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Record W3187074216 · doi:10.1111/opn.12407

Working with older people: Beginning or end of a nurse’s career?

2021· article· en· W3187074216 on OpenAlexafffund
Maya R. Kalogirou, Sherry Dahlke, Sandra Davidson, Kathleen F. Hunter, Cheryl Pollard, Vincent Salyers, Nicholas L. Swoboda, Mary Fox

Bibliographic record

VenueInternational Journal of Older People Nursing · 2021
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsYork UniversityMacEwan UniversityUniversity of CalgaryUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsOlder peopleGerontological nursingWork (physics)PerceptionNursingPsychologyQualitative researchPopulation ageingPopulationGerontologyMedicineSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The increasing numbers of older people (age 65+) make it important to understand how to attract nurses to work with this population. METHODS: A secondary analysis using qualitative descriptive methods was used to understand how student nurses' perceptions about older people may influence their desire to work with older people. RESULTS: Student nurses perceive a generational divide between them and older people, regardless of practice settings. They believe working with older people is heavy work, and not high acuity, and although good to learn skills as a student, not a population they want to work with until they are close to retirement themselves. CONCLUSIONS: It is important to enhance nursing education so that students understand the older generation, how to communicate with them and the prevalence of older people in healthcare settings, so that they are more likely to choose to work with older people.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.383
Teacher spread0.331 · 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 teacher head, not a consensus.

Study designObservational
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

Citations16
Published2021
Admission routes2
Has abstractyes

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