Predatory journals and their practices present a conundrum for systematic reviewers and evidence synthesisers of health research: A qualitative descriptive study
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.
Bibliographic record
Abstract
Predatory journals are a blemish on scholarly publishing and academia and the studies published within them are more likely to contain data that is false. The inclusion of studies from predatory journals in evidence syntheses is potentially problematic due to this propensity for false data to be included. To date, there has been little exploration of the opinions and experiences of evidence synthesisers when dealing with predatory journals in the conduct of their evidence synthesis. In this paper, the thoughts, opinions, and attitudes of evidence synthesisers towards predatory journals and the inclusion of studies published within these journals in evidence syntheses were sought. Focus groups were held with participants who were experienced evidence synthesisers from JBI (previously the Joanna Briggs Institute) collaboration. Utilising qualitative content analysis, two generic categories were identified: predatory journals within evidence synthesis, and predatory journals within academia. Our findings suggest that evidence synthesisers believe predatory journals are hard to identify and that there is no current consensus on the management of these studies if they have been included in an evidence synthesis. There is a critical need for further research, education, guidance, and development of clear processes to assist evidence synthesisers in the management of studies from predatory journals.
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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrity Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | MetaresearchScholarly communicationResearch integrity Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.825 | 0.921 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.057 | 0.108 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it