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Record W2045038511 · doi:10.12927/cjnl.2004.17016

Challenges to Developing and Providing Nursing Leadership

2004· article· en· W2045038511 on OpenAlexaffvenueabout
Sue French

Bibliographic record

VenueNursing leadership · 2004
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsMcGill University
Fundersnot available
KeywordsPaceNursingNurse AdministratorNursing researchPublic relationsPsychologyPolitical scienceMEDLINEMedicine

Abstract

fetched live from OpenAlex

Although change is not pervasive, the pace of change is becoming more rapid. Leaders must deal constantly with managing both change and continuity. Canadian nursing is experiencing a dearth of persons qualified and willing to assume leadership roles at a time unparalleled with respect to opportunities for advancing the profession. Challenges to developing and providing nursing leadership include

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)0.049
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.115
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0130.006
Scholarly communication0.0160.010
Open science0.0060.012
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.0130.008

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 head0.326
GPT teacher head0.364
Teacher spread0.038 · 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 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

Citations8
Published2004
Admission routes3
Has abstractyes

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