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Record W2092579923 · doi:10.5489/cuaj.12126

Ethics in publishing

2012· article· en· W2092579923 on OpenAlexvenueno aff
John M. Fitzpatrick

Bibliographic record

VenueCanadian Urological Association Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingSociologyLibrary sciencePolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

It was very interesting to read this paper on duplicate publications. It is just one of many transgressions which can potentially ruin someone’s academic career. In this study, original articles published in the Journal of Urology in 2006 were reviewed and the incidence of redundancy was found to be gratifyingly low.1 In the rather pressurized world of academic urology it may be tempting to an individual to improve their curriculum vitae without adhering to the rigours of academic probity by, in effect, cheating in some way. It may seem like an easy option but if it is detected, the consequences for the individual will be very serious. As an editor of an academic journal, I have, like all editors, to keep an eye out for duplication of publications, plagiarism, self-plagiarism and, the worst of all, scientific fraud. Regrettably, I have seen evidence of all of these during my time as editor. Plagiarism is relatively uncommon, but does occur. On one occasion, I was sent a manuscript about a rather abstruse topic and on the advice of one of my Assistant Editors I sent it to two reviewers, neither of whom I know. One of them wrote back to say that he had several comments to make about the paper, not the least of which was that the author had “borrowed” rather a lot from a paper that he had written previously. In fact, when we applied the technology to verify this, it was clear that 75% of the manuscript overlapped the reviewer’s previous paper. This episode of plagiarism had been discovered quite by chance and resulted in the author being reported to the Dean of his medical school and his being banned from publishing in the four main urological journals for an extended period of time. Self-plagiarism is a very easy mistake to make, particularly by the younger and less-experienced. It is easy to think that one can cut and paste several paragraphs from previous papers that the author has written, and that this will not be noticed. It will. There are very effective software technologies which are now routinely applied to every manuscript that is submitted that if is relatively easy to discover when self-plagiarism has taken place. Sadly, the person who makes this mistake may once again be subjected to the rigours of the publishing laws. It’s very important that everybody, and particularly young and inexperienced researchers who may not be fully aware that this is not permitted, realize the consequences of such a mistake. Scientific fraud is awful, with frightful consequences not only for the perpetrator, but also for everyone else in the department, particularly the head of that department. It is in many ways like athletes taking drugs to enhance performance and having an unfair advantage over their competitors. It is relatively uncommon and, I feel confident when I say this, is likely to be discovered. The article which has appeared in this issue of the CUAJ refers exclusively to “duplicate publications,” but I have taken the liberty to widen the discussion to other time-consuming problems. One of the more perplexing aspects of duplicate publications is “salami-slicing,” which the authors define in this manuscript as “portions of an index article repeated or continued.”1 It is particularly difficult to decide the validity of publications which describe case-series (level of evidence 4, by the way) of the first 500, then the first 1000, and so on. These series are repetitive of data and probably should not be sent out for review. The legality of “salami-slicing” is questionable and needs to be discussed further, as it may well be on the increase. I apologize to CUAJ readers for ranting on about this. Receiving excellent submissions is one of the joys of editorship and this has given me great pleasure over the past 10 years as Editor-in-Chief of the BJU International. Unfortunately, on occasion, the trust implicit in this relationship is sometimes broken. As an editor, I have to make sure that the product is of the highest quality; the journal must be educational, entertaining and free of any potential irregularities as described by Hennessey and colleagues.1 Increasingly, new technology is being developed which will prevent ethical breaches from taking place. We all must ensure that the highest academic standards are maintained and that the highest ethical standards are rigorously applied to what we publish.

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 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)0.047
metaresearch head score (Gemma)0.157
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.157
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0090.030
Scholarly communication0.0310.018
Open science0.0020.011
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0320.018

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 head0.187
GPT teacher head0.405
Teacher spread0.218 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainEvaluation
GenreCommentary

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

Citations2
Published2012
Admission routes1
Has abstractyes

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