Ethics in Science

Ethical Misconduct in Scientific Research, Second Edition

John D'Angelo

• Publisher: CRC Press
• Year: 2018
• ISBN:
  9781351974646
• Edition: 2
• Topic: Physical Sciences
• Subtopic: Physics
• Index: Physics

Providing the tools necessary for a robust debate, this fully revised and updated second edition of Ethics in Science: Ethical Misconduct in Scientific Research explains various forms of scientific misconduct. The first part describes a variety of ethical violations, why they occur, how they are handled, and what can be done to prevent them along with a discussion of the peer-review process. The second presents real-life case studies that review the known facts, allowing readers to decide for themselves whether an ethical violation has occurred and if so, what should be done. With 4 new chapters and an updated selection of case studies, this text provides resources for guided discussion of topical controversies and how to prevent scientific misconduct.

Key Features:

• Fully revised and updated text which explains the various forms of scientific misconduct.
• New chapters include hot topics such as Ethics of the Pharmaceutical Industry, The Responsibility of Science to the Environment and Summary of Ethics Guidelines of STEM Professional Societies.
• Provides the necessary tools to lead students in the discussion of topical controversies.
• Includes descriptions of real ethical case studies, a number of which are new for the Second Edition.
• This book is applicable to any science and any level of education.

Part A

Overview of Ethics Violations

1

Research Misconduct

What Is It, Why Does It Happen, and How Do We Identify When It Happens?

We should start by finding out what the dictionary has to say about the word ethics. And so, according to www.Dictionary.com, ethics (as it applies here) is defined in the following ways:

1. A system of moral principles
2. The rules of conduct recognized in respect to a particular class of human actions or a particular group, culture, etc.

Armed with a definition of ethics, we can ask: what does this mean to science? Unfortunately, the answer to this question is not always clear. Although scientific ethics is almost certainly more #2 than #1, definition #1 almost always asserts itself in individuals, including scientists and engineers. Despite how open to interpretation many ethical issues are, the scientific community has by and large agreed upon a standard of behavioral principles which, to be clear, the vast majority of practicing scientists largely adhere to. As with every walk of life, however, it is the exceptions that receive most of the attention and ruin it for those who are honest. The baffling paradox is that more often than not, they (the offenders) get caught red-handed and red-faced, ruining their careers. If this is the case, why do they do it? This question is explored later in the context of each violation of scientific conduct as the chapter develops.

Another issue that simply must not be ignored and is covered at the appropriate times in this book is what happens to the person who calls out the offending scientist? However, unfortunate the moniker may be, this person is usually referred to as a “whistleblower.” Also, the highly important distinction between the triforce of bad ethics, bad science, and genuine errors must be made. We must remember that science often both proves itself right and proves itself wrong. As we’ll come to find, this may be due to genuine mistakes, poorly designed experiments or poorly behaving people. Finally, such errors may also happen because of natural scientific progress. All are possible and are discussed in this book.

What Constitutes Scientific Misconduct?

Before embarking on a discussion of why ethical violations in science occur and before ultimately performing a case study of ethical violations in science, we must first identify just what scientific misconduct is. This is at least in part because the motivations for doing it are different for each “crime” and you simply cannot determine why people do something wrong or how to prevent it if you don’t know what they’re doing wrong. Ethical violations can be committed in many ways. Several specific violations are presented below. They are grouped by the type of violation in that some involve misuse of results or other data, while others are more related to intellectual property. Finally, there are “other” categories such as conflicts of interest, misconduct involving human or animal research, and misconduct during peer review.

