Evaluation of Turkish Academic and Student Attitudes on Plagiarism: Validity and Reliability of the Plagiarism Attitudes Scale.

The main purpose of this study was to translate the Plagiarism Attitude Scale into Turkish and validate it for use in Turkish settings, in order to better understand research integrity attitudes and awareness of the Turkish academic and student community, while also contributing an instrument for research in this area. The research was designed and conducted with 483 participants. In the process of adapting the scale to Turkish, language, content, and construct validity analyses were performed. Following the completion of the validity phase, the reliability of the scale was examined using Cronbach's alpha coefficient and the split-half method. The results indicate that the scale's language and content validity are deemed sufficient. According to the findings of the research, the Plagiarism Attitude Scale, in its adapted Turkish version, is considered a valid and reliable tool. The use of this Turkish scale will assist local researchers in sharing their unique perspectives and help the international community better understand research ethics concerns in Türkiye. Additionally, this scale will serve as a valuable resource for planning educational programs.

Research integrity and academic medicine: the pressure to publish and research misconduct.

CONTEXT: This narrative review article explores research integrity and the implications of scholarly work in medical education. The paper describes how the current landscape of medical education emphasizes research and scholarly activity for medical students, resident physicians, and faculty physician educators. There is a gap in the existing literature that fully explores research integrity, the challenges surrounding the significant pressure to perform scholarly activity, and the potential for ethical lapses by those involved in medical education. OBJECTIVES: The objectives of this review article are to provide a background on authorship and publication safeguards, outline common types of research misconduct, describe the implications of publication in medical education, discuss the consequences of ethical breaches, and outline possible solutions to promote research integrity in academic medicine. METHODS: To complete this narrative review, the authors explored the current literature utilizing multiple databases beginning in June of 2021, and they completed the literature review in January of 2023. To capture the wide scope of the review, numerous searches were performed. A number of Medical Subject Headings (MeSH) terms were utilized to identify relevant articles. The MeSH terms included "scientific misconduct," "research misconduct," "authorship," "plagiarism," "biomedical research/ethics," "faculty, medical," "fellowships and scholarships," and "internship and residency." Additional references were accessed to include medical school and residency accreditation standards, residency match statistics, regulatory guidelines, and standard definitions. RESULTS: Within the realm of academic medicine, research misconduct and misrepresentation continue to occur without clear solutions. There is a wide range of severity in breaches of research integrity, ranging from minor infractions to fraud. Throughout the medical education system in the United States, there is pressure to publish research and scholarly work. Higher rates of publications are associated with a successful residency match for students and academic promotion for faculty physicians. For those who participate in research misconduct, there is a multitude of potential adverse consequences. Potential solutions to ensure research integrity exist but are not without barriers to implementation. CONCLUSIONS: Pressure in the world of academic medicine to publish contributes to the potential for research misconduct and authorship misrepresentation. Lapses in research integrity can result in a wide range of potentially adverse consequences for the offender, their institution, the scientific community, and the public. If adopted, universal research integrity policies and procedures could make major strides in eliminating research misconduct in the realm of academic medicine.

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

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.

Identifying the factors influencing plagiarism in higher education: An evidence-based review of the literature.

The present study explores the major reasons for committing plagiarism, as reported in published literature. One hundred sixty-six peer-reviewed articles, which were retrieved from the Scopus database, were carefully examined to find out the research studies conducted to explore the most common reasons for academic cheating among students and researchers in different disciplines in higher education. An analysis of collected literature reveals that 19 studies were conducted to identify the perceived reasons of committing plagiarism. Four studies with similar constructs of perceived reasons of committing plagiarism, namely busy schedule, overload of homework and laziness, easy accessibility of electronic resources, poor knowledge in research writing and correct citation and lack of serious penalty, were conducted. The pooled mean and standard deviation of the four studies reveal that easy accessibility of electronic resources (Mean = 3.6, SD = 0.81), unawareness of instructions (Mean = 3.0, SD = 0.89), and busy schedule, overload of homework and laziness (Mean = 2.89, SD = 1.0) are important perceived reasons for committing plagiarism. The study findings could help create an effective intervention and a robust anti-plagiarism policy for academic institutions, administrators, and policymakers in detecting academic dishonesty while emphasizing the value of integrity in academic pursuit.

