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| Auto-plagio e riciclo di testo× | Similarità vs Plagio: Comprendere la Distinzione× | |
|---|---|---|
| Campo | Etica della ricerca | Etica della ricerca |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1990s | 2000s |
| Ideatore≠ | International Committee of Medical Journal Editors (ICMJE) | Academic integrity frameworks and plagiarism detection software companies |
| Tipo | Concept | Concept |
| Fonte seminale≠ | Roig, M. (2015). Avoiding plagiarism, self-plagiarism, and other questionable writing practices: A guide to ethical writing. U.S. Department of Health and Human Services Office of Research Integrity. link ↗ | Hirsch, L. R. (2013). Recognizing plagiarism: A guide for academic professionals. Teaching Professor Blog. link ↗ |
| Alias≠ | text recycling, self-copying, duplicate publication, redundant publication | similarity index, turnitin score, similarity percentage |
| Correlati≠ | 2 | 4 |
| Sintesi≠ | Self-plagiarism, or text recycling, occurs when an author reuses substantial portions of their own previously published work in a new publication without disclosure or acknowledgment. This includes republishing the same article in different venues, duplicating methods sections across multiple papers, or reusing discussion sections. While the intellectual property is the author's own, self-plagiarism is considered misconduct because it violates the principle that published work represents new research and it may inflate publication counts. | A critical distinction exists between similarity percentages generated by plagiarism detection software (Turnitin, iThenticate) and an actual plagiarism verdict. A similarity index is a red flag requiring review; it is not a plagiarism determination. High similarity can result from legitimate quotations, references, shared technical language, or common knowledge. Conversely, low similarity does not guarantee absence of plagiarism. Human expert judgment is essential—similarity detection software provides data, not judgment. |
| ScholarGateInsieme di dati ↗ |
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