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Dictionary termTrack DProposedv2026.2

Salami slicing

Salami slicing (salami publication) is dividing the results of a single coherent study or dataset into multiple separately submitted papers, each too fragmentary to represent the work fully, without disclosing the relationship to editors or readers.

ByCASRAI Editorial Board
· Last updated 22 Aug 2026
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Examples

Worked examples

  • Is an instance

    A single 200-participant cohort study published as four papers (one per outcome variable), none of which cross-reference the others.

Counter-examples

Looks similar, but isn't

  • Not an instance

    A baseline-cohort descriptive paper followed by an intervention-trial paper using the same recruitment infrastructure, with each paper citing the other.

Editorial commentary

Salami slicing (also called salami publication or data fragmentation) is the practice of dividing the results of one coherent study, dataset, or research question into multiple separate papers, each reporting only a partial, “least publishable unit” of the work, without disclosing the relationship to editors, reviewers, or readers. The operational test is not the number of papers a project produces but whether each individual paper could stand as a complete, honest account of the question it claims to answer, and whether any overlap with sibling papers (same sample, same cohort, same primary dataset) is disclosed and cross-referenced.

What it is not

Salami slicing is frequently confused with duplicate publication, but the two are structurally different problems. Duplicate publication republishes substantially the same results as if they were new. Salami slicing does the opposite: it splits new, non-overlapping results from one underlying study across several papers, undisclosed. Salami slicing is also distinct from a legitimate multi-paper research program: a large multi-site trial that pre-specifies a primary-outcome paper and several secondary-outcome papers, or a longitudinal study that publishes distinct, genuinely separable analyses over time, is not salami slicing when each paper addresses a different question, adds independent value, and cross-references the related papers openly.

Why it matters

Fragmenting one dataset across undisclosed papers degrades the literature in concrete ways: it can bias meta-analyses when the same participants or samples are counted more than once without cross-reference, it inflates a researcher’s individual publication count relative to the actual contribution, and it forces reviewers and readers to evaluate incomplete slices of a study without the full picture. Editors increasingly ask authors, at submission, to declare any closely related manuscripts that are in press, under review, or recently published from the same dataset, precisely to catch undisclosed fragmentation before publication rather than after.

In practice

Research offices and authors can manage this risk by deciding, before submission, whether a body of work is genuinely separable into distinct research questions, and by disclosing overlapping samples or datasets to every journal involved regardless of outcome. Confirmed cases are usually addressed with a correction, an editorial note explaining the overlap, or in more serious or repeated instances a formal COPE-guided investigation; deliberate, undisclosed fragmentation intended to inflate output can be treated as a breach of publication ethics by an institution even where it does not meet a narrower legal definition of research misconduct.

Related terms

See also questionable research practices, research misconduct, and the European Code of Conduct for Research Integrity.

References

  • COPE Discussion Document: Salami Publication (2020)
  • ICMJE Recommendations (current edition)

Also known as

salami publication · least publishable unit · LPU

Machine-readable encodings

Use in your systems

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Schema.org DefinedTerm (JSON-LD)
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