A versatile dataset for intrinsic plagiarism detection, text reuse analysis, and author clustering in Urdu.

Plagiarism detection (PD) is a process of identifying instances where someone has presented another person's work or ideas as their own. Plagiarism detection is categorized into two types (i) Intrinsic plagiarism detection primarily concerns the assessment of authorship consistency within a single document, aiming to identify instances where portions of the text may have been copied or paraphrased from elsewhere within the same document. Author clustering, closely related to intrinsic plagiarism detection, involves grouping documents based on their stylistic and linguistic characteristics to identify common authors or sources within a given dataset. On the other hand, (ii) extrinsic plagiarism detection delves into the comparative analysis of a suspicious document against a set of external source documents, seeking instances of shared phrases, sentences, or paragraphs between them, which is often referred to as text reuse or verbatim copying. Detection of plagiarism from documents is a long-established task in the area of NLP with remarkable contributions in multiple applications. A lot of research has already been conducted in the English and other foreign languages but Urdu language needs a lot of attention especially in intrinsic plagiarism detection domain. The major reason is that Urdu is a low resource language and unfortunately there is no high-quality benchmark corpus available for intrinsic plagiarism detection in Urdu language. This study presents a high-quality benchmark Corpus comprising 10,872 documents. The corpus is structured into two granularity levels: sentence level and paragraph level. This dataset serves multifaceted purposes, facilitating intrinsic plagiarism detection, verbatim text reuse identification, and author clustering in the Urdu language. Also, it holds significance for natural language processing researchers and practitioners as it facilitates the development of specialized plagiarism detection models tailored to the Urdu language. These models can play a vital role in education and publishing by improving the accuracy of plagiarism detection, effectively addressing a gap and enhancing the overall ability to identify copied content in Urdu writing.

Retraction of health science articles by researchers in Latin America and the Caribbean: A scoping review.

We aimed to conduct a scoping review to assess the profile of retracted health sciences articles authored by individuals affiliated with academic institutions in Latin America and the Caribbean (LAC). We systematically searched seven databases (PubMed, Scopus, Web of Science, Embase, Medline/Ovid, Scielo, and LILACS). We included articles published in peer-reviewed journals between 2003 and 2022 that had at least one author with an institutional affiliation in LAC. Data were collected on the year of publication, study design, authors' countries of origin, number of authors, subject matter of the manuscript, scientific journals of publication, retraction characteristics, and reasons for retraction. We included 147 articles, the majority being observational studies (41.5%). The LAC countries with the highest number of retractions were Brazil (n = 69), Colombia (n = 16), and Mexico (n = 15). The areas of study with the highest number of retractions were infectology (n = 21) and basic sciences (n = 15). A retraction label was applied to 89.1% of the articles, 70.7% were retracted by journal editors, and 89.1% followed international retraction guidelines. The primary reasons for retraction included errors in procedures or data collection (n = 39), inconsistency in results or conclusions (n = 37), plagiarism (n = 21), and suspected scientific fraud (n = 19). In conclusion, most retractions of scientific publications in health sciences in LAC adhered to international guidelines and were linked to methodological issues in execution and scientific misconduct. Efforts should be directed toward ensuring the integrity of scientific research in the field of health.

A model of the interrelationship between research ethics and research integrity.

Purpose: The purpose of this article is to explore the interrelationship between research ethics and research integrity with a focus on the primary forms of research misconduct, including plagiarism, fabrication, and falsification. It also details the main factors for their occurrence, and the possible ways for mitigating their use among scholars.Methods: The method employed a detailed examination of the main ethical dilemmas, as delineated in literature, as well as the factors leading to these ethical breaches and the strategies to mitigate them. Further, the teaching experiences of the primary author are reflected in the development of the model.Results: The results of this article are represented in a model illustrating the interrelationship between research ethics and research integrity. Further, a significant aspect of our article is the identification of novel forms of research misconduct concerning the use of irrelevant or forced citations or references.Conclusion: In conclusion, the article highlights the substantial positive effects that adherence to research ethics and integrity have on the academic well-being of scholars.

