Co-authors are colleagues with whom we implicitly contract to publish articles. Few activities are as important as publishing to launch a young researcher’s career. For good or ill the old saw, “publish or perish,” remains as true today as it ever was. To keep yourself moving forward professionally your name must appear regularly in the author line of journal articles. In some disciplines (philosophy, literary criticism) single-authored publications are the norm. However, in many fields today research is collaborative, a fact that gives rise to thorny questions about who is entitled to be an author. When has a junior member of a team done enough work to qualify? May the lead author exclude someone who has made significant intellectual contributions but not done any of the writing? Do authors differ from contributors? Whose names should be placed in the acknowledgments? In what order should names appear in the byline? How often may I publish my own work; may I publish the same paper simultaneously in a conference proceedings and in a refereed journal? And, who should make such decisions? The background essay answers these questions and provides a foundation for the issues raised in the case study.

Background essay: “Responsible authorship,” by James R. Wilson, Lonnie Balaban and Gary Comstock

As researchers, we must communicate our results with others. We are expected to write up our findings and share them, both in informal lab meetings and departmental seminars, and in more formal settings, such as conference proceedings and refereed journals.

Max Weber noted years ago that the research world is nothing but a world of confusion and ambiguity. In such cloudy conditions, as we saw in the first chapter, honesty and whistle-blowing seem to be the best policy, especially for those looking out for themselves first and foremost. Now, it is also true, as we have seen, that most of us tolerate some amount of cheating and lying. Let’s extend this analysis to the use of others’ words in our speaking and writing.

Many of us do not object to so-called “white” lies (although even in this area there is much misunderstanding, a subject to which we shall return). But which lies are objectionable, and how much lying is too much? Wherever we draw the line in answer to that question, if we tolerate cheating beyond that line we reduce everyone’s capacity to participate eagerly in the free flow of information. Since we cannot check every research result we use in our own research (indeed, we cannot check the vast majority of the results we use) we must trust in the truthfulness of others. But my willingness to trust others is diminished if I think others are plagiarizing. For I know how difficult it is to write up my research results and I know how upset I would be if I discovered someone else had gotten credit for an article that I had written. It is to an egoist’s advantage when others properly acknowledge the egoist’s written work. But does the egoist himself have any good reasons not to take unfair advantage of others’ work?

Promote our interests

I once heard a postdoctoral fellow refer to researchers as pack animals. It’s true, even the most hardened and self-absorbed of egoists at the university must cooperate with others. Every graduate student has his or her committee; every faculty member has his or her task force; and every department chair consults with others, publicly in seminars and privately in the hall. But why, we might ask, would an egoist care about the pack? Why wouldn’t egoists simply find out what their professional codes say about some issue, decide whether it serves their own interests – obey it if it does, ignore it if it doesn’t – and move on?

Now, on occasion, a code might contain confusing advice or have two rules that contradict each other. Most codes, for example, tell professionals that their education and training entitle them to autonomy. That is, they have the right to use discretion about professional matters – as, for example, when a professor decides to deal with a disruptive student in class by having a private conversation with that student. However, the same code may also require that the professor report all disruptions to the dean. How can the professor both report and not report a class disruption? It’s a puzzle. Is the professor entitled to legislate for herself in this matter, or must she defer to an authority? To protect themselves, egoists must be prepared to say why they’ve not conformed to professional codes – if that’s what they’ve done – and know how to handle potential conflicts while working within the requirements of their professional codes. They must know how to give reasons for the rules in the code.

Researchers are professionals, people who have earned positions in groups with social obligations and special privileges. Those who professed constituted the first profession – the clergy – and the clergy was followed eventually by two other professions: medicine and the law. Modernity knows of many professions, all of which share three characteristics: members have special knowledge resulting from advanced education; a solemn charge to advance the good of society; and the privilege of policing themselves.

If professionals do not conduct themselves in ways that inspire public trust, society may respond by imposing regulations. To fulfill its mission and retain its freedoms, a professional society develops a code of conduct. Many of the rules address situations commonly faced by members; these rules are developed by drawing on the collective wisdom of the group. Other rules address questions not commonly faced by members; sometimes these situations require special task forces to study the issue and issue a recommendation.

Ethical questions that commonly arise should generally be answered in the same way by all members. Should a doctor or lawyer give a newspaper reporter personal information about their patient or client? No. Should an elementary teacher discuss a student’s mental health problems on a blog? No. Should researchers mislabel photos or plagiarize manuscripts? No. Such issues are settled. However, if a given professional does not know how to behave in such familiar circumstances, they will probably be able to find the appropriate response articulated in the code. For while the ethical issues professionals face are not ethical issues the rest of society faces, they are issues that other members of their group have faced. And these familiar problems have given rise to common rules that members should internalize.

