Corruption and fraud in science

  • Trevors J
  • Saier M
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Science is conducted by people, not all of whom are honest and credible, and some of whom unfortunately do not place the interests of humanity and our common biosphere ahead of their own selfish agendas. Honest mistakes are sometimes made because of our human foibles, but in this editorial we address the problem of deliberate corruption. The importance of this issue is emphasized by the fact that intentional errors and over-generalizations arriving at misleading conclusions for the purpose of justifying unwarranted actions can be extremely destructive and cause the less perceptive reader to be confused, when confusion may not be warranted. Corruption in science can manifest itself in many forms. For example, it may take the form of plagiarism, falsified academic credentials, or the use of deliberately misleading statistical approaches. Even more serious are acts involving deliberate manipulation of data, fabrication of data sets or theft followed by publication of the stolen data. Also worthy of concern are more subtle acts such as peer reviews that are not objective, providing a competitor with a time advantage for publication. For this last reason, honest, credible reviewers must be used in the review process. This means that chief editors and senior editors must be knowledgeable about the scientific credentials and ethical values of potential reviewers. Editors, editorial boards and manuscript reviewers have an arduous task when reviewing submitted articles. It is a significant challenge to determine if any of the above-mentioned activities have occurred with regards to the article. For example, parts of plagiarized articles from journals and books are difficult to recognize as reviewers cannot possibly have read all relevant research articles. The infraction goes unnoticed until the article is in circulation, and even then it may escape being identified as corrupt. While plagiarism is certainly not as serious a crime as deliberately misleading an audience, it is relatively straightforward to acknowledge the source of information, and therefore plagiarism should and can easily be avoided by conscientious authors. Fabricated and stolen data sets that are slightly altered are difficult to identify. Raw data sets are not submitted to journals. Inaccurate data can be made to appear statistically significant by selectively altering or removing data. Evidence has been presented, for example, that Gregor Mendell must have selected his data to get results reflecting the statistically improbable high degree of accuracy reported. Fortunately in this instance, the conclusions were correct, but this is by no means always the case. Once again it is the

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  • J. T. Trevors

  • M. H. Saier

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