With plagiarism detecting software often used as a precursor to acceptance into many peer-reviewed journals today, there are often technicalities that can pose some difficulties for authors that are trying to reproduce studies, often studies they, themselves have conducted.
For example, consider one were to conduct a biodiversity survey, using a specific set of guidelines and procedures, publish, and repeat. The methodologies of their first study seemed to efficiently answer the research question, so next study uses the same methods. Although these methods may be easy to publish a second time with changes in wording, the issue with ambiguously rearranging words may prove difficult the third or fourth time around.
At what point, as a reviewer, should we consider that text-recycling of the manuscript methods are justified?
First, is this sort of plagiarism really an issue, so long as their own study is cited as the original source of the methods?
Secondly, if methods are reproduced, wouldn't it be beneficial to write them verbatim to previous studies which used them to optimize search results and meta data analyses of their effectiveness?
Russell - in short - there is no such thing as self-plagiarism. There is 'salami-saliscing' etc - but that is different.
Replication studies are fine - as long as they are rationalised and established in the context of replication as a means of establishing and preventing replication.
Dean Whitehead The issue I'm referring to isn't necessarily with replicating studies, but rather using the same text, verbatim, to explain the methods used in the replicated study manuscript.
Some guidelines and methods for studies have very specific and have specific language used to describe them. In this sense, there are usually paragraphs that match the exact text of other studies which use them. Most of the time studies by the author, especially in very 'niche' fields.
I agree there should be so such thing as "self-plagiarism". However, this is a very real issue when publishing, as the process of plagiarism detection is automated and papers are rejected simply by having similar language such as what I've described.
Plagiarism in any form should be avoided. Why should someone copy-paste from his/her own writing word by word? It is perfectly possible to change the wordings of sentences while keeping the meaning same.
Ranjan Parekh I agree to an extent... I've recently come across a few papers where identical methods by the same author have been used and published multiple times over the years. There are only so many arrangements of words you can make to explain the same concept before you run out.
Samy Azer This is another part of the issue aside from reviewers, some journals have automated software check manuscripts for plagiarism before they will accept it for review. I have seen these plagiarism softwares perform very poorly in the past with my colleague's manuscripts being rejected because it was identifying technical terms, citations, and niche methodology terms, as plagiarized.
It is an interesting and very important issue, plagiarism and self-plagiarism mean reproducing the same material that has already been published. It creates a problem when you once check the similarity index, the system keeps this text in memory and subsequently gives a higher similarity index which is interpreted as plagiarism.
The major issue is "cut and paste" and sometimes equations or relations are considered as plagiarism. If a reference is given from where the material has been taken or got inspiration then it is not plagiarism.
Aslam
Thank you for raising a very important issue. This question can be answered in two parts. In the first part we should understand what actually self-plagiarism is and how does it affect on the overall research progress? And the second part may deal with the actual question asked here?
Firstly, reproducing the same methodologies and data sets to publish new articles by the same authors with a new explanation isn't unprecedented and not even a bad practice. But their self-plagiarism creates problems for the new researchers to get their work published who follow the same methodologies to solve their research questions. Because, the repetition of the technical terminology and data doesn't leave any window open for new researchers to reproduce it. They might face high similarity index and plagiarism issues which ultimately lead to rejection of their research.
Now, how should reviewers tackle self-plagiarism? The strategies to tackle a self-plagiarism may vary based on the scope and quality of research. There should be some parameters to determine how important the repeated methodology and data are and how positively this research can be used to make further progress.? Whether there are some serious key issues identified and answered? Whether it is a plethora of words intentionally reproduced to increase research score.?
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