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WORKING WITH INTEGRITY AS A COPENHAGEN BUSINESS SCHOOL STUDENT: Data Fabrication

Data Fabrication

Fabrication and falsification are closely related and may at times be difficult to distinguish in their concrete manifestations. Popularly speaking, falsification depends on the pre-existence of data, which means that data has in fact been collected and, most likely, analyzed but just failed to meet the expectations of the researcher. Fabrication, on the other hand, in its purest form, is the creation from nothing of data whose main quality lies in the fact that it fulfills the hopes and aspirations of the researcher from the outset. In short, data made to fit.

Reasons for fabrication may vary: from practical considerations such as lack of time or non-availability of relevant respondents to personal traits such as scientific ineptness and bloated ambition. 

Data may be fabricated in their entirety or in parts and fabrication can take many different shapes and forms, from respondents that do not exist and interviews that were never conducted to corruption of samples to tests that were never actually run.

Consequences of fabrication

The implications of fabrication are obvious as the results are inherently untrustworthy and may even run counter to what in an objective sense is real and good. Fabrication in a human trial setting in medical research is but an extreme example of the damage that fabricated data may cause to real people. Invention of data may also cause havoc in business. Just try to imagine the consequences of a major investment decision that is based on fabricated information about the investment target. This could spell the end for the investor. 

On a personal level, as fabrication necessarily always involves a high degree of premeditation and creative engineering and for that reason alone is considered a very serious offense, detection may put a lot of obstacles in the way of successful completion of your degree, and indeed, in life beyond university, may hold you back on your career path.

Fabrication is never an acceptable escape route from disappointing research results or suboptimal efforts, It is always and without exception a serious offense.

Above anything, it is important to stay loyal to your data, honorable to your reader, and transparent about your process, also about any issues that may adversely affect your findings. If you observe these general requirements, the need and inclination to fabricate data disappear like morning dew.

Do not despair

So, if you do not have the data that you were hoping for and dreaming of, do not despair! Instead make the most of what you do have.

It may not be the key to unlock the secrets of the universe,  but it may still and very well be enough for you to excel in the way that you discuss your work, including the strengths and shortcomings of your methodological choices and actual findings, something that may be equally valuable in the final assessment of your attained academic skills.  

Section Author

Joshua Kragh Bruhn - jkb.lib@cbs.dk