Research Ethics & Integrity

It is tempting to treat research ethics as a set of forms to complete before the real work begins - a checkpoint to clear rather than a discipline to master. That attitude is exactly what this course is designed to dislodge. Ethics is not external to good research; it is a condition of it. A study that harms its participants, or that reports results the data do not support, has failed as research, not merely as paperwork.

Why research is a special case

Three features of research generate obligations that ordinary conduct does not carry.

• Power over participants. Research routinely exposes people to risk - a new drug, an invasive question, an experimental manipulation - in the pursuit of generalizable knowledge rather than the participant's own benefit. That distinguishes research from clinical care and raises the moral stakes of consent and protection.
• A privileged claim on public trust. Science speaks with authority. Physicians prescribe on the strength of trials; governments legislate on the strength of studies; the public funds the whole enterprise. That authority is a loan against integrity. When a fabricated result enters the literature, it is not one lab that suffers but every downstream decision built on it.
• Self-regulation. Much of research is checked not by outside inspectors but by the researchers themselves, through peer review, replication, and honest reporting. A profession that polices itself must internalize the standards, because no external system can catch every lapse.

Three domains of obligation

This course is organized around three families of ethical duty that together define responsible conduct of research (often abbreviated RCR).

1. Protecting participants. Duties owed to the humans and animals who make research possible: consent, risk minimization, privacy, and fair treatment. Modules 2 and 3 address these.
2. Integrity of the record. Duties owed to the truth and to fellow scientists: honest data, fair credit, disclosed conflicts, transparent methods. Modules 4 and 5 address these.
3. Responsibility to the community. Duties owed to trainees and to the health of the field itself: good mentoring, fair peer review, and a culture in which raising a concern is safe. Module 6 addresses these.

Ethics is judgment, not a checklist

A recurring theme is that principles frequently conflict. A study that would benefit many might most easily recruit a desperate few; a commitment to openness might collide with a duty of confidentiality; the drive to publish might tempt a researcher to overstate a finding. Ethical competence is not the memorization of rules but the capacity to recognize these tensions and reason through them defensibly. Regulations set a floor. The rest is professional judgment - which is precisely why it must be trained, discussed, and practiced rather than assumed.

One caution as you begin: it is comforting to imagine that unethical research is done only by villains. The historical record and the modern retraction record both say otherwise. Most misconduct is committed by intelligent, well-intentioned people under pressure, who talked themselves into it one small step at a time. The purpose of studying ethics is to install the habits and the vocabulary that let you notice the first small step - in your own work as much as in others'.

Every major protection in research ethics was written in blood. The regulations can feel abstract until you learn the cases that produced them; then each requirement reads as a direct answer to a specific harm. This lesson walks through that history so the rules will never again seem arbitrary.

Nazi experimentation and the Nuremberg Code (1947)

During the Second World War, physicians in Nazi Germany conducted lethal experiments on concentration-camp prisoners without consent - immersion in freezing water, deliberate infection, high-altitude exposure to the point of death. At the subsequent Nuremberg Medical Trial, judges articulated the Nuremberg Code, ten principles for permissible human experimentation. Its opening line is the foundation of everything that follows: "The voluntary consent of the human subject is absolutely essential." The Code also required that experiments yield fruitful results unprocurable by other means, avoid unnecessary suffering, and allow the subject to withdraw.

The Declaration of Helsinki (1964)

The Nuremberg Code was aimed at atrocity and said little about ordinary clinical research. In 1964 the World Medical Association adopted the Declaration of Helsinki, a set of ethical principles for medical research that has been revised many times since. It introduced ideas the Code lacked: the distinction between therapeutic and non-therapeutic research, the requirement for independent review of protocols, and the enduring principle that the well-being of the individual research subject must take precedence over the interests of science and society.

Tuskegee and the U.S. reckoning

The United States did not need to look abroad for abuse. The Tuskegee syphilis study, run by the U.S. Public Health Service from 1932 to 1972, followed the untreated progression of syphilis in about 600 Black men in Alabama - most of them poor sharecroppers - who were never told they had the disease and were actively prevented from getting treatment. Even after penicillin became the standard cure in the 1940s, it was withheld so investigators could continue to observe the "natural history" of the illness. When a journalist exposed the study in 1972, the public revulsion forced reform.

The National Research Act and the Belmont Report

Congress responded with the National Research Act of 1974, which created a national commission and mandated review boards for federally funded research. The commission's landmark product, the Belmont Report (1979), distilled research ethics into three principles - respect for persons, beneficence, and justice - that remain the ethical backbone of U.S. regulation and the subject of the next lesson.

Case / abuse	Document produced	Central lesson
Nazi medical experiments	Nuremberg Code (1947)	Voluntary consent is essential
Need for clinical-research norms	Declaration of Helsinki (1964)	Individual welfare over science; independent review
Tuskegee syphilis study	National Research Act (1974); Belmont Report (1979)	Consent, honesty, and justice for the vulnerable

Other cases reinforced the pattern. In the Willowbrook hepatitis studies, children with intellectual disabilities at a state institution were deliberately infected. At the Jewish Chronic Disease Hospital, live cancer cells were injected into elderly patients without their knowledge. Each scandal added weight to the same conclusion: researchers cannot be trusted to be the sole judges of what they may do to participants, and independent, principled review is not optional. Hold that history in mind. When a review board asks you to justify a risk or rewrite a consent form, it is enforcing a promise made to the people these cases harmed.

The Belmont Report reduced a tangle of rules to three principles that a researcher can actually hold in mind. Nearly every requirement you will meet in human-subjects work is an application of one of them. Learn the three, learn what each grounds in practice, and you will be able to reconstruct most of the regulation from first principles.