• Let’s call violations where results are involved crimes against science.
  • Falsifying and fabricating data
  • Deliberate omission of known data that doesn’t agree with the hypothesis
  • Misrepresenting others’ previous work done
  • Intentional negligence in the acknowledgment of previous work done
• Let’s call violations where ownership or authorship of results are involved crimes against researchers.
  • Passing off another researcher’s data as one’s own
  • Publication of results without the consent of all the researchers
  • Failure to acknowledge all the researchers who performed the work
  • Repeated publication of too similar results or reviews
  • Breach of confidentiality
• “Other violations”
  • Conflict of interest
  • Violations where animals or humans are involved
    • – Violations of human subjects research committee or animal research committee protocols and/or federal regulations
  • Violations during the review process
    • – Peer reviewer violations
      What each of the violations is, why they happen, and how they are caught will now be discussed. When appropriate, the damages each cause will likewise be discussed.

Crimes Against Science

Falsifying and Fabricating of Data You’ve Collected

What Is It?

The more colloquial way to describe fabrication of data is lying. It is one instance of scientific misconduct that is also, without question, a violation of the moral ethics of decent people. In this ethical violation, researchers quite literally make up data, claiming experiments were carried out when they were not or significantly altering the results they do obtain so that they fit the pre-experimental hypothesis or previous studies. This ethical violation is among the most difficult to catch. This is because data fabrication can only be caught if another scientist attempts to repeat or otherwise use the research that was fabricated. This ethical violation is also perhaps the most damaging of them all—not just because it is also, undeniably, morally wrong, but because it also has the unfortunate consequence of leading other researchers down an incorrect and potentially impossible path trying to repeat and/or use the fabricated results. This then has many negative effects on other researchers’ careers resulting in wasted time and research funds. In these days of intense pressure to publish and obtain grants in times of tight financial stress, losing time and/or money could result in grants being terminated or denied funding and/or in the destruction of a new faculty member’s chances of being awarded tenure or promotion. Consequently, fabrication of data violations is often met with severe repercussions such as termination from a position or bans from applying for federal grants. Even with such serious threats hanging overhead, many people still succumb to the temptation for reasons that will be touched upon below.

Consider This Hypothetical Scenario

FALSIFYING DATA

A researcher is searching for new planets using an infrared telescope, measuring how the heat signature of the stars decreases as the planets pass between our relative position and the stars’. It is a total failure, but they create a table of results that describes the effect being observed and write it up describing the identification of planets previously discovered, claiming it is proof the method works.

FABRICATING DATA

A researcher believes that planets can be discovered using an infrared telescope. The researcher claims that as the planets pass between Earth and the star, they absorb enough heat to be measured. The researcher calculates how much heat would be absorbed with Mercury and Venus as they pass between Earth and the Sun and then claim that using the infrared telescope, and is able to detect when the planets traverse the Sun between 25% and 75% with the maximum calculated absorption at 50%; meanwhile, no experiments were carried out.

Also falling into this category is alteration of results (especially spectroscopic results such as NMR) to make the data appear more like that which was expected or desired, or to make the product of a chemical reaction appear purer. Although some may argue that “It’s no big deal, I only photo-shopped out the solvent,” it is still scientific misconduct. It is most unfortunate that this is virtually impossible to catch. Many would argue that this is not as bad as quoting a crude yield of 96% while neglecting to report that the pure yield is 34%, and perhaps that’s true though I cannot agree. These are, without question, bona fide fabrications of data. With the advent of more and more advanced computer programs, this type of data fabrication is becoming easier with each passing year. In fact, somewhat recently, the Journal of Biological Chemistry announced its adoption of the Journal of Cell Biology’s policy because this has become a more prevalent issue that reviewers and readers must be more cognizant of than ever before.¹ The policy reads: “No specific feature within an image may be enhanced, obscured, moved, removed, or introduced. The grouping of images from different parts of the same gel, or from different gels, fields, or exposures must be made explicit by the arrangement of the figure (e.g. using dividing lines) and in the text of the figure legend. Adjustments of brightness, contrast, or color balance are acceptable if they are applied to the whole image and as long as they do not obscure or eliminate any information present in the original, non-linear adjustments (e.g. changes to gamma settings) must be disclosed in the figure legend.” The Journal goes on to list the procedure that they feel will ensure the prevention/detection of such misconduct. Their comments conclude with the following: “After due process involving the JBC editors, editorial staff and ASBMB Publications Committee, papers found to contain inappropriately manipulated images will be rejected or withdrawn and the matter referred to institutional officers.”