Research Integrity: Where We Are and Where We Are Heading.

The concept of research integrity (RI) refers to a set of moral and ethical standards that serve as the foundation for the execution of research activities. Integrity in research is the incorporation of principles of honesty, transparency, and respect for ethical standards and norms throughout all stages of the research endeavor, encompassing study design, data collecting, analysis, reporting, and publishing. The preservation of RI is of utmost importance to uphold the credibility and amplify the influence of scientific research while also preventing and dealing with instances of scientific misconduct. Researchers, institutions, journals, and readers share responsibilities for preserving RI. Researchers must adhere to the highest ethical standards. Institutions have a role in establishing an atmosphere that supports integrity ideals while also providing useful guidance, instruction, and assistance to researchers. Editors and reviewers act as protectors, upholding quality and ethical standards in the dissemination of research results through publishing. Readers play a key role in the detection and reporting of fraudulent activity by critically evaluating content. The struggle against scientific misconduct has multiple dimensions and is continuous. It requires a collaborative effort and adherence to the principles of honesty, transparency, and rigorous science. By supporting a culture of RI, the scientific community may preserve its core principles and continue to contribute appropriately to society's well-being. It not only aids present research but also lays the foundation for future scientific advancements.

Chatbots, generative AI, and scholarly manuscripts: WAME recommendations on chatbots and generative artificial intelligence in relation to scholarly publications.

This statement revises our earlier "WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications" (January 20, 2023). The revision reflects the proliferation of chatbots and their expanding use in scholarly publishing over the last few months, as well as emerging concerns regarding lack of authenticity of content when using chatbots. These recommendations are intended to inform editors and help them develop policies for the use of chatbots in papers published in their journals. They aim to help authors and reviewers understand how best to attribute the use of chatbots in their work and to address the need for all journal editors to have access to manuscript screening tools. In this rapidly evolving field, we will continue to modify these recommendations as the software and its applications develop.

Esta declaración revisa las anteriores "Recomendaciones de WAME sobre ChatGPT y Chatbots en Relation to Scholarly Publications" (20 de enero de 2023). La revisión refleja la proliferación de chatbots y su creciente uso en las publicaciones académicas en los últimos meses, así como la preocupación por la falta de autenticidad de los contenidos cuando se utilizan chatbots. Estas recomendaciones pretenden informar a los editores y ayudarles a desarrollar políticas para el uso de chatbots en los artículos sometidos en sus revistas. Su objetivo es ayudar a autores y revisores a entender cuál es la mejor manera de atribuir el uso de chatbots en su trabajo y a la necesidad de que todos los editores de revistas tengan acceso a herramientas de selección de manuscritos. En este campo en rápida evolución, seguiremos modificando estas recomendaciones a medida que se desarrollen el software y sus aplicaciones.

An examination of retracted articles in nursing literature.

INTRODUCTION: The output of scholarly publications in scientific literature has increased exponentially in recent years. This increase in literature has been accompanied by an increase in retractions. Although some of these may be attributed to publishing errors, many are the result of unsavory research practices. The purposes of this study were to identify the number of retracted articles in nursing and reasons for the retractions, analyze the retraction notices, and determine the length of time for an article in nursing to be retracted. DESIGN: This was an exploratory study. METHODS: A search of PubMed/MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, and Retraction Watch databases was conducted to identify retracted articles in nursing and their retraction notices. RESULTS: Between 1997 and 2022, 123 articles published in the nursing literature were retracted. Ten different reasons for retraction were used to categorize these articles with one-third of the retractions (n = 37, 30.1%) not specifying a reason. Sixty-eight percent (n = 77) were retracted because of an actual or a potential ethical concern: duplicate publication, data issues, plagiarism, authorship issues, and copyright. CONCLUSION: Nurses rely on nursing-specific scholarly literature as evidence for clinical decisions. The findings demonstrated that retractions are increasing within published nursing literature. In addition, it was evident that retraction notices do not prevent previously published work from being cited. This study addressed a gap in knowledge about article retractions specific to nursing.

