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Record W4289778517 · doi:10.3138/jsp-2021-0021

Achieving a Professorship with Proper Academic Merit: Discouraging Questionable Publishing

2022· article· en· W4289778517 on OpenAlexvenueno aff
Tove Faber Frandsen, Richard Bruce Lamptey, Edward Mensah Borteye, Victor Teye

Bibliographic record

VenueJournal of Scholarly Publishing · 2022
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingPublicationPromotion (chess)IncentivePublic relationsTracking (education)Process (computing)Position (finance)Political scienceBusinessSociologyComputer scienceEconomicsLaw

Abstract

fetched live from OpenAlex

There are frequent discussions in many research communities about publishing in predatory and questionable outlets. It is necessary to address the researchers who publish in these publications, since this problem could be resolved if researchers stopped engaging with them. One of the factors contributing to an author’s decision to engage with these journals is the advantage of having more publications and editorial board involvement when they apply for a faculty position or a promotion. Fast-tracking promotions using questionable publications is an increasing problem, as scholars see the strategy working well for their colleagues. Universities are increasingly being called upon to take action. Promotion guidelines are vital for setting expectations, and more specifically pressures and incentives, when addressing the issue of questionable journals. In the case study presented in this article, new promotion guidelines have been developed at Kwame Nkrumah University of Science and Technology in Ghana to discourage faculty members from publishing in questionable journals. A verification process for all publications listed in promotion applications has been implemented. Since the implementation of this scheme in October 2019, 221 researchers have applied for promotion. Our analysis shows that one fifth of submitted publications do not meet the new criteria. Furthermore, we find no correlation between the proportion of verified publications and an applicant’s college or total number of listed publications. The implications of these findings are discussed.

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

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)0.177
metaresearch head score (Gemma)0.245
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesMetaresearch, Bibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1770.245
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0550.125
Science and technology studies0.0020.000
Scholarly communication0.2510.288
Open science0.0100.003
Research integrity0.0000.012
Insufficient payload (model declined to judge)0.0010.000

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 head0.534
GPT teacher head0.516
Teacher spread0.018 · 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

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
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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