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What is a predatory journal? A scoping review

2018· review· en· W4249889786 on OpenAlexafffund
Kelly D. Cobey, Manoj M. Lalu, Becky Skidmore, Nadera Ahmadzai, Agnes Grudniewicz, David Moher

Bibliographic record

VenueF1000Research · 2018
Typereview
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersOttawa Hospital Anesthesia Alternate Funds AssociationOttawa Hospital Research InstituteUniversity of Ottawa
KeywordsPsycINFOGrey literatureMEDLINECINAHLWeb of scienceMedicineInformation retrievalComputer scienceBiology

Abstract

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<ns4:p> <ns4:bold>Background:</ns4:bold> There is no standardized definition of what a predatory journal is, nor have the characteristics of these journals been delineated or agreed upon. In order to study the phenomenon precisely a definition of predatory journals is needed. The objective of this scoping review is to summarize the literature on predatory journals, describe its epidemiological characteristics, and to extract empirical descriptions of potential characteristics of predatory journals. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> We searched five bibliographic databases: Ovid MEDLINE, Embase Classic + Embase, ERIC, and PsycINFO, and Web of Science on January 2 <ns4:sup>nd</ns4:sup> , 2018. A related grey literature search was conducted March 27 <ns4:sup>th</ns4:sup> , 2018. Eligible studies were those published in English after 2012 that discuss predatory journals. Titles and abstracts of records obtained were screened. We extracted epidemiological characteristics from all search records discussing predatory journals. Subsequently, we extracted statements from the empirical studies describing empirically derived characteristics of predatory journals. These characteristics were then categorized and thematically grouped. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> 920 records were obtained from the search. 344 of these records met our inclusion criteria. The majority of these records took the form of commentaries, viewpoints, letters, or editorials (78.44%), and just 38 records were empirical studies that reported empirically derived characteristics of predatory journals. We extracted 109 unique characteristics from these 38 studies, which we subsequently thematically grouped into six categories: journal operations, article, editorial and peer review, communication, article processing charges, and dissemination, indexing and archiving, and five descriptors. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> This work identified a corpus of potential characteristics of predatory journals. Limitations of the work include our restriction to English language articles, and the fact that the methodological quality of articles included in our extraction was not assessed. These results will be provided to attendees at a stakeholder meeting seeking to develop a standardized definition for what constitutes a predatory journal. </ns4:p>

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
gemmaMetaresearchScholarly communication
Domain: Evaluation · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptResearch integrityScholarly communication
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.038
metaresearch head score (Gemma)0.199
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.199
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0460.043
Science and technology studies0.0030.003
Scholarly communication0.0090.011
Open science0.0030.004
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.915
GPT teacher head0.750
Teacher spread0.166 · 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.

MetaresearchScholarly communicationResearch integrity

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

Citations154
Published2018
Admission routes2
Has abstractyes

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