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Record W2472637513 · doi:10.3928/01484834-20070201-08

Patient Safety: Where Is Nursing Education?

2007· review· en· W2472637513 on OpenAlexaff
David Gregory, Lorna Guse, Diana Davidson Dick, Cynthia K. Russell

Bibliographic record

VenueJournal of Nursing Education · 2007
Typereview
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsSaskatchewan PolytechnicUniversity of ManitobaUniversity of Lethbridge
Fundersnot available
KeywordsMemphisPatient safetyRubricHealth careNursingPsychologyMedicineMedical educationPedagogyPolitical science

Abstract

fetched live from OpenAlex

Patient safety is receiving unprecedented attention among clinicians, researchers, and managers in health care systems. In particular, the focus is on the magnitude of systems-based errors and the urgency to identify and prevent these errors. In this new era of patient safety, attending to errors, adverse events, and near misses warrants consideration of both active (individual) and latent (system) errors. However, it is the exclusive focus on individual errors, and not system errors, that is of concern regarding nursing education and patient safety. Educators are encouraged to engage in a culture shift whereby student error is considered from an education systems perspective. Educators and schools are challenged to look within and systematically review how program structures and processes may be contributing to student error and undermining patient safety. Under the rubric of patient safety, the authors also encourage educators to address discontinuities between the educational and practice sectors.

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)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.005
Science and technology studies0.0020.004
Scholarly communication0.0060.008
Open science0.0020.002
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0050.002

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 head0.194
GPT teacher head0.573
Teacher spread0.379 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations58
Published2007
Admission routes1
Has abstractyes

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