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Record W4289778533 · doi:10.3138/jsp-2021-0023

Predatory Journals in Journalism and Mass Communication: A Case Study of Deceptions

2022· article· en· W4289778533 on OpenAlexvenueno aff
Eric Freedman, Bahtiyar Kurambayev

Bibliographic record

VenueJournal of Scholarly Publishing · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipJournalismPublishingPublish or perishPublicationPublic relationsGovernment (linguistics)Face (sociological concept)SociologyPolitical scienceMedia studiesSocial scienceLaw

Abstract

fetched live from OpenAlex

Predatory publishing is an increasingly difficult challenge to ignore because it threatens the integrity of research literature and scholarship. Still, this scholarly area is largely overlooked in journalism and media communications (J&MC) literature. This case study examines two J&MC journals from companies listed as possibly predatory by analyzing the experiences of scholars purportedly affiliated with them. Using a survey and interviews, the analysis suggests that these journals used deceptive and unethical tactics to recruit scholars as ostensible editorial board members and reviewers. Some scholars were listed without their consent or knowledge, and others asked unsuccessfully to be removed from the journals’ posted list of editorial board members and/or reviewers. However, some say they find their affiliation rewarding intellectually, for their careers, and for the discipline. The findings have practical implications for J&MC scholarship, especially for developing country academics with insufficient English-language proficiency and who face publish-or-perish pressures from their universities and government higher education ministries.

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 integrity
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptResearch integrityScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
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)0.017
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Research integrity
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0040.019
Open science0.0010.000
Research integrity0.0000.002
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 head0.091
GPT teacher head0.360
Teacher spread0.269 · 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 designQualitative · Other design
DomainEvaluation
GenreEmpirical

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

Citations7
Published2022
Admission routes1
Has abstractyes

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