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Record W2986512685 · doi:10.1101/19010850

Defining predatory journals and responding to the threat they pose: a modified Delphi consensus process

2019· preprint· en· W2986512685 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemedRxiv · 2019
Typepreprint
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungOttawa Hospital Anesthesia Alternate Funds AssociationInstitute of Health Services and Policy ResearchUniversity of OttawaInstitute of Musculoskeletal Health and ArthritisNatural Sciences and Engineering Research Council of CanadaOttawa Hospital Research InstituteNational Science Foundation
KeywordsPublicationOutreachPublishingDelphi methodPolitical sciencePublic relationsChecklistPsychologyComputer scienceLaw

Abstract

fetched live from OpenAlex

ABSTRACT Background Posing as legitimate open access outlets, predatory journals and publishers threaten the integrity of academic publishing by not following publication best practices. Currently, there is no agreed upon definition of predatory journals, making it difficult for funders and academic institutions to generate practical guidance or policy to ensure their members do not publish in these channels. Methods We conducted a modified three-round Delphi survey of an international group of academics, funders, policy makers, journal editors, publishers and others, to generate a consensus definition of predatory journals and suggested ways the research community should respond to the problem. Results A total of 45 participants completed the survey on predatory journals and publishers. We reached consensus on 18 items out of a total of 33, to be included in a consensus definition of predatory journals and publishers. We came to consensus on educational outreach and policy initiatives on which to focus, including the development of a single checklist to detect predatory journals and publishers, and public funding to support research in this general area. We identified technological solutions to address the problem: a ‘one-stop-shop’ website to consolidate information on the topic and a ‘predatory journal research observatory’ to identify ongoing research and analysis about predatory journals/publishers. Conclusions In bringing together an international group of diverse stakeholders, we were able to use a modified Delphi process to inform the development of a definition of predatory journals and publishers. This definition will help institutions, funders and other stakeholders generate practical guidance on avoiding predatory journals and publishers.

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
gemmaMetaresearchScholarly communication
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
gptMetaresearchResearch integrityScholarly communication
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
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)0.012
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.002
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 head0.149
GPT teacher head0.462
Teacher spread0.313 · 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