Respect for persons

This principle has two parts. First, individuals are autonomous agents entitled to make their own choices about whether to participate. Second, persons with diminished autonomy - children, prisoners, those with cognitive impairment - are entitled to additional protection. In practice, respect for persons grounds informed consent: the requirement that participation be voluntary, informed, and revocable. It also grounds the special safeguards for vulnerable groups covered later in this course.

Beneficence

Beneficence obliges the researcher to maximize possible benefits and minimize possible harms. It is often paired with the older maxim of non-maleficence (do no harm), but Belmont frames it positively: not merely avoiding harm but actively securing well-being. In practice this principle grounds the risk-benefit analysis at the heart of ethical review. A protocol is acceptable only when its risks are reasonable in relation to its anticipated benefits, and when risks have been minimized as far as sound design allows.

Justice

Justice concerns the fair distribution of the benefits and burdens of research. It asks: who bears the risks, and who reaps the rewards? It is unjust for one group - the poor, the institutionalized, the marginalized - to shoulder the dangers of research while the benefits flow to others. In practice, justice grounds equitable selection of participants: people should not be recruited simply because they are convenient, powerless, or easy to pressure, and populations that bear research risk should stand to benefit from the results.

Principle	Core commitment	Grounds in practice
Respect for persons	Autonomy; protection of the vulnerable	Informed consent
Beneficence	Maximize benefit, minimize harm	Risk-benefit assessment
Justice	Fair distribution of benefits and burdens	Equitable participant selection

When principles collide

The principles are not a checklist to be satisfied independently; they routinely pull against one another, and ethical review is the disciplined negotiation of the tension.

• A study promising great social benefit (beneficence) might most easily recruit a captive population such as prisoners (violating justice).
• Full disclosure (respect for persons) can ruin the science of a study whose validity depends on participants not knowing its true purpose, forcing a careful, reviewed use of deception.
• Protecting an individual from all risk (a strict reading of beneficence) can be unjust if it excludes a whole group - say, pregnant women - from research that would ultimately benefit them.

There is no formula that resolves these conflicts automatically. The Belmont framework does something more modest and more useful: it names the competing goods precisely, so that a researcher and a review board can argue about the right balance in the open, on the record, rather than letting one value silently override the others. When you write a protocol, address all three principles explicitly. A reviewer trained on Belmont will be looking for exactly that.

In the United States, the Belmont principles are enforced through a system of local committees called Institutional Review Boards (IRBs), operating under a federal regulation known as the Common Rule (codified at 45 CFR 46). Most other countries run an equivalent system under names such as Research Ethics Committee or Ethics Review Board. Wherever you work, some independent body must approve research with human participants before it begins. This lesson explains what that body does and how it calibrates its scrutiny to risk.

What an IRB is

An IRB is a standing committee charged with reviewing research protocols to protect the rights and welfare of human participants. Federal rules require a minimum composition designed to prevent groupthink and conflict of interest: at least five members of varying backgrounds, at least one scientist, at least one non-scientist, and at least one member unaffiliated with the institution (a community member). This mix ensures that a protocol is judged not only on its science but on its acceptability to the wider community whose members might enroll.

The threshold questions

Two definitions decide whether the IRB has jurisdiction at all. First, is it research - a systematic investigation designed to contribute to generalizable knowledge? A hospital collecting data purely to improve its own operations may not meet this bar. Second, does it involve human subjects - living individuals about whom the researcher obtains data through intervention or interaction, or whose identifiable private information is used? If both answers are yes, the study needs review.

Three tiers of review

Not all research carries equal risk, so review is calibrated in three ascending levels of scrutiny.

1. Exempt. Certain low-risk categories - some anonymous surveys, research in normal educational settings, secondary analysis of publicly available de-identified data - may be exempt from continuing review. The decisive rule: the investigator does not decide exemption unilaterally. The IRB or its designated official makes that determination, precisely because researchers cannot be trusted to judge their own studies harmless.
2. Expedited. Research that poses no more than minimal risk and fits defined categories may be reviewed by the chair or a single experienced member rather than the convened board. Minimal risk is a term of art: the probability and magnitude of harm are no greater than those ordinarily encountered in daily life or during routine physical or psychological examinations.
3. Full board. Research that exceeds minimal risk - a new drug, a stressful manipulation, work with a vulnerable population - must be reviewed at a convened meeting with a majority of members present and a favorable vote.

Tier	Risk level	Who reviews
Exempt	Low, in a defined category	IRB official confirms exemption
Expedited	No more than minimal risk	Chair or single member
Full board	Greater than minimal risk	Convened committee, majority vote

Ongoing obligations

Approval is not a one-time event. Investigators must report adverse events and unanticipated problems, submit amendments for any change to an approved protocol before implementing it, and undergo continuing review for higher-risk studies. The IRB can suspend or terminate research that endangers participants. The lesson to carry forward: the IRB is not an adversary to be outmaneuvered but a partner in a promise. Build time for review into your project from the start, describe risks honestly, and never begin data collection on human participants before you hold written approval.

Informed consent is the operational heart of respect for persons. It is not a signature and not a form; it is a process of communication through which a person comes to a genuine, uncoerced decision about participating. A stack of signed forms means nothing if the participants did not understand what they agreed to. This lesson breaks consent into the components that make it valid.

