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Ten Simple Rules for Scientific Fraud & Misconduct

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Uploaded by RRI Tools on 27 July 2017

Nicolas Rougier, John Timmer. Ten Simple Rules for Scientific Fraud & Misconduct. 2017.

Disclaimer

We obviously do not encourage scientific fraud nor misconduct. The goal of this article is to alert the reader to problems that have arisen in part due to the Publish or Perish imperative, which has driven a number of researchers to cross the Rubicon without the full appreciation of the consequences. Choosing fraud will hurt science, end careers, and could have impacts on life outside of the lab. If you're tempted (even slightly) to beautify your results, keep in mind that the benefits are probably not worth the risks.

Introduction

So, here we are! You’ve decided to join the dark side of Science. That’s great! You’ll soon discover a brand new world of surprising results, non-replicable experiments, fabricated data, and funny statistics. But it’s not without risks: fame and shame, retractions and lost grants, and… possibly jail. But you’ve made your choice, so now you need to know how to manage these risks. Only a few years ago, fraud and misconduct was a piece of cake (See the Mechanical Turk, Perpetual motion machine, Life on Moon, Piltdown man, Water memory). But there are lots of new players in town (PubPeer, RetractionWatch, For Better Science, Neuroskeptic to name just a few) who have gotten pretty good at spotting and reporting fraudsters. Furthermore, publishers have started to arm themselves with high-tech tools, and your fellow scientists are willing to name and shame you on social media. To commit fraud or misconduct without getting caught in 2017 is a real challenge and requires serious dedication to your task. While you’ll never be smarter than an entire community of scientists, we’re generously giving you some simple rules to follow in your brand new career in fraud . Of course, neither results or (lack of) consequences are guaranteed.

Ten Rules for Scientific Fraud Misconduct

  1. Rule 1: Misrepresent, falsify, or fabricate your data
  2. Rule 2: Hack your results
  3. Rule 3: Copy/paste from others
  4. Rule 4: Write your own peer-review
  5. Rule 5: Take advantage of predatory publishers
  6. Rule 6: Don’t give access to your code and data
  7. Rule 7: Do not allow for replication outside your lab
  8. Rule 8: Never, ever, retract your results
  9. Rule 9: Don’t get caught. Deny if caught.
  10. Rule 10: Be creative (for once)
     

 

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