Research on Predatory Publishing in Health Care: A Scoping Review
Bibliographic record
Abstract
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.
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrityScholarly communication Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | Scholarly communicationResearch integrity Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.280 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.075 | 0.083 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".