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Record W4319602168 · doi:10.5430/jnep.v13n5p25

Caring in nursing education

2023· article· en· W4319602168 on OpenAlexvenueno aff
Maria Kozlowski-Gibson, Mary Gergis

Bibliographic record

VenueJournal of Nursing Education and Practice · 2023
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)LicenseGeneral partnershipNursingNurse educationWork (physics)Medical educationPsychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

In modern life, student nurses holding a registered nurse license can no longer dedicate themselves full time to further their education. Most of them depend on the financial resources from working in the profession to meet their basic needs and deal with other life challenges. Further, the work that they perform at bedside is very demanding physically, psychologically, and intellectually. It means, the work is very stressful. Reform in nursing education is necessary to avoid added stress and to meet specific needs of students, creating essential conditions for their academic and post-graduation professional-practice success. This includes instructors demonstrating that they care for students by creating a learning partnership with them and making their education personal, creative, and balanced. The goal of this reform is to enhance students’ motivation to pursue and achieve a higher academic degree than they currently have.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.015
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.115
GPT teacher head0.577
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 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
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

Citations1
Published2023
Admission routes1
Has abstractyes

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