Three functional components

• Disclosure. The researcher must provide the information a reasonable person would need to decide: the purpose of the study, the procedures, foreseeable risks and discomforts, anticipated benefits, reasonable alternatives, how confidentiality will be protected, that participation is voluntary, and whom to contact with questions or in case of injury.
• Comprehension. Disclosure that cannot be understood is not disclosure. Information must be presented in plain language, at an appropriate reading level, in the participant's own language, and with time and opportunity to ask questions. For complex studies, comprehension may need to be checked, not assumed.
• Voluntariness. The decision must be free of coercion (an explicit or implicit threat) and of undue influence (an excessive or inappropriate reward that overwhelms judgment). Payment may compensate for time and inconvenience but must not be so large that it induces people to accept risks they would otherwise refuse. Crucially, consent is revocable: a participant may withdraw at any time, without penalty and without losing benefits to which they were otherwise entitled.

The consent document

Regulations specify required elements the written consent must contain, including the eight core disclosures above and, since the 2018 revision of the Common Rule, a concise key information summary at the beginning so that the most decision-relevant facts are not buried. The trend in consent design is away from long, defensive legal documents and toward genuinely usable communication, because an unreadable form defeats the purpose consent exists to serve.

Waivers and alterations

Consent is not absolute. An IRB may waive or alter consent only when a strict set of conditions is met: the research is no more than minimal risk, the waiver will not adversely affect participants' rights and welfare, the research could not practicably be carried out without the waiver, and, where appropriate, participants are given relevant information afterward. This is how large-scale secondary data research or certain emergency studies can proceed - not by ignoring consent, but by an explicit, justified regulatory exception.

Special cases

Situation	How consent is handled
Competent adult	Informed consent by the participant
Minor child	Parental permission plus the child's assent
Adult unable to consent	Consent by a legally authorized representative
Study requiring deception	Limited consent up front, full debriefing afterward

Two terms deserve emphasis. Assent is a minor's affirmative agreement to take part; because a child cannot give legally valid consent, an adult gives permission while the child gives assent, and a child's refusal is generally to be respected. Deception - withholding or misstating the study's purpose to prevent reactive behavior - is permissible only when the study could not be done otherwise, risks are minimal, and participants are fully debriefed afterward and offered the chance to withdraw their data. Deception is in standing tension with respect for persons, so it must be justified to the IRB, never simply assumed to be acceptable.

Even a study that never touches a participant's body can harm them - through a breach of the sensitive information they shared. A leaked record of a mental-health diagnosis, an immigration status, or an illegal behavior can cost someone a job, a relationship, or their liberty. Protecting information is therefore a core ethical duty, and it rests on three terms that students routinely blur.

Three distinct concepts

• Privacy is about people: a person's control over the extent to which they share themselves - their body, thoughts, and information - with others. Respecting privacy means, for example, not observing or contacting people in ways they would find intrusive, and not asking for more sensitive information than the research genuinely needs.
• Confidentiality is about data: the researcher's obligation to control who can access identifiable information a participant has shared, and to use it only as agreed. Confidentiality is a promise about the handling of data that has already been collected.
• Anonymity is the strongest protection: data are collected with no identifiers at all, so that not even the researcher can link a response to a person. True anonymity makes a confidentiality breach impossible, but it also rules out follow-up and longitudinal linkage.

Identifiers and de-identification

Data are identifiable when they contain, or can be readily linked to, information naming an individual. Direct identifiers are obvious: name, address, medical-record number. Indirect (quasi-) identifiers are subtler: a combination of birth date, sex, and postal code can uniquely single out a person even with names removed. This is why de-identification - stripping identifiers so a record can no longer reasonably be traced to an individual - must consider combinations, not just obvious fields. A related technique, pseudonymization, replaces identifiers with a code while a separate, secured key allows re-linkage when necessary; it is reversible and so offers weaker protection than true de-identification.

Practical safeguards

1. Collect the minimum. The best-protected datum is the one never gathered. Do not collect identifiers you do not need.
2. Separate and secure. Store the key that links codes to identities separately from the research data, under access controls and encryption.
3. Limit access. Restrict identifiable data to team members who need it, and train them in their obligations.
4. Plan the end. Specify how long identifiable data will be retained and how it will be destroyed or fully de-identified afterward.

Limits and legal tools

Confidentiality is a strong promise but not always an absolute one. Certain disclosures may be legally mandated - for example, credible threats of serious harm or, in many jurisdictions, suspected child abuse - and participants must be told of such limits during consent so the promise you make is one you can keep. To strengthen protection against compelled disclosure (such as a subpoena), researchers studying sensitive topics can sometimes obtain a legal instrument, in the United States a Certificate of Confidentiality, that shields identifiable research data from forced release. The overarching principle is honesty: promise only the protection you can actually deliver, describe its limits plainly, and then engineer your data handling to honor it.

The Belmont principle of respect for persons requires extra protection for those with diminished autonomy, and justice requires that the vulnerable not be exploited simply because they are available. Federal regulation translates these duties into specific safeguards for named groups. Understanding why each group is vulnerable clarifies why its protections take the shape they do.

What vulnerability means here

A population is vulnerable when its members have a reduced ability to protect their own interests in the research relationship. Vulnerability can arise from compromised capacity to give informed consent (young children, persons with dementia), from a situation of dependency or constraint that undermines voluntariness (prisoners, employees, students of the researcher), or from heightened susceptibility to harm (pregnant women and fetuses). The same person can be vulnerable in one respect and fully autonomous in another, so the analysis is contextual rather than a fixed label.

