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Peer‐reviewed publication output of psychiatric nurses in the Republic of Ireland

2007· article· en· W2074537361 on OpenAlexaff
Agnès Higgins, Mary Farrelly

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsTrinity College
Fundersnot available
KeywordsNursingMental healthBenchmarkingMedicineNurse educationPsychiatry

Abstract

fetched live from OpenAlex

Pre-registration psychiatric nursing education, in the Republic of Ireland, has recently moved to a 4-year degree programme, with the first cohort of psychiatric nursing graduants graduating in 2006. In addition, a number of other policy initiatives have taken place that will have a significant impact on psychiatric nursing practice, education and research activity. To provide a baseline for future benchmarking and evaluation, the year 2005 seemed an appropriate time to reflect on and record publications by psychiatric nurses in the Republic of Ireland. This article reports the findings of a study undertaken to identify psychiatric nursing publications in peer-reviewed journals, with a view to establishing trends in publication, such as the type of publication, subject area and journal type. Emerging trends are identified and discussed in light of concurrent changes in psychiatric nursing and mental health care, and suggestions are made for future development of publication capacity.

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)0.012
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.091
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0160.012
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.005

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 head0.079
GPT teacher head0.501
Teacher spread0.422 · 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.

Study designObservational
DomainEvaluation
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

Citations5
Published2007
Admission routes1
Has abstractyes

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