Comparisons of Quality, Correctness, and Similarity Between ChatGPT-Generated and Human-Written Abstracts for Basic Research: Cross-Sectional Study.

BACKGROUND: ChatGPT may act as a research assistant to help organize the direction of thinking and summarize research findings. However, few studies have examined the quality, similarity (abstracts being similar to the original one), and accuracy of the abstracts generated by ChatGPT when researchers provide full-text basic research papers. OBJECTIVE: We aimed to assess the applicability of an artificial intelligence (AI) model in generating abstracts for basic preclinical research. METHODS: We selected 30 basic research papers from Nature, Genome Biology, and Biological Psychiatry. Excluding abstracts, we inputted the full text into ChatPDF, an application of a language model based on ChatGPT, and we prompted it to generate abstracts with the same style as used in the original papers. A total of 8 experts were invited to evaluate the quality of these abstracts (based on a Likert scale of 0-10) and identify which abstracts were generated by ChatPDF, using a blind approach. These abstracts were also evaluated for their similarity to the original abstracts and the accuracy of the AI content. RESULTS: The quality of ChatGPT-generated abstracts was lower than that of the actual abstracts (10-point Likert scale: mean 4.72, SD 2.09 vs mean 8.09, SD 1.03; P<.001). The difference in quality was significant in the unstructured format (mean difference -4.33; 95% CI -4.79 to -3.86; P<.001) but minimal in the 4-subheading structured format (mean difference -2.33; 95% CI -2.79 to -1.86). Among the 30 ChatGPT-generated abstracts, 3 showed wrong conclusions, and 10 were identified as AI content. The mean percentage of similarity between the original and the generated abstracts was not high (2.10%-4.40%). The blinded reviewers achieved a 93% (224/240) accuracy rate in guessing which abstracts were written using ChatGPT. CONCLUSIONS: Using ChatGPT to generate a scientific abstract may not lead to issues of similarity when using real full texts written by humans. However, the quality of the ChatGPT-generated abstracts was suboptimal, and their accuracy was not 100%.

Plagiarism: A Bird's Eye View.

Plagiarism is among the prevalent misconducts reported in scientific writing and common causes of article retraction in scholarly journals. Plagiarism of idea is not acceptable by any means. However, plagiarism of text is a matter of debate from culture to culture. Herein, I wish to reflect on a bird's eye view of plagiarism, particularly plagiarism of text, in scientific writing. Text similarity score as a signal of text plagiarism is not an appropriate index and an expert should examine the similarity with enough scrutiny. Text recycling in certain instances might be acceptable in scientific writing provided that the authors could correctly construe the text piece they borrowed. With introduction of artificial intelligence-based units, which help authors to write their manuscripts, the incidence of text plagiarism might increase. However, after a while, when a universal artificial unit takes over, no one will need to worry about text plagiarism as the incentive to commit plagiarism will be abolished, I believe.

[Scientific integrity faces plagiarism fabricated with the ChatGPT]. / La integridad científica ante los plagios fabricados con el ChatGPT.

Among the malpractices that undermine research integrity, plagiarism is a major threat given its frequency and evolving presentations. Plagiarism implies the intentional grabbing of texts, ideas, images, or data belonging to others and without crediting them. However, the different and even masked forms of plagiarism often difficult a clear identification. Currently, the many kinds of fraud and plagiarism account for most retractions in traditional and open access journals. Further, the rate of retracted articles is higher in the Latin American databases LILACS and Scielo than in PubMed and Web of Science. This difference has been related to the typical laxity of our culture and the lack of English writing skills of non-Anglophone researchers. These features explain the conflict experienced by Latin American students in USA where they face a stricter culture regarding academic and scientific plagiarism. In the internet era, the ease of accessing scientific literature has increased the temptation to plagiarize but this ethical breach has been countered by antiplagiarism software. Now, the so-called "paraphragiarism" prompted by paraphrasing tools exceeds the infamous "copy-paste". For instance, the innovative ChatGPT can be used for plagiarizing and paraphragiarizing. Moreover, its inclusion as coauthor in scientific papers has been banned by prestigious journals and the International Committee of Medical Journal Editors because such chatbot cannot meet the required public responsibility criterium. To avoid plagiarism, it is enough to always give due credit in the proper way. Lastly, I question the ill-fated and now prevailing conjunction of blind faith in progress and zero skepticism that prevents us from foreseeing the negative consequences of technological advances.

