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Record W4368360813 · doi:10.1177/08445621231172621

Research on Predatory Publishing in Health Care: A Scoping Review

2023· review· en· W4368360813 on OpenAlexvenueno aff
Marilyn H. Oermann, Julee Waldrop, Leslie H. Nicoll, Gabriel M. Peterson, Kerry Simmons Drabish, Heather Carter‐Templeton, Jacqueline K. Owens, Teresa Moorman, Bridget S. Webb, Jordan Wrigley

Bibliographic record

VenueCanadian Journal of Nursing Research · 2023
Typereview
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingCINAHLMEDLINEHealth careGrey literatureScopusEmpirical researchMultidisciplinary approachScientific literatureMedicinePsychologyNursingPolitical scienceSocial scienceSociologyPsychological interventionBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Predatory publishers and their associated journals have been identified as a threat to the integrity of the scientific literature. Research on the phenomenon of predatory publishing in health care remains unquantified. PURPOSE: To identify the characteristics of empirical studies on predatory publishing in the health care literature. METHODS: A scoping review was done using PubMed/MEDLINE, CINAHL, and Scopus databases. A total of 4967 articles were initially screened; 77 articles reporting empirical findings were ultimately reviewed. RESULTS: The 77 articles were predominantly bibliometric analyses/document analyses (n = 56). The majority were in medicine (n = 31, 40%) or were multidisciplinary (n = 26, 34%); 11 studies were in nursing. Most studies reported that articles published in predatory journals were of lower quality than those published in more reputable journals. In nursing, the research confirmed that articles in predatory journals were being cited in legitimate nursing journals, thereby spreading information that may not be credible through the literature. CONCLUSION: The purposes of the evaluated studies were similar: to understand the characteristics and extent of the problem of predatory publishing. Although literature about predatory publishing is abundant, empirical studies in health care are limited. The findings suggest that individual vigilance alone will not be enough to address this problem in the scholarly literature. Institutional policy and technical protections are also necessary to mitigate erosion of the scientific literature in health 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

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
gemmaMetaresearchResearch integrityScholarly communication
Domain: Evaluation · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
gptScholarly communicationResearch integrity
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
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)0.403
metaresearch head score (Gemma)0.321
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4030.321
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.3840.415
Science and technology studies0.0010.001
Scholarly communication0.0140.002
Open science0.0120.000
Research integrity0.0010.013
Insufficient payload (model declined to judge)0.0000.001

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 head0.958
GPT teacher head0.777
Teacher spread0.181 · 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

Labeled directly by 2 models reading the full record.

MetaresearchResearch integrityScholarly communication

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
DomainEvaluation
GenreReview

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

Citations12
Published2023
Admission routes1
Has abstractyes

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