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News Brief: Second State of the World's Nursing report expected in 2025.

2023· article· en· W4386116976 on OpenAlexaboutno aff

Bibliographic record

VenueAJN American Journal of Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsNursingPsychologyState (computer science)MedicineComputer science

Abstract

fetched live from OpenAlex

Second State of the World's Nursing report expected in 2025. A second State of the World's Nursing report will be produced by the World Health Organization (WHO) in 2025. WHO director-general Tedros Adhanom Ghebreyesus made the announcement via video address to the more than 6,000 nurses attending the International Council of Nurses (ICN) Congress 2023 in Montreal in early July. The WHO will work with the ICN to produce the report, which will detail the impact of the COVID-19 pandemic on the global nursing workforce. Speaking at a news briefing shortly after the announcement, ICN president Pamela Cipriano and chief executive officer Howard Catton said the organization had lobbied for a second State of the World's Nursing report because the data included in the first, which was produced in 2020, was gathered before the pandemic. Since then, the nursing workforce landscape has changed significantly, with reports of many nurses leaving the profession and significant increases in international recruitment and the replacement of RNs in some countries with nonlicensed personnel. The WHO director-general urged all nurses to work with their national nursing organizations “to support and advocate for your country's efforts to share robust data, on which this critical report depends.”

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.349
Teacher spread0.328 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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