Groups with specific protections

• Children. Because minors cannot give legally valid consent, research requires parental permission plus the child's assent, and the regulations limit the level of risk permissible in relation to the potential benefit. Research offering no direct benefit to the child is capped at low levels of risk.
• Prisoners. Incarceration inherently compromises voluntariness: the promise of better conditions or early consideration can be powerfully coercive. Special rules restrict prison research to categories that either carry minimal risk or stand to benefit prisoners, and require an IRB member with relevant expertise (often a prisoner representative).
• Pregnant women, fetuses, and neonates. Because interventions can affect two parties, one of whom cannot consent, regulation imposes additional conditions balancing potential benefit against risk to the fetus, while cautioning against reflexive, blanket exclusion that would leave the group under-studied.
• Persons with impaired decision-making capacity. For those who cannot consent - due to cognitive disability, acute illness, or unconsciousness in emergency research - a legally authorized representative may consent, subject to tighter risk limits and, where possible, the person's own assent.

The two-edged nature of protection

There is a tension worth naming. Overprotection can itself be an injustice. If pregnant women, children, or the seriously ill are routinely excluded, then medicine is left prescribing to them on the basis of studies never done in them - guessing at doses and effects. The modern stance is therefore not exclusion but appropriate inclusion with heightened safeguards: bring vulnerable groups into research when the knowledge will serve them, but wrap that participation in the strongest protections.

Group	Source of vulnerability	Key safeguard
Children	Cannot legally consent	Permission plus assent; risk limits
Prisoners	Constrained voluntariness	Restricted categories; prisoner representative
Pregnant women / fetuses	Risk to a party who cannot consent	Benefit-risk conditions; avoid blanket exclusion
Impaired capacity	Cannot give valid consent	Authorized representative; tighter risk limits

When you design a study touching any of these groups, expect and welcome tighter review. The extra scrutiny is the system keeping the promise made after Willowbrook and Tuskegee - that those least able to protect themselves will be protected most carefully.

A great deal of biomedical and behavioral knowledge - and nearly every modern medicine - rests on research using animals. That fact sits atop a genuine moral problem: animals can suffer but cannot consent, and they are used for human ends. Serious ethics does not resolve this by pretending the problem away in either direction. It acknowledges the moral weight of animal welfare and constructs a framework to ensure that when animals are used, their use is justified, minimized, and as humane as possible.

The ethical landscape

Positions on animal research span a spectrum. A strict animal-rights view holds that sentient animals have interests that may not be sacrificed for others' benefit, which would forbid most research. A utilitarian view - influential in shaping actual policy - weighs the suffering caused against the benefits gained, permitting research when the expected benefit is large and the suffering is minimized. A welfarist consensus, embodied in law and oversight, accepts that animals may be used but insists that their capacity to suffer imposes strict duties to protect their welfare. Most modern regulation is welfarist in structure: it does not ban animal research, but it heavily constrains it.

The 3Rs

The organizing framework for humane animal research, proposed by Russell and Burch in 1959, is the 3Rs. It has become the internationally accepted standard and is worth memorizing precisely.

• Replacement. Wherever possible, replace animals with alternatives that achieve the scientific aim without them - cell and tissue cultures, computer models, or studies in organisms of lower sentience. The first ethical question is always whether an animal is needed at all.
• Reduction. Use the fewest animals necessary to obtain valid, statistically meaningful results. This is where good experimental design and power analysis become an ethical matter: an underpowered study wastes animals by being unable to answer its question, and an oversized one wastes them needlessly.
• Refinement. Modify procedures and husbandry to minimize pain, distress, and lasting harm and to improve welfare - better analgesia and anesthesia, humane endpoints that stop a study before suffering becomes severe, and enriched living conditions.

Oversight and the committee

Just as human research requires an IRB, animal research requires review by an institutional animal-care and use committee (in the United States, the IACUC). Before work begins, investigators submit a protocol that must justify the species and numbers, demonstrate that alternatives were seriously considered (the Replacement search), describe how pain will be assessed and relieved, and specify humane endpoints. The committee - which must include a veterinarian and a member of the public - can require changes or reject the protocol. Ongoing duties include veterinary care, inspection of facilities, and reporting.

R	Question it forces	Example measure
Replacement	Is an animal needed at all?	Cell culture or computer model
Reduction	What is the fewest that yields valid results?	Sound power analysis and design
Refinement	How is suffering minimized?	Analgesia and humane endpoints

The 3Rs do more than soften a hard practice; they align good ethics with good science. A well-designed study that uses the right number of animals under low-stress conditions produces cleaner, more reproducible data than a wasteful, stressful one. As with human research, the deepest point is that ethical rigor and scientific rigor are not opponents. They are the same discipline applied to different stakeholders.

The 3Rs supply the ethical logic of humane animal research; regulation and institutional oversight turn that logic into enforceable practice. Just as the IRB protects human participants, a network of law, committees, and professional standards protects research animals. This lesson describes that machinery and the protocol at its center, so that the requirements read as safeguards rather than hurdles.

Layers of governance

Animal research is typically governed by several overlapping layers. Law sets baseline requirements - in the United States the Animal Welfare Act and, for federally funded work, the Public Health Service Policy, with parallel statutes elsewhere. Institutional oversight is exercised by a standing committee: in the United States the Institutional Animal Care and Use Committee (IACUC), which must include a veterinarian with relevant expertise, at least one practicing scientist, and at least one member unaffiliated with the institution to represent community concerns. Professional norms and accreditation add a further layer, as do the veterinary staff who provide daily care.