De entre las malas prácticas que socavan la integridad científica destaca el plagio, tanto por su frecuencia como por sus cada vez más evolucionadas presentaciones. Plagiar implica apropiarse intencionalmente de textos, ideas, imágenes o datos ajenos sin dar el crédito debido. Sin embargo, las muchas y, a veces, sutiles maneras de plagiar dificultan identificar esta práctica deshonesta. Los fraudes y plagios explican la mayoría de los artículos retractados en revistas tradicionales y en las de acceso abierto. Además, las retractaciones por plagios en las bases de datos LILACS y SciELO exceden las reportadas en PubMed y Web of Science. Dicha diferencia se atribuye a la permisividad propia de nuestra cultura y a la dificultad para escribir en inglés que los académicos no angloparlantes enfrentamos. Tales peculiaridades explican el conflicto que experimentan los estudiantes latinoamericanos de posgrado en Estados Unidos, país cuya cultura es mucho más estricta en cuestión de plagios académicos y científicos. Al facilitar el acceso a la literatura científica, los avances digitales han propiciado los plagios, pero también el desarrollo de programas para detectar tales apropiaciones. Además del burdo "copiar y pegar", las herramientas para parafrasear han refinado y quizá aumentado el llamado "parafragio". Así, el novedoso ChatGPT puede usarse para plagiar y "parafragiar". Peor aún, la inclusión del ChatGPT como coautor de artículos científicos ha llevado a que el International Committee of Medical Journal Editors y editoriales de prestigio precisen que tal recurso no debe incluirse en la lista de autores. Para evitar el plagio, basta dar siempre el crédito a quien corresponda y apropiadamente. Por último, cuestiono la fe ciega en el progreso y el nulo escepticismo ahora imperantes que nos impiden prever las consecuencias negativas de los avances tecnológicos.

Characteristics of Retracted Publications From Kazakhstan: An Analysis Using the Retraction Watch Database.

BACKGROUND: Retraction is a correction process for the scientific literature that acts as a barrier to the dissemination of articles that have serious faults or misleading data. The purpose of this study was to investigate the characteristics of retracted papers from Kazakhstan. METHODS: Utilizing data from Retraction Watch, this cross-sectional descriptive analysis documented all retracted papers from Kazakhstan without regard to publication dates. The following data were recorded: publication title, DOI number, number of authors, publication date, retraction date, source, publication type, subject category of publication, collaborating country, and retraction reason. Source index status, Scopus citation value, and Altmetric Attention Score were obtained. RESULTS: Following the search, a total of 92 retracted papers were discovered. One duplicate article was excluded, leaving 91 publications for analysis. Most articles were retracted in 2022 (n = 22) and 2018 (n = 19). Among the identified publications, 49 (53.9%) were research articles, 39 (42.9%) were conference papers, 2 (2.2%) were review articles, and 1 (1.1%) was a book chapter. Russia (n = 24) and China (n = 5) were the most collaborative countries in the retracted publications. Fake-biased peer review (n = 38), plagiarism (n = 25), and duplication (n = 14) were the leading causes of retraction. CONCLUSION: The vast majority of the publications were research articles and conference papers. Russia was the leading collaborative country. The most prominent retraction reasons were fake-biased peer review, plagiarism, and duplication. Efforts to raise researchers' understanding of the grounds for retraction and ethical research techniques are required in Kazakhstan.

Overdue Assignment: A Case Study on Academic Writing Development for Postgraduate Health Professional Trainees in Kenya.

