality (philosophy)Process (computing)PsychologyMedicineComputer scienceEpistemologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

A three-stage process is being undertaken to investigate the fundamentals of care. Stage One (reported here) involves the use of a met a-narrative review methodology to undertake a thematic analysis, categorization and synthesis of selected contents extracted from seminal texts relating to nursing practice. Stage Two will involve a search for evidence to inform the fundamentals of care and a refinement of the review method. Stage Three will extend the reviews of the elements defined as fundamentals of care. This introductory paper covers the following aspects: the conceptual basis upon which nursing care is delivered; how the fundamentals of care have been defined in the literature and in practice; an argument that physiological aspects of care, self-care elements and aspects of the environment of care are central to the conceptual refinement of the term fundamentals of care; and that efforts to systematize such information will enhance overall care delivery through improvements in patient safety and quality initiatives in health systems.

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)0.036
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0060.024
Scholarly communication0.0230.019
Open science0.0040.009
Research integrity0.0060.008
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 head0.087
GPT teacher head0.559
Teacher spread0.472 · 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 designTheoretical or conceptual
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

Citations240
Published2010
Admission routes1
Has abstractyes

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