The animal-use protocol

Before any animal work begins, investigators submit a protocol that the committee must approve. A rigorous protocol is essentially the 3Rs written out and defended. It must:

• Justify the species and numbers. Explain why animals are necessary at all (a Replacement analysis), why this species is appropriate, and how the number requested is the minimum needed for valid results (a Reduction analysis, usually supported by a power calculation).
• Document a search for alternatives. Most frameworks require a literature search demonstrating that non-animal methods and less-sentient models were seriously considered and found inadequate for the aim.
• Describe pain and its relief. Classify procedures by their potential to cause pain or distress, and specify the anesthesia, analgesia, and humane endpoints (Refinement) that will limit suffering.
• Ensure competence. Confirm that personnel are trained to perform the procedures skillfully, since unskilled technique is itself a welfare hazard.

Monitoring across the study

Approval is the beginning of oversight, not the end. Veterinary staff monitor animal health, the committee inspects facilities and programs on a recurring schedule, and investigators must report unexpected outcomes and seek approval before changing an approved protocol. When welfare problems arise that cannot be corrected, the committee has the authority to suspend the activity, mirroring the IRB's power over human research. This continuity of oversight recognizes that welfare depends on daily practice, not merely on a well-written plan.

Layer	Function
Law and policy	Baseline legal requirements for care and use
Oversight committee (IACUC)	Protocol review, inspection, authority to suspend
Veterinary staff	Daily health monitoring and clinical care
Professional standards	Accreditation and discipline-specific norms

Ethics and validity together

A theme worth restating is that this oversight serves science as much as it serves animals. Stressed, poorly cared-for animals yield noisy, less reproducible data; the same practices that reduce suffering - skilled handling, low-stress housing, careful design - also improve the quality and generalizability of results. A protocol that takes welfare seriously is not paying a tax on good research; it is doing good research. When a committee asks you to justify a number or refine a procedure, it is enforcing both an ethical duty to the animals and a scientific duty to the reliability of your findings.

The integrity of science depends on a simple premise: that what researchers report actually happened. When that premise is broken deliberately, the offense is research misconduct, the most serious violation in the profession. U.S. federal policy defines it precisely as fabrication, falsification, or plagiarism - the three are often abbreviated FFP - in proposing, performing, reviewing, or reporting research.

The three categories

• Fabrication is making up data or results and recording or reporting them. The fabricator did not run the experiment, or ran it and invented the numbers. It is the manufacture of evidence from nothing.
• Falsification is manipulating research materials, equipment, or processes, or changing or omitting data or results, such that the research record does not accurately represent the work. This includes altering images, selectively deleting inconvenient data points, or misrepresenting a method. The data existed but were distorted.
• Plagiarism is the appropriation of another person's ideas, processes, results, or words without giving appropriate credit. It is theft of intellectual property and a deception of the reader about the origin of the work. Note that plagiarism can include self-plagiarism - reusing one's own previously published text or data as if new - which deceives readers and editors even though no one else is robbed.

The boundary with honest error

Crucially, the federal definition contains a mental-state requirement: misconduct must be committed intentionally, knowingly, or recklessly, and it does not include honest error or honest differences of opinion. Science advances by making and correcting mistakes; a researcher who reports a result later found to be wrong, through no deception, has not committed misconduct. The dividing line is not whether the work turned out to be correct but whether the researcher was honest. This is why a good-faith correction or even a retraction of an honest mistake is a mark of integrity, not an admission of guilt.

The standard and the process

Because the accusation is grave, findings of misconduct follow a defined process, typically requiring that the act be a significant departure from accepted practices, that it was committed with a culpable state of mind, and that it be proven by a preponderance of the evidence. Institutions conduct an inquiry and, if warranted, a formal investigation, with protections for both the accused and the person who raised the concern (the whistleblower). Confirmed misconduct can end careers, trigger retraction of publications, and require repayment of grant funds.

Type	What is done	Core deception
Fabrication	Inventing data or results	The work was never done as reported
Falsification	Distorting data, images, or methods	Real work is misrepresented
Plagiarism	Taking others' work without credit	False claim of originality

Why it matters beyond the offender

A single fabricated paper is not a self-contained crime. Other labs waste years and resources building on a result that was never real; meta-analyses are poisoned; in clinical fields, patients can be harmed by treatments endorsed on fraudulent evidence. Because science is cumulative, misconduct contaminates everything downstream. That is why the profession treats FFP not as a private failing but as an assault on the shared enterprise, and why the obligation to report credible suspicions - carefully and through proper channels - is itself an ethical duty.

Fabrication, falsification, and plagiarism are the bright-line offenses, and they are relatively rare. Far more corrosive to science, in aggregate, is a broad gray zone of questionable research practices (QRPs): choices that are not outright fraud, that many researchers have made without feeling like cheats, but that systematically bias the literature toward false-positive findings. Precisely because they feel normal, QRPs may do more cumulative damage than the dramatic cases of FFP.

What makes a practice questionable

A QRP exploits the flexibility, or researcher degrees of freedom, in how data are collected, analyzed, and reported. In any real analysis there are dozens of defensible choices - which outliers to exclude, which covariates to include, when to stop collecting data, which of several measures to report. If a researcher tries many of these and reports only the combination that "worked," the result looks far more convincing than it is, and the reported statistics no longer mean what they claim to mean.

A catalog of common QRPs

• p-hacking. Trying analyses, exclusions, and subgroups until a p-value crosses the 0.05 threshold, then reporting only that path. Because each unreported test inflates the chance of a false positive, p-hacking manufactures significance that would not survive an honest accounting.
• HARKing (Hypothesizing After the Results are Known). Observing a pattern in the data and then presenting the hypothesis it suggested as if it had been predicted in advance. This disguises an exploratory, hypothesis-generating finding as a confirmatory test, stripping away the skepticism it deserves.
• Optional stopping. Repeatedly checking results as data accumulate and stopping the moment significance appears, which badly inflates the false-positive rate unless the analysis is designed for it.
• Selective reporting. Publishing only the measures, conditions, or studies that produced favorable results and quietly dropping the rest - the individual-lab version of publication bias.

