The academic world is not without its flaws. Given the mad rush to get published and the number of publications being a measure of one’s acumen, it is not surprising that many authors often resort to some of the below-mentioned misconducts. However, it must also be remembered that often younger authors unwittingly fall prey to these same misconducts simply because they are too naïve or fail to take proper precautions.
Here are some of the top misconducts in research publication and tips on how to avoid them.
Plagiarism: Plagiarism is perhaps the most common and well-understood issue with the publication. It is also technically one of the most complicated to ascertain. Plagiarism refers to the inappropriate usage of other’s ideas or any intellectual property without explicit consent or attribution. Thus, if you pass off someone else’s words or works as your’s own, it is plagiarism.
However, what many young scholars miss out on is that even referring to some other study or project without proper attribution is also plagiarism, even if one does not try to pass it as one’s own idea. While citing an article, unless you quote the entire section under parentheses, you may be guilty of plagiarism. Technically, today in the publishing world it is accepted as a norm that if five consecutive words are the same as source material, it is considered plagiarism. Therefore, it is advised to be extremely careful even in the literature review section to avoid allegations of plagiarism.
Falsification: Data manipulation is one of the biggest problems of any research publication. More often than not, researchers resort to such measures to get more amicable results, to ensure their hypothesis is proven right, or simply to present a more robust and powerful finding than their peers. Technically, there can be 2 types of misconducts; fabrication of data in the form of generating fictitious data, or falsification in the form of selective choosing of data to suit one’s research objective. In either case, it is regarded as manipulation of falsification of data and is considered as grave misconduct.
Data duplication: This is misconduct often done unintentionally though there are instances when unscrupulous researchers do it on purpose. Technically, data duplication refers to creating exact copies same data, usually for back-up. However, in many research methodologies, especially those involving sampling or surveying, mishandling of data can lead to unintentional data duplication within the data set. Often this is done to artificially increase the total sample size, or to cover for failed experimentation. Data duplication leads to amplification of the results and in academic research it is considered a grave methodological error if done unintentionally and a form of data manipulation if done intentionally.
Unethical practices: unethical practices may include exposing individuals of groups to risks (say in medical experiments) without their knowledge, breach of individual privacy, non-anonymization of survey data, improper usage or disposal of hazardous materials, etc. Any research that violates any such norm, even unintentionally, is also considered as misconduct.