Fabrication of data is significantly different from the data that is accused of being erroneous but not fabricated. I would argue that the latter of these cases are not an example of bad science or bad ethics but an example of scientific progress. Take as a brief example now the ancient belief that Earth was at the center of the universe. Based upon the evidence that was collected, this was indeed a logical conclusion for ancient humans to make. Modern evidence refutes this however, and we now know this to be incorrect. This, for certain, doesn’t make ancient man’s approach toward this conclusion unethical. It is also not bad science. They took the data they had and made what they believed to be the most logical conclusion. As science has progressed, we’ve become capable of not only proving that Earth is not at the center of the universe but also not even at the center of the galaxy or even our stellar neighborhood, the solar system. This is clearly a case of scientific progress and our ability to both collect and interpret data. Examples like this abound especially in medicine and are neither bad science nor scientific misconduct.

Why Does It Happen?

Why do people fabricate their data? Well, this one should be easy, even for someone who has nothing to do with any scientific field to answer. Many reasons, in fact, should come to mind instantaneously. For one, it is exceedingly difficult to catch, making it (potentially) very easy to get away with. Second, you’ll very rarely, if ever, get a grant or publish a manuscript based on poor results, and without these (grants and publications), you’re not going to keep your job very long and you will certainly have a difficult time earning tenure, a promotion, or a raise. Excuses for a pharmaceutical company to fabricate data are even clearer—many millions or even billions of dollars hang in the balance. The incentive to display good results is clear; your career and livelihood depend on it. The greed to be (or appear to be, more accurately) the best is a very tempting thing to some people.

How Is It Caught?

This is one of the worst forms of ethical misconduct and one of the hardest to catch. It is simply impossible to catch this via the peer-review process (which will be discussed in detail later), as that would require a reviewer to check every claim.² With the enormous volume of work and increasing specialization of research, such a widespread effort is nothing short of unreasonable. Wholesale fabrication of data is impossible to catch before publication. Usually, instead, this violation is learned the hard way by an innocent researcher trying to use or further develop the fabricated results.

One way to potentially catch the digital alteration of results may be to take advantage of the improving computer technology that the perpetrators exploit and have raw data files (that have the appropriate time and date stamps) sent to reviewers. The reviewer could then use the appropriate software to recreate the figures and perform a check. This, however, would put enormous strain on the peer-review process, and, frankly, the point of peer review is to evaluate the science, not to detect fraud. This science is taken as being true, and this trust is essential to science. Furthermore, manuscripts that have a large volume of results have a correspondingly large volume of supporting data. Thus, it would be unreasonably lengthening the peer-review process. Such data could be made available in the supplemental information, however, so that all readers could perform this check it they desire.

Deliberate Omission of Known Data that Doesn’t Agree with Your Hypotheses

What Is It?

Consider This Hypothetical Scenario

A researcher is studying the behavior and training/conditioning of dogs, monitoring their reaction to a particular stimulus. Of the 13 dogs in the study, 9 have the predicted reaction, while 4 do not. The researcher only reports the 9 showing the predicted reaction and makes no mention of the other 4.

This is very similar, but not identical, to the fabrication of data, especially since it may be better thought of as selective inclusion of data. It can be argued that this constitutes a falsification of data and this would not be incorrect. However, the action is different enough to warrant its own mention and category in my opinion. If any particular result(s) is/are left out of a publication, just because they do not agree with pre-experimental hypotheses, an ethical violation has certainly been committed. We are obliged as scientists to report all the data (without revision) that we obtain. (For sure, rounding to the appropriate number of significant figures is acceptable as performing appropriate statistical analyses.) Unfortunately, all too often there is a tendency toward leaving outlying data out and providing re...