OBJECTIVES: Though essential for research capacity building, development of authorial identity for thesis projects and publications has been overlooked in African postgraduate residency programs. This study aims to explore authorial identity among postgraduate health professional trainees at two universities in Kenya. It also evaluated the effect of Age of Acquisition of English on confidence in writing. METHODS: This exploratory case study utilized quantitative and qualitative data. Pre- and post-workshop surveys were generated from learning objectives and evaluated confidence in writing and plagiarism awareness, both important attributes of authorial identity. As confidence in writing might be influenced by the English Age of Acquisition, the questionnaire also included items from the Language Experience and Proficiency Questionnaire. Pre- and post-workshop responses were analyzed using planned comparisons. Focus group discussions further explored authorial identity among participants and were analyzed thematically. RESULTS: A total of 57 postgraduate trainees from nine medical specialties participated in the study. Both confidence in writing and plagiarism awareness improved significantly after the workshop: confidence in writing pre-test (M = 3.20, SD = 0.59) and post-test (M = 3.97, SD = 0.61), t(56) = 6.93, P < .001, d = 0.9; plagiarism awareness pre-test (M = 3.01, SD 0.72) and post-test (M = 3.92, SD 0.65), t(56) = 6,8, P < .001, d = 0.9. The average English Age of Acquisition was 4.98 years and showed no correlation with confidence in writing. Participants recognized that authentic authorship requires hard work and suggested plagiarism is driven by inadequate writing instruction. They proposed that changing perceptions of research and writing could overcome a graduation requirement mindset among trainees. CONCLUSIONS: Interactive workshops using procedural and enculturation approaches may be useful to develop authorial identity among postgraduate health professionals in Kenya. Further research is needed on evaluating workshop effectiveness using direct indicators of learning and other curricular reforms to promote authorship.

Analysis of Retracted Publications in Medical Literature Due to Ethical Violations.

BACKGROUND: Retraction is an essential procedure for correcting scientific literature and informing readers about articles containing significant errors or omissions. Ethical violations are one of the significant triggers of the retraction process. The objective of this study was to evaluate the characteristics of retracted articles in the medical literature due to ethical violations. METHODS: The Retraction Watch Database was utilized for this descriptive study. The 'ethical violations' and 'medicine' options were chosen. The date range was 2010 to 2023. The collected data included the number of authors, the date of publication and retraction, the journal of publication, the indexing status of the journal, the country of the corresponding author, the subject area of the article, and the particular retraction reasons. RESULTS: A total of 177 articles were analyzed. The most retractions were detected in 2019 (n = 29) and 2012 (n = 28). The median time period between the articles' first publication date and the date of retraction was 647 (0-4,295) days. The leading countries were China (n = 47), USA (n = 25), South Korea (n = 23), Iran (n = 14), and India (n = 12). The main causes of retraction were ethical approval issues (n = 65), data-related concerns (n = 51), informed consent issues (n = 45), and fake-biased peer review (n = 30). CONCLUSION: Unethical behavior is one of the most significant obstacles to scientific advancement. Obtaining appropriate ethics committee approvals and informed consent forms is crucial in ensuring the ethical conduct of medical research. It is the responsibility of journal editors to ensure that raw data is controlled and peer review processes are conducted effectively. It is essential to educate young researchers on unethical practices and the negative outcomes that may result from them.

An overview of the capabilities of ChatGPT for medical writing and its implications for academic integrity.

The artificial intelligence (AI) tool ChatGPT, which is based on a large language model (LLM), is gaining popularity in academic institutions, notably in the medical field. This article provides a brief overview of the capabilities of ChatGPT for medical writing and its implications for academic integrity. It provides a list of AI generative tools, common use of AI generative tools for medical writing, and provides a list of AI generative text detection tools. It also provides recommendations for policymakers, information professionals, and medical faculty for the constructive use of AI generative tools and related technology. It also highlights the role of health sciences librarians and educators in protecting students from generating text through ChatGPT in their academic work.

Women Are Underrepresented Among Authors of Retracted Publications: Retrospective Study of 134 Medical Journals.

We examined the gender distribution of authors of retracted articles in 134 medical journals across 10 disciplines, compared it with the gender distribution of authors of all published articles, and found that women were underrepresented among authors of retracted articles, and, in particular, of articles retracted for misconduct.