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Record W2099380846 · doi:10.12927/cjnl.2012.23058

Who Will Lead Nursing into the Future?

2012· article· en· W2099380846 on OpenAlexaffvenueabout
Kathleen Miller, Greta G. Cummings

Bibliographic record

VenueNursing leadership · 2012
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsMacEwan University
Fundersnot available
KeywordsNursingFront lineSet (abstract data type)PsychologyNurse educationNursing researchWork (physics)MedicinePolitical science

Abstract

fetched live from OpenAlex

Recent research reveals a need for improved leadership capabilities among nurses, from the front-line nurse to those in management capacities. This "op-ed" piece is a discussion arising from the results of a study examining two groups of high school students: one participating in a leadership training program and one not participating. With their responses, these students demonstrated a stereotypical view of the work of nurses and were not interested in pursuing a career in nursing. They also didn't see nursing as a career in which to practise their leadership abilities. We raise questions about our ability to meet the goals of the Canadian Nursing Association as set out in Toward 2020 if we, in the nursing profession, are not successful in attracting students who understand the complexities of nursing practice and have a desire and the ability to help advance the profession in Canada. Recommendations for further research are presented.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.337
Teacher spread0.238 · 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 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

Citations3
Published2012
Admission routes3
Has abstractyes

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