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Record W2157505964 · doi:10.12927/cjnl.2004.16266

ACEN Position Statement: Nursing Workload-A Priority for Healthcare

2004· article· en· W2157505964 on OpenAlexaffvenueabout
Mary Ferguson-Paré

Bibliographic record

VenueNursing leadership · 2004
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsWorkloadPosition statementNursingPosition (finance)Health careStatement (logic)Nurse AdministratorPsychologyMEDLINEMedicineBusinessPolitical scienceComputer scienceFamily medicine

Abstract

fetched live from OpenAlex

The Academy of Canadian Executive Nurses (ACEN), the organization of chief nurse executives of teaching hospitals across Canada, has agreed on this position statement on nursing workload.In a previous issue of the Canadian Journal of Nursing Leadership, Affonso et al. (2003) identified workload as a significant issue for nurses in delivering processes of care in a way that supports patient safety.We cannot underestimate the importance of appropriate work design and nursing workload to ensure patient safety and the retention of an adequate number of nurses.We hope that you will find this position statement a useful tool in planning for the future.

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)0.015
metaresearch head score (Gemma)0.035
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.327
Threshold uncertainty score0.649

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0080.003
Scholarly communication0.0090.004
Open science0.0050.003
Research integrity0.0220.022
Insufficient payload (model declined to judge)0.0060.006

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 head0.439
GPT teacher head0.489
Teacher spread0.050 · 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
GenreCommentary

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

Citations5
Published2004
Admission routes3
Has abstractyes

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