The remedy: pre-specification and transparency

The common thread of QRPs is that undisclosed flexibility, applied after seeing the data, corrupts the logic of statistical inference. The remedy is to fix the key decisions before seeing the outcomes and to disclose them.

• Pre-registration records the hypotheses, design, and analysis plan in a time-stamped public archive before data collection, so the line between confirmatory and exploratory work cannot later be blurred.
• Registered Reports go further: a journal reviews and accepts the plan before results exist, so publication cannot depend on how the results turn out.
• Full reporting of all measures, conditions, exclusions, and analyses - not just the flattering ones - lets readers judge the evidence honestly.

Notice that none of these reforms forbids exploration. Exploratory, data-driven discovery is vital; it is simply a different kind of claim than a confirmatory test, and it must be labeled as such. The sin in a QRP is not looking at the data - it is looking, deciding, and then pretending you decided in advance. Keeping that distinction honest, in your own work and in what you demand of others, is one of the most consequential integrity habits a modern researcher can build.

Authorship is the currency of academic science: it confers credit, establishes priority, and drives hiring, promotion, and funding. Because so much rides on it, authorship is also a frequent source of dispute and dishonesty. Ethical authorship rests on a single idea - that credit should track genuine intellectual contribution and be coupled to accountability.

Criteria for authorship

The most widely cited standard, from the International Committee of Medical Journal Editors (the ICMJE criteria), holds that an author should satisfy all four of the following:

1. Substantial contribution to the conception or design of the work, or the acquisition, analysis, or interpretation of data;
2. Drafting the work or revising it critically for important intellectual content;
3. Final approval of the version to be published;
4. Agreement to be accountable for all aspects of the work, including the integrity and accuracy of the whole.

The fourth criterion is the moral core: authorship is not only credit but responsibility. Someone whose name appears on a paper is vouching for it. Contributions that do not meet all four criteria - securing funding alone, general supervision of the group, technical assistance, or providing materials - merit acknowledgment, not authorship.

Dishonest practices

• Guest (or honorary) authorship lists someone who did not meet the criteria, often a senior figure added to lend prestige or in a quid pro quo. It dilutes the meaning of authorship and falsely assigns accountability.
• Gift authorship is closely related: adding a colleague or friend as a favor.
• Ghost authorship is the inverse and arguably worse: a substantial contributor is omitted, most notoriously when an industry writer drafts a paper that appears under an academic's name alone, hiding a conflict of interest from readers.
• Coercion authorship occurs when a senior person uses power to demand undeserved credit from a junior one.

Order, corresponding author, and contributorship

Conventions for author order vary by field, but in many disciplines the first author did the most work and the last author is the senior investigator who directed the project; the corresponding author takes responsibility for communication and for the integrity of the submission. Because these conventions are ambiguous across fields, there is a strong movement toward explicit contributorship statements. A widely adopted taxonomy, CRediT (Contributor Roles Taxonomy), lists specific roles - conceptualization, methodology, formal analysis, writing, and so on - so each person's actual contribution is stated rather than inferred from position.

Practice	What happens	Why it is wrong
Guest / gift authorship	Non-contributor is listed	False credit and false accountability
Ghost authorship	Real contributor is omitted	Hides contribution and often a conflict
Coercion authorship	Power extracts undeserved credit	Exploits a junior researcher

The practical safeguard is to discuss authorship early and openly, ideally when a project begins, and to revisit it as contributions evolve. Most authorship disputes grow from silence and assumption. Naming expectations in advance - who will do what, and what that earns - prevents the great majority of them, and models the fairness you will one day owe your own trainees.

A conflict of interest (COI) exists when a secondary interest - money, career advancement, personal loyalty - has the potential to compromise, or appear to compromise, a researcher's judgment about a primary interest such as the validity of the research or the welfare of participants. Note the structure carefully: a conflict is a situation, not an act. Having a conflict is not itself wrong; the ethical questions are whether it is disclosed and how it is managed.

Actual, potential, and perceived

Conflicts come in three shades, and all three matter. An actual conflict is currently compromising judgment; a potential conflict could do so if circumstances change; a perceived conflict is one that a reasonable observer might suspect, whether or not judgment is in fact affected. Perception matters because science runs on trust: even the appearance of a compromised judgment can undermine confidence in a result, which is why disclosure standards deliberately reach beyond conflicts that have already caused harm.

Financial and non-financial forms

• Financial conflicts are the most scrutinized: research funding from a company whose product is being tested, personal consulting fees or speaker honoraria, equity or stock options, patents and royalties. The concern is well founded - studies funded by an interested sponsor are, on average, more likely to report results favorable to that sponsor, an effect sometimes called the funding effect.
• Non-financial conflicts are subtler but real: the drive to confirm one's own prior theory, the desire to help a friend or harm a rival, ideological commitment, or the pressure of one's own reputation riding on a particular outcome. These are harder to disclose on a form but can bias judgment just as powerfully.

Disclosure and management

The governing principle is not prohibition but transparency plus management. Researchers disclose relevant interests to their institution, to journals when they publish, and often to participants during consent. The institution or journal then decides how to manage the conflict along a graduated scale:

1. Disclose the interest so readers and oversight bodies can weigh it.
2. Manage it - for example, by adding independent oversight, or by having someone without the conflict analyze the data or consent the participants.
3. Prohibit the arrangement or recuse the conflicted person entirely when the conflict is severe and unmanageable, such as a researcher who stands to profit directly evaluating their own product in participants at risk.