Egoism has much to recommend it. For one thing, it seems consistent with what biology suggests about the way the moral system might have evolved. Imagine our ancestors on the African plain competing for the attention of mates. Individuals who were indifferent about, unaware of, or insufficiently attentive to their own interests would be at a decided disadvantage. If individuals didn’t look out for themselves, then who would look out for them? Those Homo sapiens skilled at getting what they wanted almost certainly had fitness advantages over individuals who were clueless, especially when it came to maximizing one’s chances of finding a partner willing to have children with them. It seems, therefore, that egoists would win out over non-egoists, for they would outcompete whoever was not willing to scratch and claw to fulfill their needs.

Egoists must be conscious of observation bias

But things may not be so simple for the egoist. The reason is that many self-interested individuals have survived over time and, following this line of thought, many egoists must now exist. All of them, according to this story, must have exquisite means of reading, anticipating, and responding to others’ behaviors, too. So if I’m an egoist today and I want to try to get away with slighting others in the contemporary research world, then, I will have my work cut out for me. In this chapter, we will explore the reasons that it’s hard out there for an egoist.

Fabricating, manipulating, changing, making up, falsifying, omitting: what do these verbs have in common? All are part of the Health and Human Services definition of research misconduct and all may be used, given the right context, as synonyms for cheating. As noted in Part A, the research community disapproves of cheating but an egoist need not if a particular act of cheating is in the egoist’s own best interests. So what reasons, if any, does an egoist have not to commit falsification or fabrication of data, or plagiarism?

To answer this question we must understand the complexity of the research context in which the egoist operates, and then ask how likely it is that an egoist’s actual interests will be served by surreptitious corner cutting in research. These are the goals of the next four chapters.

What is cheating?

According to the saying, it takes two to tango. It takes more than one to cheat, too, because cheating is a social act in which one person deceives another. Although we occasionally say that someone “cheats himself,” ordinarily cheating requires one who deceives and another who is deceived (Gert 2001). To deceive is to mislead or lie, to manipulate another’s expectations falsely and so to gain unearned benefits for oneself.

Not all acts of deception are objectionable. Some we not only enjoy but praise. When the basketball player Derrick Rose feints right, crosses over his opponent and drives left around him to the basket, he has definitely misled his defender. But he hasn’t cheated. Basketball rules encourage misdirection. If D. Rose sees that no official is in position to make a call and gains an advantage by touching the ball with both hands while dribbling it, his deception is now illicit because he has harmed others. That is cheating. But when he gains an advantage by deception within the rules he harms no one. His deception is legitimate.

The image of the solitary biologist standing in a field counting butterflies and recording the numbers in a notebook still conjures up a picture of “real science” for some of us old timers. Research procedures are vastly different now. Typically, single individuals don’t produce data on their own – or record them only by hand; rather, interdisciplinary groups use computers and other electrical devices, amassing and recording their findings on software spreadsheets and in databases. Consequently the production, management, mining, and stewardship of data are processes rife with social, ethical, political, and legal implications. The moral issues associated with the interpretation of statistics are complex.

To get the ball rolling, consider just one introductory example. Journals generally seem unwilling to publish negative findings. If your study does not produce positive results, should you explore hypotheses about relationships in the data that were not part of your original design? If you switch mid-stream to a new statistical method in order to try to find some positive results, you may be mining, milking, or dredging data. In this way you may be able to suggest some interesting relationships and spur additional research, but your work may not be useful in proving any hypothesis. There are limits to the number of statistical methods and tests that may legitimately be used to explore a data set. In general, you should stick to the methods identified in your original plan for data analysis. If after the data are collected you adopt novel methods you may be guilty of making post hoc inferences. Such inferences themselves are not illegitimate but you must adopt appropriate methods to explore them. And the dangers are significant because it’s so easy to find misleading patterns. Caution is essential when looking for correlations the set was not constructed to reveal.

Let us take stock. We’ve emphasized in this book the centrality of the research community and we have taken a philosophical approach to the traditional RCR topics. We’ve also stressed the idea that researchers, even as they watch out for hidden dangers, must persist in asking new questions. We have placed some red flags around areas where pitfalls lurk. And we’ve introduced the expanding moral circle as a heuristic device to guide our decisions when we are confronted with a difficult moral decision.

