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Record W4415479184 · doi:10.12968/ijap.2025.0008

International collaboration in advanced practice education — a catalyst for workforce sustainability and health system resilience

2025· article· en· W4415479184 on OpenAlexaff
Melanie Clarkson, Jennie M. Scarvell, Susan Nancarrow

Bibliographic record

VenueInternational Journal for Advancing Practice · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsOceanWorks International (Canada)
Fundersnot available
KeywordsWorkforceSustainabilityWorkforce developmentResilience (materials science)Health careCommunity of practiceHealthcare systemPsychological resilience

Abstract

fetched live from OpenAlex

Australia faces significant challenges in providing accessible, high-quality healthcare, particularly owing to workforce retention issues and the growing complexity of patient needs. This article provides a commentary on the collaboration between universities to develop a contemporary postgraduate programme for advanced practitioners in Australia. To support the development of advanced practitioner roles, the University of Canberra in Australia collaborated with Sheffield Hallam University in England to develop a sustainable programme tailored to Australia's diverse healthcare needs. This international collaboration involved an open exchange of knowledge and expertise. Unlike traditional, discipline-specific programmes, the new programme is inclusive of diverse healthcare professions and contexts, empowering them to provide advanced, evidence-based care.

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)0.053
metaresearch head score (Gemma)0.044
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.053
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.044
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.039
Scholarly communication0.0130.019
Open science0.0030.032
Research integrity0.0150.030
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.537
Teacher spread0.514 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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