Direct comparison
Falsification vs. Fabrication in Research
Fabrication in research means inventing data never collected; falsification manipulates real data. Compared under 42 CFR 93.211/93.212, with cases.
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How do Falsification, Fabrication compare side by side?
The table below compares Falsification, Fabrication across 7 procurement-relevant dimensions, from did the underlying research event occur? through requires intent to be adjudicated as misconduct?.
Side-by-side comparison
| Dimension | Falsification | Fabrication |
|---|---|---|
| Did the underlying research event occur? | Yes — the experiment, observation, or process actually happened | No — the reported result has no real underlying event |
| What's dishonest | The representation of real data or materials | The existence of the data itself |
| 42 CFR Part 93 definition | Manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record | Making up data or results and recording or reporting them |
| Typical form | Selective exclusion of data points, undisclosed image adjustment, altered measurement values, misrepresented protocol steps | Invented survey responses, non-existent experiments, wholly synthetic datasets presented as real |
| Common detection methods | Image-forensic tools (Proofig, ImageTwin), statistical forensics (GRIM, SPRITE, Benford's law), failed independent replication | Failed independent replication, absent raw data/lab notebooks, whistleblower reports from collaborators with access to the real record |
| Federal citation | 42 CFR 93.212 (Falsification); research misconduct itself is defined at 93.234 | 42 CFR 93.211 (Fabrication); research misconduct itself is defined at 93.234 |
| Requires intent to be adjudicated as misconduct? | Yes — honest error or differences of opinion are explicitly excluded | Yes — honest error or differences of opinion are explicitly excluded |
Common questions
Common questions about Falsification vs Fabrication
What is fabrication in research?
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Fabrication in research is making up data, results, or an entire experiment that was never actually conducted, then recording or reporting it as if it were real — for example, claiming survey responses from 200 participants when only 80 were recruited, or reporting an experiment that was never run. It is defined at 42 CFR 93.211 as one of the three components of the federal FFP (fabrication, falsification, plagiarism) definition of research misconduct at 42 CFR 93.234. It differs from falsification (42 CFR 93.212), which involves manipulating or omitting data from a research event that did happen.
Can a single case involve both falsification and fabrication?
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Yes. Eric Poehlman (University of Vermont, 2005) fabricated and falsified data across roughly ten publications and 17 grant applications in the same body of work, admitting to 54 separate ORI and institutional misconduct findings — the two categories are independent, not mutually exclusive, and often appear together.
Is falsification worse than fabrication, or vice versa?
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Neither the regulation nor ORI ranks one as categorically worse — both are treated as equally serious forms of research misconduct under 42 CFR 93.234, which lists fabrication and falsification side by side with no hierarchy, and sanctions are determined case by case based on severity, extent, and impact, not which FFP category applies.
Does an honest mistake count as falsification?
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No. 42 CFR 93.234 defines research misconduct and expressly excludes honest error and differences of opinion. A separate section, 42 CFR 93.103, sets the standard a finding must meet: a significant departure from accepted practices of the relevant research community, committed intentionally, knowingly, or recklessly, and proven by a preponderance of the evidence.
Where does plagiarism fit relative to these two?
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Plagiarism is the third FFP component, defined separately at 42 CFR 93.227 as appropriating another person's ideas, processes, results, or words without giving appropriate credit — it concerns attribution, not the honesty of the data itself. 93.227(b) also expressly excludes self-plagiarism and authorship or credit disputes. A case can involve any one, two, or all three FFP categories.
Going deeper