As the circle makes clear, we have not exhausted our responsibilities once we have followed our profession’s rules. For research exists to benefit all of society and a researcher’s obligations reach beyond his or her circle of friends, loved ones, and other researchers. We must respect the rights of strangers even though they are beyond the reach of our explicit contracts, take seriously the interests of all animals we conscript into our studies, and consider the interests as well of future generations. For their pains and sufferings will matter just as much to them as ours do to us. When deciding how to act, we respect human rights, but we also use our professional training to make the world as attractive and rewarding as possible for as many as possible.

The moral circle is grounded in four ethical theories. The theories are briefly summarized in Table 1.

Given that each theory has some weakness or other, how should we proceed in making decisions? The expanding circle heuristic does not invite us to choose theories randomly, as if we were selecting dessert from a menu. Instead, it requires that we take all of the considerations on the chart into account and seek the well-being of all individuals potentially affected by our actions. Table 1 reminds us that ethical decision-making may be difficult and that we must use our moral imaginations and challenge ourselves to ensure that we are thinking in a truly comprehensive way. Table 2 builds on Table 1 to suggest questions we should ask as we think critically about issues in practical ethics.

Thomas Edison is often credited with creating the first research laboratory. Legend has it that when a new hire asked about the rules of the lab, Edison responded with a wisecrack. “We don’t have rules. We’re trying to accomplish something.”

This book, in part, is about the rules of research – but those of you who find such rules burdensome, don’t put the book down yet. We have some empathy with you. We understand the sentiment behind Melissa Anderson’s assertion that it’s “no secret that researchers tend to view instruction in the responsible conduct of research as an annoyance” (Anderson 2009). That said, we must immediately add that the policies and regulations governing research are critical to your – to our – success. If someone tries to conduct research in ignorance of the rules they are headed for trouble. And that said, we return to our opening theme, Edison’s quip. In this book we will not take a traditional approach to what is now called RCR “training.” Rather than emphasizing the rules, we emphasize what we’re trying to accomplish.

And what is that? In a phrase, it is a philosophical task, the asking of good questions.

The goal of this book is to welcome researchers into the community of question-askers

But let’s start with who “we” are. The book is addressed primarily to graduate students beginning their careers as researchers, people who ask and try to answer good questions. Because there are all kinds of good questions, the book features the contributions of scholars from diverse disciplines within the so-called knowledge industries. So “we” usually means the so-called author’s we – me and you. Sometimes, however, I use the editorial we and cast myself in the role of a spokesman for a larger group of people all of whom – you must take it on my authority – agree with my opinions. I’ll let the context convey which form of “we” I mean.

A mentor is a counselor

A mentor is a counselor into whose hands is entrusted the teaching of the next generation. Odysseus, preparing to leave for war, entrusted the care of his son, Telemachus, to his friend, Mentor. Each junior researcher must have a mentor, an advisor or professor or principal investigator to watch out for them, to encourage and challenge them. Junior researchers need advice both on technical aspects of their research and on the broader social aspects of making a good life as a professional. Because it involves a relationship of unequal power, mentoring is difficult enough when the junior and senior persons involved share a cultural background, gender, and ethnic identity. When the relationship involves individuals of groups traditionally under-represented in research, the activity requires special care and attention. Here we first consider the marks of a healthy mentoring relationship and then explore the challenges and opportunities inherent in the gender and racial diversity of mentors and mentees.

Who is a good mentor? He or she is someone with integrity who takes as their primary responsibility the development of the mentee’s academic and research skills. A good mentor fosters an atmosphere of openness and mutual respect, commits to helping the mentee through to the end of the mentee’s project, has significant research experience, and is an excellent teacher. Good mentors know the literature of the field, are in touch with principal authors and opinion-makers, and are respected by their colleagues. They give constructive criticism and encouragement through difficult times; they help mentees to develop conference presentations and alert them to postdoctoral opportunities and job openings. They ensure that a mentee’s advisory committee is formed expeditiously and meets at least once a year.

Suppose your research group has been collecting data for 2 years when an associate convinces the team to investigate an additional hypothesis. The hypothesis strikes everyone as intriguing, and you collectively decide to add ten new questions to a survey instrument you have people filling out online. A few months later you, a first-year graduate student, wake up in the middle of the night and realize that the group never asked the Institutional Review Board (IRB) to approve the new questions. You even have reason to believe that the Principal Investigator (PI) is aware of the situation and has decided to do nothing. What should you do? We will return to this question at the end of the chapter. First we must lay out the reasons that the informed consent of research subjects is so important.

Introduction

Researchers enroll tens of thousands of people in experiments each year. In many cases, the participants benefit profoundly from the experience. In some cases, though, some participants are harmed. How do we minimize the risks to each individual, ensure that moral rights are protected, and maximize overall well-being?

