A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.'s case

Retracted publications in autism research are mostly concerned with ethical misconduct

BACKGROUND

As the prevalence of autism appears to increase, more research to guide effective diagnosis and intervention practices is needed. Findings disseminated through peer-reviewed publications are critical, but the number of retractions continues to rise. An understanding of retracted publications is imperative to ensure the body of evidence is corrected and current.

OBJECTIVES

The objectives of this analysis were to summarize key characteristics of retracted publications in autism research, examine the length of time between publication and retraction, and assess the extent journals are adhering to publishing ethical guidelines for reporting retracted articles.

METHODS

We searched five databases through 2021 (PubMed, EMBASE, Scopus, Web of Science, and Retraction Watch).

RESULTS

A total of 25 retracted articles were included in the analysis. Ethical misconduct accounted for the majority of retractions rather than scientific error. The shortest time to retraction was 2 months and the longest length was 144 months.

DISCUSSION

The time lag between publication and retraction since 2018 has improved considerably. Nineteen of the articles had retraction notices (76%), whereas six articles did not have a notice (24%).

CONCLUSION

These findings summarize errors of previous retractions and illuminate opportunities for researchers, journal publishers and librarians to learn from retracted publications.

Impact of COVID-19 research: a study on predicting influential scholarly documents using machine learning and a domain-independent knowledge graph

Multiple studies have investigated bibliometric features and uncategorized scholarly documents for the influential scholarly document prediction task. In this paper, we describe our work that attempts to go beyond bibliometric metadata to predict influential scholarly documents. Furthermore, this work also examines the influential scholarly document prediction task over categorized scholarly documents. We also introduce a new approach to enhance the document representation method with a domain-independent knowledge graph to find the influential scholarly document using categorized scholarly content. As the input collection, we use the WHO corpus with scholarly documents on the theme of COVID-19. This study examines different document representation methods for machine learning, including TF-IDF, BOW, and embedding-based language models (BERT). The TF-IDF document representation method works better than others. From various machine learning methods tested, logistic regression outperformed the other for scholarly document category classification, and the random forest algorithm obtained the best results for influential scholarly document prediction, with the help of a domain-independent knowledge graph, specifically DBpedia, to enhance the document representation method for predicting influential scholarly documents with categorical scholarly content. In this case, our study combines state-of-the-art machine learning methods with the BOW document representation method. We also enhance the BOW document representation with the direct type (RDF type) and unqualified relation from DBpedia. From this experiment, we did not find any impact of the enhanced document representation for the scholarly document category classification. We found an effect in the influential scholarly document prediction with categorical data.

An analysis of retracted papers in Computer Science

CONTEXT

The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent.

OBJECTIVE

The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact upon systematic reviews and mapping studies.

METHOD

We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar.

RESULTS

We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., ≈ 8%. For CS, 56% of retracted papers provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also some disparity between different publishers, a tendency for multiple versions of a retracted paper to be available beyond the Version of Record (VoR), and for new citations long after a paper is officially retracted (median = 3; maximum = 18). Systematic reviews are also impacted with ≈ 30% of the retracted papers having one or more citations from a review.

CONCLUSIONS

Unfortunately, retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies.

Reducing the Inadvertent Spread of Retracted Science: recommendations from the RISRS report

BACKGROUND

Retraction is a mechanism for alerting readers to unreliable material and other problems in the published scientific and scholarly record. Retracted publications generally remain visible and searchable, but the intention of retraction is to mark them as "removed" from the citable record of scholarship. However, in practice, some retracted articles continue to be treated by researchers and the public as valid content as they are often unaware of the retraction. Research over the past decade has identified a number of factors contributing to the unintentional spread of retracted research. The goal of the Reducing the Inadvertent Spread of Retracted Science: Shaping a Research and Implementation Agenda (RISRS) project was to develop an actionable agenda for reducing the inadvertent spread of retracted science. This included identifying how retraction status could be more thoroughly disseminated, and determining what actions are feasible and relevant for particular stakeholders who play a role in the distribution of knowledge.

METHODS

These recommendations were developed as part of a year-long process that included a scoping review of empirical literature and successive rounds of stakeholder consultation, culminating in a three-part online workshop that brought together a diverse body of 65 stakeholders in October-November 2020 to engage in collaborative problem solving and dialogue. Stakeholders held roles such as publishers, editors, researchers, librarians, standards developers, funding program officers, and technologists and worked for institutions such as universities, governmental agencies, funding organizations, publishing houses, libraries, standards organizations, and technology providers. Workshop discussions were seeded by materials derived from stakeholder interviews (N = 47) and short original discussion pieces contributed by stakeholders. The online workshop resulted in a set of recommendations to address the complexities of retracted research throughout the scholarly communications ecosystem.

RESULTS

The RISRS recommendations are: (1) Develop a systematic cross-industry approach to ensure the public availability of consistent, standardized, interoperable, and timely information about retractions; (2) Recommend a taxonomy of retraction categories/classifications and corresponding retraction metadata that can be adopted by all stakeholders; (3) Develop best practices for coordinating the retraction process to enable timely, fair, unbiased outcomes; and (4) Educate stakeholders about pre- and post-publication stewardship, including retraction and correction of the scholarly record.

CONCLUSIONS

Our stakeholder engagement study led to 4 recommendations to address inadvertent citation of retracted research, and formation of a working group to develop the Communication of Retractions, Removals, and Expressions of Concern (CORREC) Recommended Practice. Further work will be needed to determine how well retractions are currently documented, how retraction of code and datasets impacts related publications, and to identify if retraction metadata (fails to) propagate. Outcomes of all this work should lead to ensuring retracted papers are never cited without awareness of the retraction, and that, in public fora outside of science, retracted papers are not treated as valid scientific outputs.

Greenwashed word of mouth (GWWOM): a vibrant influence on customer green behaviour

Purpose

The purpose of this study is to examine the role of greenwashed word of mouth (GWWOM) originating from trickery and misleading green marketing practices on customer behavior. The outcomes of this study are expected to contribute in the domain of responsible green marketing. The significance of this study lies in its ability to provide useful recommendations to marketers, policymakers and customers toward accomplishment of sustainable development goals through usage and adoption of environment-friendly products.

Design/methodology/approach

This study is primarily descriptive in nature, as it attempted to investigate the implications of customers' reactions toward greenwashed practices prevailing in the fast-moving consumer goods (FMCG) market. The information gathered through a self-administered online questionnaire was analyzed using Smart PLS software package to verify the proposed hypotheses. The consistency and validity of the measurement and structural models proposed were tested using inferential statistical procedures.

Findings

The results significantly confirmed the mediating role of GWWOM in shaping the relationship between green skepticism and shift in green behavior. It was verified from the results that customers’ futuristic behavioral patterns toward green products are negatively influenced by misleading and false claims of marketers through GWWOM communications.

Practical implications

The primary implications of this study are for marketers in understanding the role of GWWOM on organizations’ reputation. The policymakers may contribute by implementing appropriate changes in regulations to control greenwashed practices. Finally, customers may become more aware about the unethical marketing practices and act responsibly in the market place.

Originality/value

This study revealed an intriguing finding in the sense that customers, who feel cheated by erroneous and mislead green claims of the marketers, are expected to communicate their experiences through variety of channels. Therefore, it is very likely that they may influence others to change their behaviors while going for environmentally safe products and may have significant consequences on the sustainable consumer behavior.