Analysis of duplicated publications in Russian journals

Chekhovich, Yu. V.; Khazov, Andrey V.

doi:10.1016/j.joi.2021.101246

Cited by 10 publications

(2 citation statements)

References 24 publications

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“…The total number of indexed publications is 41 million, and 15 million full texts are available at eLIBRARY.RU. Recently, Antiplagiat was used to study academic ethics violations in Russian scientific periodicals related to the duplicated publication (Chekhovich & Khazov, 2022 ). Thus, Antiplagiat is a reasonable instrument for detecting academic plagiarism.…”

Section: Methodsmentioning

confidence: 99%

Ambiguity in Ethical Standards: Global Versus Local Science in Explaining Academic Plagiarism

Guba,

Tsivinskaya

2024

Sci Eng Ethics

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The past decade has seen extensive research carried out on the systematic causes of research misconduct. Simultaneously, less attention has been paid to the variation in academic misconduct between research fields, as most empirical studies focus on one particular discipline. We propose that academic discipline is one of several systematic factors that might contribute to academic misbehavior. Drawing on a neo-institutional approach, we argue that in the developing countries, the norm of textual originality has not drawn equal support across different research fields depending on its level of internationalization. Using plagiarism detection software, we analyzed 2,405 doctoral dissertations randomly selected from all dissertations defended in Russia between 2007 and 2015. We measured the globalization of each academic discipline by calculating the share of publications indexed in the global citation database in relation to overall output. Our results showed that, with an average share of detected borrowings of over 19%, the incidence of plagiarism in Russia is remarkably higher than in Western countries. Overall, disciplines closely follow the pattern of higher globalization associated with a lower percentage of borrowed text. We also found that plagiarism is less prevalent at research-oriented institutions supporting global ethical standards. Our findings suggest that it might be misleading to measure the prevalence of academic misconduct in developing countries without paying attention to variations at the disciplinary level.

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Section: Methodsmentioning

confidence: 99%

Ambiguity in Ethical Standards: Global Versus Local Science in Explaining Academic Plagiarism

Guba,

Tsivinskaya

2024

Sci Eng Ethics

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“…One important aspect of duplication detection is the determination of threshold values [19]. Selecting a high threshold value will result in a false negative, while choosing a low threshold value will result in a positive false value that cannot accurately detect duplicate information.…”

Section: Introductionmentioning

confidence: 99%

Proposed threshold-based and rule-based approaches to detecting duplicates in bibliographic database

Amin,

Stiawan,

Ermatita

et al. 2024

Bulletin EEI

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Bibliographic databases are used to measure the performance of researchers, universities and research institutions. Thus, high data quality is required and data duplication is avoided. One of the weaknesses of the threshold-based approach in duplication detection is the low accuracy level. Therefore, another approach is required to improve duplication detection. This study proposes a method that combines threshold-based and rule-based approaches to perform duplication detection. These two approaches are implemented in the comparison stage. The cosine similarity function is used to create weight vectors from the features. Then, the comparison operator is used to determine whether the pair of records are grouped as duplication or not. Three research databases: Web of Science (WoS), Scopus, and Google Scholar (GS) on the Science and Technology Index (SINTA) database are investigated. Rule 4 and Rule 5 provide the best performance. For WoS dataset, the accuracy, precision, recall, and F1-measure values were 100.00%. For Scopus dataset, the accuracy and precision values were 100.00%, recall: 98.00%, and the F1-measure value is 98.00%. For GS dataset, the accuracy value was 100.00%, precision: 99.00%, recall: 97.00%, and the F1-measure value is 98.00%. The proposed method is potential tool for accurate detection on duplication records in publication databases.

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Quality and Policies for Academic Integrity: Challenges Faced by Russian Universities

Abalkina

2023

Handbook of Academic Integrity

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Analysis of duplicated publications in Russian journals

Cited by 10 publications

References 24 publications

Ambiguity in Ethical Standards: Global Versus Local Science in Explaining Academic Plagiarism

Ambiguity in Ethical Standards: Global Versus Local Science in Explaining Academic Plagiarism

Proposed threshold-based and rule-based approaches to detecting duplicates in bibliographic database

Quality and Policies for Academic Integrity: Challenges Faced by Russian Universities

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