Two settings deserve special vigilance. In clinical research, a financial stake in a positive outcome can distort the risk-benefit judgment owed to patients, so the strictest management applies. In peer review and editing, a reviewer who competes with or collaborates closely with the authors has a conflict and should recuse rather than exploit privileged access to an unpublished manuscript. The uniting lesson is disarmingly simple: you cannot always avoid having interests, but you can always be transparent about them. Concealment converts an ordinary, manageable conflict into misconduct.

Data are the evidentiary foundation of every empirical claim, and how they are recorded, stored, and shared is an ethical matter, not merely a technical one. Sloppy data management can make honest work irreproducible and indistinguishable from fraud; good stewardship protects both the integrity of the record and the people the data describe. Increasingly, funders and journals require researchers to plan for data before collecting any.

The data management plan

A data management plan (DMP) is a document, usually written at the proposal stage, that specifies how data will be handled across its life cycle. A serviceable DMP addresses:

• What data will be generated, in what formats, and how much.
• Documentation and metadata - the contextual information (variable definitions, collection procedures, units) without which a dataset is uninterpretable to anyone else, and often to the researcher a year later.
• Storage, backup, and security during the project, including protection of any identifiable data.
• Retention - how long data are kept after the project (institutions often require several years to allow verification) and how they are eventually destroyed or archived.
• Sharing and access - whether, how, and under what conditions others may obtain the data.

The FAIR principles

The modern standard for good data stewardship is captured by the acronym FAIR, which holds that data should be:

Letter	Principle	In practice
F	Findable	Deposited with a persistent identifier and rich metadata
A	Accessible	Retrievable by a clear protocol, even if access is controlled
I	Interoperable	In standard formats and vocabularies others' tools can use
R	Reusable	Well documented and clearly licensed for reuse

A subtle but important point: FAIR is not the same as "open." Accessible means retrievable under a defined, transparent protocol - which may legitimately include authentication and approval. Sensitive human data can be FAIR while remaining controlled-access, released only to qualified researchers under a data-use agreement. The slogan of responsible sharing is therefore "as open as possible, as closed as necessary."

Sharing versus protecting

The duty to share collides, at times, with duties of confidentiality and the limits of consent. Three guardrails keep sharing ethical.

1. Consent must anticipate sharing. If you intend to deposit data for reuse, the consent form should say so; you cannot ethically release data in ways participants never agreed to.
2. De-identify before sharing human data, attending to quasi-identifiers, and use controlled access for data that cannot be safely anonymized.
3. Honor legitimate constraints - genuine privacy risks, Indigenous data-sovereignty rights, and certain proprietary or security limits are valid reasons to restrict, though never a cover for hiding inconvenient results.

Done well, data sharing multiplies the value of research: others can verify findings, ask new questions of existing data, and avoid duplicating costly collection. The ethical craft is to maximize that public good while keeping faith with the individuals whose lives the data represent.

Over the past two decades, science has confronted an uncomfortable discovery about itself: a substantial fraction of published findings, across fields from psychology to cancer biology, do not hold up when others try to reproduce them. This is the reproducibility (or replication) crisis, and the reform movement it triggered - open science - is reshaping research practice. Understanding both is now part of basic research literacy.

Two terms that are often confused

Precision matters here.

• Reproducibility, in the strict sense, means obtaining the same results from the same data and analysis. If a colleague runs your code on your dataset and gets different numbers, the work is not reproducible - a failure of computational transparency.
• Replicability means obtaining consistent results from new data collected in a new study of the same question. Replication tests whether a finding is real and general, not merely whether the original arithmetic was correct.

A finding can be perfectly reproducible (the analysis is faithfully repeatable) yet fail to replicate (a fresh study finds no effect), which typically signals that the original result was a false positive.

The evidence and its causes

Large coordinated efforts have attempted to replicate published studies and found that a worrying share do not replicate, or replicate with markedly smaller effects than originally reported. The causes are, by now, familiar from earlier lessons and reinforce one another:

1. Publication bias - journals favor novel, positive results, so the literature over-represents false positives and hides null findings in the "file drawer."
2. Questionable research practices - p-hacking, HARKing, and optional stopping inflate the rate of spurious significant results.
3. Underpowered studies - small samples yield unstable estimates and, when they do reach significance, often exaggerate the true effect size.
4. Insufficient transparency - when data, materials, and code are unavailable, errors cannot be caught and replications cannot be attempted.

The open-science response

Open science is the umbrella term for practices that make research more transparent, and therefore more self-correcting, at every stage.

Practice	Problem it targets
Pre-registration and Registered Reports	p-hacking, HARKing, publication bias
Open data and open materials	Reproducibility, error detection
Open-source analysis code	Computational reproducibility
Preprints and open access	Slow, restricted dissemination
Registered replication and multi-lab studies	Testing whether effects are real and general

Two clarifications guard against overreaction. First, a failed replication does not by itself prove the original was fraudulent or even wrong; effects can be real but fragile, context-dependent, or smaller than first estimated. The crisis is less about lies than about a system that rewarded novelty over reliability. Second, replication is not a threat to be resented but the mechanism by which science earns its authority; a field that welcomes replication and shares its materials is not admitting weakness but demonstrating strength. The trajectory of reform is toward valuing credible findings over merely novel ones - a cultural shift that individual researchers advance every time they pre-register a study, share their data, or attempt a replication.

