Science Means Never Having to Say You’re Sorry? Apologies for Scientific Misconduct

Retractions of journal articles exclude fraudulent or erroneous research from legitimate science and perform boundary work. Analyzing retractions from different disciplines and focusing on their apologetic aspects, we find that these apologies shift between openly addressing emotional, normative, and social themes and concealing them in a more scientific style of communication. Their boundary work remains highly ambivalent: They alternate between scientific and nonscientific forms of speaking, portray unstable patterns of control and coercion, and avoid drawing a boundary between legitimate and nonlegitimate science. In line with the hypothetical nature of scientific knowledge, retractions thus leave boundary making to the future.Bundesministerium für Bildung und Forschung https://doi.org/10.13039/501100002347Peer Reviewe

ReTracker: Actively and Automatically Matching Retraction Metadata in Zotero

Retraction removes seriously flawed papers from the scientific literature. However, even papers retracted for scientific fraud continue to be cited and used as valid after their retraction. Retracted papers are inadequately identified on publisher pages and in scholarly databases, and scholars’ personal libraries frequently contain retracted papers. To address this, we are developing a tool called ReTracker (https://github.com/nikolausn/ReTrackers) that automatically checks a user’s Zotero library for retracted articles, and adds retraction status as a new metadata field directly in the library. In this paper, we present the current version of ReTracker, which automatically flags retracted articles from PubMed. We describe how we have iteratively improved ReTracker’s matching performance through its initial two versions. Our tests show that the current version of ReTracker is able to flag retracted articles from PubMed with high precision and recall, and to distinguish retracted articles from articles about retraction. In its current state, ReTracker can actively and automatically bring retraction metadata into Zotero, and in future work we will test its usability with scholars.Ope

What difference might retractions make? An estimate of the potential epistemic cost of retractions on meta-analyses

The extent to which a retraction might require revising previous scientific estimates and beliefs – which we define as the epistemic cost – is unknown. We collected a sample of 229 meta-analyses published between 2013 and 2016 that had cited a retracted study, assessed whether this study was included in the meta-analytic estimate and, if so, re-calculated the summary effect size without it. The majority (68% of N = 229) of retractions had occurred at least one year prior to the publication of the citing meta-analysis. In 53% of these avoidable citations, the retracted study was cited as a candidate for inclusion, and only in 34% of these meta-analyses (13% of total) the study was explicitly excluded because it had been retracted. Meta-analyses that included retracted studies were published in journals with significantly lower impact factor. Summary estimates without the retracted study were lower than the original if the retraction was due to issues with data or results and higher otherwise, but the effect was small. We conclude that meta-analyses have a problematically high probability of citing retracted articles and of including them in their pooled summaries, but the overall epistemic cost is contained

A multi-disciplinary perspective on emergent and future innovations in peer review [version 2; referees: 2 approved]

Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments