From plagiarism to predatory journals: academic misconduct, misrepresentation, and gaming

writing desk

When we hear the words academic misconduct, we usually think of individuals involved in plagiarism and other kinds of unethical scholarly behavior, and less often of organizations implicated in such affairs. Yet in recent years, universities have earned a reputation for ruthless manipulating figures to improve their positions in international rankings. Editors attempting to elevate their impact factor compel authors to cite articles published by their journals. To maximize profits, publishers launch predatory journals ready to publish practically every submission, while individuals resort to gaming strategies like text-recycling and self-citations to enhance their chances for promotion.

These examples, very much characteristic of recent times, suggest that the phenomenon of academic misconduct has evolved. But what about our understanding of it? To fill in the gap in our knowledge regarding research misconduct, its taxonomy, prevalence, and factors that contribute to this kind of behavior, Mario Biagioli and colleagues have prepared a special issue of Research Policy dedicated entirely to it, which they appropriately titled “Academic Misconduct, Misrepresentation, and Gaming.”

Let’s take a look at what the authors in this issue have to say about this increasingly important subject.

What is academic misconduct?

The guest editors of this special issue propose moving beyond the traditional definition of misconduct, which focuses on deliberate malpractices such as fabrication, falsification, and plagiarism (Biagioli et al., 2019). The so-called questionable research practices, such as impact factor gaming or the emergence of pseudo journals, should also be part of research on academic misconduct. These practices are considered questionable because they include behavior that might be deemed legitimate in some cases, thus not every scientist would consider them to be unethical. Self-citation may be defined as establishing an approach to research similar in focus, as well as a strategy to boost citation counts (Seeber et al., 2019).

Several papers in the special issue offer their categorization of behaviors that exist beyond fabrication and falsification. In the editorial of the special issue, the guest editors establish a wide-ranging array of deviant behaviors within the life-cycle of research production to dissemination (Biagioli et al., 2019). During the first stage of research, the most obvious examples of misconduct include the fabrication of research data, material evidence, and results. The stage of the review process also offers opportunities for gaming, such as positive bias of mentorship networks or harsh criticism by competitors. When an article is published, the most widespread examples of malpractice range from adding undeserved authors and omitting individuals who made a significant contribution to plagiarism and text-recycling. The reason for these instances of misconduct can be traced back to the desire to maximize the impact factor by gaming citations.

To reduce ambiguity, Hall and Martin (2019) developed a theory-based taxonomy that differentiates various forms of research behavior including appropriate practices, questionable conduct, inappropriate practices, and blatant misconduct. As an example, winsorization, which is a way to minimize the influence of outliers on a data set, is widely accepted as good scientific practice while data fabrication and falsification are clearly identified as methods that break scientific norms. This taxonomy incorporates the nature and severity of different types of research misconduct, its sources, and the affected stakeholders. In addition to contributing the taxonomy, Hall and Martin explore different theoretical perspectives including rational choice, strain, cultural, network, and bounded rationality theories of misconduct.

How common is academic misconduct?

The answer depends on which methods researchers use to track misconduct. One strategy is to rely on self-reported or ‘observed’ misconduct. According to Biagioli et al. (2019), although researchers rarely report their own academic dishonesty, they confirm that such practices are comparatively widespread in academia. However, the sensitivity of the topic is a critical limitation in self-reported evidence regarding misconduct. As an alternative, measuring unethical behavior by analyzing publications has the potential to overcome this limitation.

Several empirical papers in the special issue use publications as the primary source for data analysis. Horbach and Halffman (2019) analyzed 922 journal articles using Turnitin plagiarism detection software. Bagues, Sylos-Labini, and Zinovyeva (2019) found that five percent of Italian academics have published in Beall’s list of predatory journals. To detect strategic use of self-citations, Seeber et al. (2019) retrieved information on publications and citations for a total of 886 Italian academics. This line of research builds on the considerable availability of publications and citations via citation databases. Another data source is national databases maintained at the central level by state officials. According to national assessment procedures, academics are obligated to provide information about their research performance that, in many recent cases, is publicly available for analysis, as was the case for Italy.

Studies exploring the scale of misconduct reveal remarkable variation across disciplines, countries, and individuals. For example, Horbach and Halffman did not detect any plagiarism in their analysis of publications across four disciplines, while previous research on plagiarism in management found it in 25 percent of papers (Honig & Bedi, 2012). This high degree of variation makes researchers focus on factors contributing to academic misconduct.

Which factors influence academic misconduct?