The question directs attention to one of the most important issues in research ethics because unspeakable crimes have been committed in the name of science. The Nazi doctor Josef Mengele, for example, conducted experiments on twins in which he injected dye into the eyes of brown-eyed patients to determine whether he could transform them into blue eyes (Robert Jay Lifton, The Nazi Doctors: Medical Killing And The Psychology Of Genocide. Basic Books, 1986). He forcibly distended the rectums of adolescents, without anesthesia, and excised tissue samples from their kidneys and prostates. When experiments were concluded, the subjects were killed by injections to the heart. The justification Mengele gave for his research was that he was trying to discover basic scientific knowledge about physiological processes in order to assist in the medical treatment of wounded German soldiers. But could such awful experiments ever be justified by appeals to their potential consequences? No reasonable observer would answer such a question affirmatively.

Give reasons to justify your decisions

One need not fabricate data or figures to be guilty of misconduct. “Significant departures” from “accepted practices of the scientific community” are also forbidden. When researchers violate standards “intentionally, or knowingly, or recklessly,” they are guilty of misconduct. What counts as a significant departure from accepted practice? Sometimes it is difficult to say. Consider the challenges of representing data through the use of images. Images are often easier to interpret than other formats and data may be more readily conceptualized if they are modified with image-enhancing software. Is using Photoshop to “clean up” or emphasize certain aspects of a digital image falsification? Is it a federal crime to add or change the colors of various structures in an image? Not necessarily. For if you can adequately justify your work to others, you will be on safe ground. To stay on safe ground, be sure to disclose what you have done – and read this chapter carefully.

Your being ready to provide reasons for your decisions is even more important in light of the fact that acceptable practices vary from field to field. Some rules even vary within a field, and some from lab to lab. It is not even unheard of for different students to receive different reprimands from the same professor for violating the same rule when the two students have different levels of experience. Nor do the complexities end there, for sometimes rules change at the level of the professional organization – and without any formal notice. How can a junior member of the community expect to stay upright on such shifting ground? How can we keep up with nuanced changes or be expected to know how to behave in novel moral dilemmas for which there are, as yet, no accepted rules?

If you work in a discipline such as toxicology, psychology, or neurology, you may well find yourself in the position of having to decide whether you will harm animals in research. Those who decide to perform harmful animal research are either doing it for the benefit of the actual animals used, as in veterinary work with sick or injured animals, or have been able to find for themselves an answer to the question: what gives us the right to inflict pain and suffering on innocent creatures? The justifications offered for harming animals are almost always consequentialist in form; by harming a small number of animals in as limited a way as possible, goes the argument, we can produce great benefits for humans and other animals. In this chapter we will explore this utilitarian way of thinking.

According to the US Department of Agriculture, 1,134,693 vertebrate animals were used in research in the USA in 2010 (Animal and Plant Health Inspection Service 2011). Of that number, 71,317 were nonhuman primates and roughly 85,000 were cats or dogs. More than 300,000 animals were used in experiments involving pain that was treated with drugs, and almost 100,000 were caused pain with no drugs administered.

By all accounts, these figures vastly underestimate the actual numbers of animals used because the Animal Welfare Act does not require researchers to report figures on the most commonly used species: rats, mice, birds, fish, and frogs. According to Larry Carbone, the number of rodents alone used in 2001 was 80 million (Carbone 2004). (The numbers are also a fraction of the total numbers of animals killed for food and fiber in the USA, which the US Department of Agriculture estimates at 35 million cows, 110 million hogs, and 8.8 billion chickens (United States Department of Agriculture 2011).) The commonly accepted rationale for using animals in biomedical research is to advance basic knowledge of human disease and function and so to improve human life without having to subject humans to the experiments being run on the animals.

Introduction

Graduate students may wonder who owns the data they produce and who is responsible for mistakes in articles they help to author. Intellectual property refers to a set of rights that convey exclusive ownership of intangible assets to the people who create them. The assets in question include such things as artistic designs, scientific discoveries, and research publications. Intellectual property protects the rights of creators through legal instruments such as copyrights and patents. This chapter explores these issues, addressing the possibility of one’s owning data, new knowledge, coauthored papers – even our own DNA.

Who owns your data?

Start with the question of whether students and postdocs own the data they generate. For example, suppose Sami is a postdoctoral fellow in a lab involved in a clinical trial testing a new implantable device with the potential to prevent heart arrhythmia. The lab’s Principal Investigator has been supported by the National Institutes of Health. If the lead investigator is interested in patenting the machine, she may assemble the group for a discussion of each one’s rights in the event that the device is patented. She might explain that in the Bayh-Dole Act of 1980, the US Congress clarified the fiduciary relationship between public universities, taxpayer-supported scientific granting agencies, and individual researchers.