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Record W2592422958 · doi:10.3138/jsp.48.3.137

The Rewards of Predatory Publications at a Small Business School

2017· article· en· W2592422958 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.

fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Scholarly Publishing · 2017
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
FundersUniversity of British ColumbiaThompson Rivers University
KeywordsPublishingPublicationIncentiveCompensation (psychology)Public relationsMarketingSociologyBusinessPolitical scienceAdvertisingPsychologyEconomicsLawSocial psychology

Abstract

fetched live from OpenAlex

This study is the first to compare the rewards of publishing in predatory journals with the rewards of publishing in traditional journals. It finds that the majority of faculty with research responsibilities at a small Canadian business school have publications in predatory journals. In terms of financial compensation, these publications produce greater rewards than many non-predatory journal publications. Publications in predatory journals are also positively correlated with receiving internal research awards. By improving the understanding of the incentives to publish in predatory journals, this research aims to contribute to a better-informed debate on policies dealing with 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.

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)0.112
metaresearch head score (Gemma)0.718
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication, Open science
Consensus categoriesMetaresearch, Bibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1120.718
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0250.045
Science and technology studies0.0030.000
Scholarly communication0.2820.099
Open science0.0160.003
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 head0.618
GPT teacher head0.534
Teacher spread0.084 · 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