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Record W3152812623 · doi:10.1101/2021.04.19.21255561

Clarivate listed nursing journals in 2020: what they publish and how they measure use of social media

2021· preprint· en· W3152812623 on OpenAlexaff
Roger Watson, Ahtisham Younas, Salma Rehman, Parveen Ali

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPublicationCitationSocial mediaBibliometricsPublishingImpact factorCitation analysisLibrary scienceComputer scienceMedicineWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Objectives To investigate what the most common types of articles that nursing journals purport to publish are and what they actually publish? And to investigate the extent to which academic nursing journals listed by Clarivate track alternative metrics? Methods Journals included in the nursing Journal Citation Report journal category in 2019 described as nursing were identified and considered suitable for inclusion in the analysis. Instructions for authors were reviewed online and mention of each type of article identified. The tables of contents of each issue of each journal published during 2019 was examined and the types of articles published were extracted to a spreadsheet into permitted article types and published articles. Likewise, the use of alternative metrics by each journal was extracted to a spreadsheet. Pearson’s and Spearman’s correlation analysis was applied to investigate the relationship between articles permitted and articles published. Results In the 2020 Journal Citation Report, 123 journals were listed. The most common article type permitted was original research (n=117), followed by review papers (n=116) and discussion papers (n=63). Original research (n=7045); review papers (n=1268); discussion papers (n=1225); editorials (n=793) and commentaries (n=776) were the most commonly published categories of article. Of journals examined, 108 (96.8%) tracked mentions on social media and the Altmetric score was the most commonly use (75%). There was a strong correlation (r=0.73; p=0,002) between the numbers of article permitted and published and a strong correlation (rho=0.86; p<0.001) in terms of the rankings of the permitted and published articles. Conclusions There is a relationship between the most frequently permitted article types and those published, especially for the most frequent categories of both. Original articles, review papers and discussion papers are the backbone of academic publishing in nursing with original articles vastly outweighing review and discussion papers. Most Clarivate listed journals now use some method of tracking alternative metrics indicating how seriously publishers take their social media profiles.

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)0.020
metaresearch head score (Gemma)0.133
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.133
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0550.039
Science and technology studies0.0010.001
Scholarly communication0.0090.007
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.219
GPT teacher head0.399
Teacher spread0.180 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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