To explain the prevalence of academic misconduct, scholars have used two principal approaches, individual- and organization-oriented, (Berggren & Karabag, 2019). Individual factors are related to the characteristics, position, and identity of an individual author. For example, Bagues and his colleagues explain that “researchers who publish in dubious journals are usually younger, they are more prolific but have fewer publications in high-impact journals, and they tend to be based in departments with lower research quality” (Bagues et al., 2019, p. 2). Furthermore, young scientific writers are more likely to recycle previous work (Horbach & Halffman, 2019).

Organization-oriented factors bring attention to the idea that misconduct emerges as a result of organizational or institutional incentives. In the special issue, authors used the case of Italy to model how national incentive systems designed to improve performance could have carried detrimental effects on scientific integrity. Seeber et al. (2019) showed that Italian academics respond to the use of citations when making career decisions through increasing the number of self-citations. This is especially the case with scientists in a vulnerable position with fewer citations in comparison to their peers. Similarly, Italian professors publish in predatory journals to meet requirements for academic positions (Bagues et al., 2019). These studies emphasize the importance of designing evaluation procedures that take into account the strategic nature of scientists. The authors recommend not only excluding self-citations but also determining the value of a citation in proportion to the institutional network distance between the citing and cited authors.

Walsh, Lee, and Tang (2019) join other authors in arguing that organizational theory can provide insights for explaining variations in pathology rates that surpass individual explanation. They developed an organization theory of scientific pathologies that links a strict division of labor among highly skilled specialists with the likelihood of pathologies. Such a division of labor made it more difficult to identify misconduct because structural secrecy, miscommunication, alienation, and delegation of responsibility prevent detection and correction pathologies. Data on retractions in biomedical and life sciences demonstrate that after controlling for societal corruption and high-stakes incentive systems, a greater division of labor is still associated with retractions.

Key contributions and future line of research

The special issue contributes to the research on academic misconduct in several ways. First, attention is brought to questionable research practices that, in general, are an under-researched topic. Second, empirical studies demonstrate the advantages of secondary sources that represent a significant source of data considering the extreme sensitivity concerning misconduct. Third, studies reveal the fruitfulness of employing different theoretical perspectives from organizational science (Berggren & Karabag, 2019; Walsh, Lee, & Tang, 2019), game theory (Gall & Maniadis, 2019), and sociology (Hussinger & Pellens, 2019) in understanding questionable research behaviors. Since the literature on academic misconduct is largely descriptive and written by scientists in different fields concerned with such misbehavior in their communities (Biagioli et al., 2019), this promising line of research is greatly determined with providing explanatory frameworks from the social sciences.


Bagues, M., Sylos-Labini, M., & Zinovyeva, N. (2019). A walk on the wild side: ‘Predatory’ journals and information asymmetries in scientific evaluations. Research Policy, 48(2), 462–477.

Berggren, C., & Karabag, S. F. (2019). Scientific misconduct at an elite medical institute: The role of competing institutional logics and fragmented control. Research Policy, 48(2), 428–443.

Biagioli, M., Kenney, M., Martin, B. R., & Walsh, J. P. (2019). Academic misconduct, misrepresentation and gaming: A reassessment. Research Policy, 48(2), 401–413.

Gall, T., & Maniadis, Z. (2019). Evaluating solutions to the problem of false positives. Research Policy, 48(2), 506–515.

Hall, J., & Martin, B. R. (2019). Towards a taxonomy of research misconduct: The case of business school research. Research Policy, 48(2), 414–427.

Honig, B., & Bedi, A. (2012). The fox in the hen house: A critical examination of plagiarism among members of the academy of management. Academy of Management Learning & Education, 11(1), 101–123.

Horbach, S.P.J.M., & Halffman, W. (2019). The extent and causes of academic text recycling or ‘self-plagiarism’. Research Policy, 48(2), 492–502.

Hussinger, K., & Pellens, M. (2019). Guilt by association: How scientific misconduct harms prior collaborators. Research Policy, 48(2), 516–530.

Seeber, M., Cattaneo, M., Meoli, M., & Malighetti, P. (2019). Self-citations as strategic response to the use of metrics for career decisions. Research Policy, 48(2), 478–491.

Walsh, J. P., Lee, Y.-N., & Tang, L. (2019). Pathogenic organization in science: Division of labor and retractions. Research Policy, 48(2), 444–461.

Katerina Guba is a lead researcher at the Centre for Institutional Analysis of Science and Education, European University at St. Petersburg, Russia. In 2015, she defended her thesis on the comparative analysis of the journal publishing market in American and Russian sociology. You can follow Katerina on Twitter.

Photo: Pexels

Leave a Reply