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Research integrity became a major debated topic in biological sciences after 1970, due to a combination of factors: the development of advanced data analysis methods, the growing commercial relevancy of fundamental research, [7] and the increased focus of federal funding agencies in the context of big science. [8]
Falsification is manipulating research materials, equipment, or processes or changing or omitting data or results such that the research is not accurately represented in the research record. Plagiarism is the appropriation of another person's ideas, processes, results, or words without giving appropriate credit.
Intellectual honesty is an applied method of problem solving characterised by a nonpartisan and honest attitude, which can be demonstrated in a number of different ways: One's personal beliefs or politics do not interfere with the pursuit of truth;
Brian Wansink (US), former John S. Dyson Endowed Chair in the Applied Economics and Management Department at Cornell University, was found in 2018 by a University investigatory committee to have "committed academic misconduct in his research and scholarship, including misreporting of research data, problematic statistical techniques, failure to ...
Research integrity or scientific integrity is an aspect of research ethics that deals with best practice or rules of professional practice of scientists. First introduced in the 19th century by Charles Babbage, the concept of research integrity came to the fore in the late 1970s.
In scientific inquiry and academic research, data fabrication is the intentional misrepresentation of research results. As with other forms of scientific misconduct, it is the intent to deceive that marks fabrication as unethical, and thus different from scientists deceiving themselves. There are many ways data can be fabricated.
The industrialization of science increased the number of publications and research outcomes and the rise of the computers allowed effective analysis of this data. [6] While the sociology of science focused on the behavior of scientists, scientometrics focused on the analysis of publications. [1] Accordingly, scientometrics is also referred to ...
[2] [3] [4] However, researcher degrees of freedom can lead to data dredging and other questionable research practices where the different interpretations and analyses are taken for granted [5] [6] Their widespread use represents an inherent methodological limitation in scientific research, and contributes to an inflated rate of false-positive ...