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Research citation analysis of nursing academics in Canada: identifying success indicators

2010· article· en· W1941622179 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Advanced Nursing · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsScopusCitationCitation analysisNursing researchBibliometricsSummative assessmentMedicineSubject (documents)Library scienceMedical educationNursingMEDLINEPsychologyPolitical scienceComputer sciencePedagogy

Abstract

fetched live from OpenAlex

AIM: This article is a report of a citation analysis of research publications by Canadian nursing academics. BACKGROUND: Citation analysis can yield objective criteria for assessing the value of published research and is becoming increasingly popular as an academic evaluation tool in universities around the world. Citation analysis is useful for examining the research performance of academic researchers and identifying leaders among them. METHODS: The journal publication records of 737 nursing academics at 33 Canadian universities and schools of nursing were subject to citation analysis using the Scopus database. Three primary types of analysis were performed for each individual: number of citations for each journal publication, summative citation count of all published papers and the Scopus h-index. Preliminary citation analysis was conducted from June to July 2009, with the final analysis performed on 2 October 2009 following e-mail verification of publication lists. RESULTS: The top 20 nursing academics for each of five citation categories are presented: the number of career citations for all publications, number of career citations for first-authored publications, most highly cited first-authored publications, the Scopus h-index for all publications and the Scopus h-index for first-authored publications. CONCLUSION: Citation analysis metrics are useful for evaluating the research performance of academic researchers in nursing. Institutions are encouraged to protect the research time of successful and promising nursing academics, and to dedicate funds to enhance the research programmes of underperforming academic nursing groups.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchBibliometrics
Domain: Incentives · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Observationallow
gptMetaresearchBibliometricsScholarly communication
Domain: Evaluation · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.086
GPT teacher head0.384
Teacher spread0.299 · 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