Researcher Fraud and Plagiarism (UGC-NET Unit VI)

Research misconduct is defined, with local variation across journals, universities and funders, as fabrication, falsification or plagiarism in proposing, performing or reviewing research, or in reporting research results.

The shorthand for this three-part definition is FFP. It is deliberately narrow: it does not cover honest mistakes, differences of scientific judgement about how to analyse a dataset, or authorship disputes. What separates misconduct from error is intent, meaning the act was committed knowingly, intentionally or with reckless disregard for the truth of the record.

For NET purposes, hold three points together. First, FFP requires intent, not just an outcome that turned out wrong. Second, findings are established on a preponderance of evidence, not proof beyond reasonable doubt. Third, coverage of FFP varies by jurisdiction even though the underlying concept travels well: national systems, professional bodies and journals each apply their own procedures on top of the shared FFP core.

Fabrication invents the evidentiary record outright. A fabricating researcher reports survey responses no respondent gave, transcripts from interviews that never happened, or statistics from no actual dataset. It starts from nothing and manufactures the appearance of a study. Fabrication is comparatively rare next to the other two categories because a fabricated dataset must remain internally consistent across every table, and it risks exposure if an editor, co-author or replicating team asks to see the raw material.

Falsification differs because the underlying study is real. Data were collected or records were coded, but the researcher then changes, omits or selectively presents that material so the published account no longer matches what actually happened.

Common forms include altering values, deleting inconvenient outliers without disclosure, and dropping cases that do not support the intended conclusion. Because these choices can be dressed up as ordinary analytic discretion, falsification is often harder to prove than fabrication, and an investigation typically needs the original data and coding sheets to establish that a change was deliberate.

Plagiarism ranges from verbatim copying of another author's sentences, through close paraphrasing that keeps the original structure while swapping surface wording, to unattributed use of a dataset, coding scheme or theoretical argument developed by someone else.

All three breach the same norm: credit follows the person who did the intellectual work. Detection is now largely automated, with text-similarity software flagging overlapping passages for a human reviewer to assess in context, since a high similarity score can also come from properly quoted material or a shared literature review.

Self-plagiarism, also called text recycling, occurs when an author reuses substantial portions of their own previously published text, data or findings in a new publication without disclosure, presenting the work as new.

It is treated as a form of plagiarism because it misrepresents the originality of the output. A related practice, salami slicing, splits one dataset into the smallest publishable units to maximise a publication count, and is treated as a questionable research practice for the same reason: it distorts how much genuinely new evidence exists.

Between clean conduct and outright FFP sits a wider set of questionable research practices, often shortened to QRPs, that fall short of the formal misconduct definition but still distort what a study appears to show. P-hacking means trying multiple analytic choices on the same dataset until one combination crosses a conventional significance threshold, then reporting only that combination as the planned analysis.

HARKing, hypothesising after the results are known, presents a hypothesis formed after seeing the data as though it had been predicted in advance. Two responses have gained traction against both: pre-registration, which files hypotheses and planned analysis before data collection, and open data policies, which let other researchers check a reported result against the original material.

Most institutions handle a misconduct allegation in staged fashion. An initial inquiry establishes whether the allegation is specific and credible enough to warrant a full investigation. If it clears that bar, a formal investigation panel, usually made up of researchers outside the accused person's immediate team, examines the original data and correspondence and reaches a finding on the balance of the evidence.

A finding can lead to correction or retraction of the published work, restrictions on future funding, and disciplinary action, with the exact sanctions set by the employing institution and funder. Much of what surfaces first comes from whistleblowers, meaning colleagues, students or collaborators who notice an inconsistency and report it.