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@article{208934,
        author = {Dr. Sanjay Kumar},
        title = {Understanding Issues of Plagiarism: Forms, Causes, Detection Limits and Regulatory Responses in Higher Education and Research},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {1-8},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208934},
        abstract = {Plagiarism remains one of the most frequently cited threats to academic integrity, yet universities often treat it as a single offence to be caught by software. This paper examines plagiarism as a layered problem: a set of distinct practices with different causes, uneven detectability and varying seriousness, now complicated by generative artificial intelligence. The study follows an integrative review of peer-reviewed research, meta-analyses, tool evaluations and one national regulatory instrument, the University Grants Commission (UGC) regulations of 2018. Sources were verified against publisher records and synthesised thematically. No primary data were collected; all figures reported are drawn from the cited studies. Plagiarism spans a continuum from verbatim copying and idea theft to patchwriting, text recycling and undisclosed ghost or machine authorship. Self-reported plagiarism among scientists is low (a pooled 1.7%), but 30% report having witnessed it, and plagiarism accounts for nearly one in ten biomedical retractions. Causes operate at individual, instructional, institutional and technological levels. Text-matching software finds verbatim overlap but misses paraphrase and translation, while detectors for AI-generated text are neither accurate nor reliable and misclassify non-native writing. India's UGC framework ties sanctions to similarity percentages, which risks equating a software score with misconduct. The paper proposes a four-level framework linking causes to responses and argues that institutions should move from percentage-based policing towards judgement-based, educative integrity systems},
        keywords = {Plagiarism; academic integrity; patchwriting; self-plagiarism; text-matching software; generative AI; research misconduct; UGC regulations},
        month = {October},
        }