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Record W2572767375 · doi:10.1016/j.ijnss.2017.01.002

A review of advanced practice nursing in the United States, Canada, Australia and Hong Kong Special Administrative Region (SAR), China

2017· review· en· W2572767375 on OpenAlexaboutno aff
Judith Parker

Bibliographic record

VenueInternational Journal of Nursing Sciences · 2017
Typereview
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsChinaLegislaturePromotion (chess)Context (archaeology)AccreditationScope (computer science)Mainland ChinaReferralPolitical scienceMedicinePublic administrationNursingMedical educationGeography

Abstract

fetched live from OpenAlex

This paper provides an overview of Advanced Practice Nursing (APN) in the USA, Canada, Australia and Hong Kong. It is based upon documents presented to the China Medical Board (CMB) China Nursing Network (CNN) as background for discussions held by the CNN in Shanghai. It discusses the APN role in these countries and regions according to topics identified by the CNN. These are APN educational preparation; role legitimacy; capacity requirements; scope of practice, domains of activities and limited rights for prescription and referral; professional promotion ladder; accreditation system; and, performance evaluation system. Both Canada and Australia have adapted many aspects of the USA model of APN to fit their specific legislative requirements and local conditions. Hong Kong has taken a different path which may be of interest in the Chinese context.

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)0.002
metaresearch head score (Gemma)0.006
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: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.017
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.375
GPT teacher head0.616
Teacher spread0.241 · 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
GenreReview

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

Citations103
Published2017
Admission routes1
Has abstractyes

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