Peer review is the quality-control mechanism at the heart of scholarly publishing: before a manuscript becomes part of the record, independent experts evaluate its rigor, novelty, and validity. Because reviewers wield real power over careers and over what counts as knowledge, the role carries strict ethical duties. Most researchers will spend far more hours reviewing others' work than they expect, so learning to do it honorably is a core professional skill.

What peer review is for

Review serves the field, not the reviewer. Its aims are to help editors decide what to publish, to catch errors and overstatement before they mislead others, and to improve a manuscript through constructive critique. It is not a gate for enforcing personal preferences, settling scores, or delaying a competitor. A good review is rigorous but fair: it judges the work against appropriate standards, distinguishes fatal flaws from matters of taste, and offers criticism the authors can act on.

Core duties of a reviewer

• Confidentiality. A manuscript under review is a privileged, unpublished document. A reviewer must not share it, discuss it beyond what the journal permits, or - most seriously - use its ideas, data, or results in their own work before publication. Doing so is a form of theft of unpublished intellectual property.
• Competence and diligence. Accept only manuscripts you are qualified to judge, and evaluate them carefully within the agreed time. Declining a review you cannot do well is itself responsible conduct.
• Impartiality and disclosure of conflicts. A reviewer who competes closely with, collaborates with, or has a personal stake against the authors has a conflict and should recuse, or at minimum disclose it to the editor rather than exploit privileged access.
• Constructive, evidence-based critique. Ground criticisms in specifics, remain civil, and separate the quality of the work from the identity or reputation of its authors.

Unethical publication practices

Beyond the review itself, the publication system has recognized abuses that every researcher should be able to name.

Practice	What it is
Duplicate publication	Publishing the same work in more than one venue as if each were new
Salami slicing	Splitting one study into several thin papers to inflate a publication count
Redundant self-plagiarism	Reusing one's own text or data without disclosure, deceiving readers
Predatory publishing	Journals that charge fees but provide no genuine peer review or quality control

Each of these corrupts the record in a different way - by double-counting, by fragmenting knowledge, by hiding reuse, or by lending a veneer of legitimacy to unvetted claims. The editor, too, has duties: to judge manuscripts on merit, to manage conflicts, to protect confidentiality, and to correct the record through corrections or retractions when serious errors emerge.

Openness in review

Traditional review is often anonymous, which protects candor but can shield unfair or careless reviewing from accountability. In response, some venues now use open peer review, publishing reviewers' reports or names, and post-publication review, in which scrutiny continues in the open after a paper appears. These experiments reflect the same impulse driving open science generally: that transparency, applied to evaluation as well as to data, makes the whole system more trustworthy. Whatever the model, the reviewer's underlying obligation is constant - to serve the integrity of the shared record with the same honesty you would want applied to your own work.

Research ethics is not only a set of individual choices; it is sustained or corroded by the culture and relationships in which researchers work. The single most formative relationship in a scientist's development is with a mentor - and mentoring is therefore an ethical responsibility in its own right, the channel through which the norms of an entire field are transmitted or lost. This final lesson turns from rules to the human environment that makes rules stick.

What a mentor owes a trainee

A research mentor is more than a supervisor of tasks. Recognized responsibilities include:

• Training in responsible conduct - teaching not only techniques but the ethical standards of the discipline, by explicit instruction and, more powerfully, by example. Trainees learn integrity mostly by watching what their mentor tolerates.
• Fair credit and support of independence - giving trainees deserved authorship, promoting their work, and steadily fostering their capacity to work on their own, rather than exploiting their labor to advance the mentor.
• Realistic guidance and honest feedback - including candid advice about careers and the limits of a chosen path.
• Reasonable protection - shielding trainees, so far as possible, from undue pressure, and never demanding participation in questionable practices.

The peril of power asymmetry

The mentor-trainee relationship is marked by a steep power differential. A supervisor typically controls a student's funding, authorship, recommendation letters, and future prospects. That dependency is what makes certain abuses possible - coercion authorship, pressure to produce a desired result, or exploitation of labor - and what makes trainees reluctant to report problems they observe. Recognizing this asymmetry is the first step to using power responsibly rather than carelessly.

Pressure and the conditions for integrity

Individual virtue is necessary but not sufficient; environments powerfully shape behavior. The intense pressures of academic life - "publish or perish," competition for scarce funding, the premium on novel positive results - can push otherwise honest people toward corner-cutting. A healthy research culture counteracts these pressures deliberately:

1. Psychological safety - an environment in which a junior member can question a result, admit a mistake, or report a concern without fear of retaliation. Where raising a problem is dangerous, problems are hidden rather than fixed.
2. Modeling by leaders - senior researchers who visibly value rigor and honesty over sheer output set the norm the whole group follows.
3. Protected channels - ombuds offices, research-integrity officers, and clear procedures that let concerns be raised and whistleblowers be protected from reprisal.

The obligation to respond

Finally, membership in a research community carries a duty not to look away. If you have a good-faith, well-founded concern about serious wrongdoing, you have an obligation to raise it through appropriate channels - discussing it first with a trusted advisor or an integrity officer, documenting what you observed, and acting on evidence rather than rumor. This is hard, especially against a power differential, which is exactly why whistleblower protections exist and why a mature institution treats a good-faith report as a service rather than a betrayal. The through-line of this entire course returns here: ethics is not a set of external constraints imposed on science from outside, but the very fabric of trust that makes cumulative, collaborative knowledge possible. You inherit that fabric from those who trained you, and you will hand it, strengthened or frayed, to those you train.