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The online sourcing, supply, and purchase of illicit drugs is fast transforming drug markets worldwide. Although the long-term development of simple communications technology over time (from pagers to mobile phones) continues to impact and extend local drug supply dynamics, it is the recent developments of dark web cryptomarkets, social media applications (like Instagram), encrypted messaging applications (like WhatsApp), and surface web platforms, such as LeafedOut, that are changing the drug supply landscape online. The use of technology in drug supply has tended to go hand in hand with improving the efficiency of supply and opportunities to reduce exchange-related risks for both buyers and sellers. In relation to app-mediated supply, for example, the use of encrypted messaging provides enhanced security for arranging purchases beyond the lurking surveillance of law enforcement. Despite the perception of improved safety, however, the use of social media apps and other online platforms can expose both buyers and sellers to risk scenarios they may not fully appreciate. Drawing on two recent studies on the use of social media apps and the online platform LeafedOut as mediators of drugs supply, this chapter will consider how these mid-range (between cryptomarkets and traditional telecommunications such as basic texting/calling and material ‘street’ markets) virtual spaces are being utilised for drug supply and the extent to which this is ‘just more of the same’ or provides new structures and experiences for those engaging with it and in what ways. Consideration will also be given to contradictions in the mid-range market space where the broad perception of reduced risk from the use of encrypted messaging can in fact produce greater levels of risk for some buyers and sellers depending on how they engage with the process/es.

Collegiality is often discussed and analyzed as a challenged form of governance, a form of working that used to function well in universities prior to the emergence of contemporary and modern forms of governance. This seems to suggest that collegiality used to dominate, while other forms of governance are now taking over. The papers in volume 86 of this special issue support the notion of challenged collegiality, but also show that for the most part, nostalgic notions of “the good old days” are neither true nor helpful if we are to revitalize academic collegiality. After examining whether a golden age of collegiality ever existed, we discuss why collegiality matters. Exploring what are often described as limitations or “dark sides” of collegiality, we address four such “dark sides” related to slow decision-making, conflicts, parochialism, and diversity. This is followed by a discussion of how these limitations may be handled and what measures must be taken to maintain and develop collegiality. With a brief summary of the remaining papers under two headings, “Maintaining collegiality” and “Revitalizing collegiality,” we preview the rest of this volume.

Large-scale data analytics have raised a number of ethical concerns. Many of these were introduced in a seminal paper by boyd and Crawford and have been developed since by others (boyd & Crawford, 2012; Lagoze, 2014; Martin, 2015; Mittelstadt, Allo, Taddeo, Wachter, & Floridi, 2016). One such concern which is frequently recognised but under-analysed is the focus on correlation of data rather than on the causative relationship between data and results. Advocates of this approach dismiss the need for an understanding of causation, holding instead that the correlation of data is sufficient to meet our needs. In crude terms, this position holds that we no longer need to know why X+Y=Z. Merely acknowledging that the pattern exists is enough.

In this chapter, the author explores the ethical implications and challenges surrounding a focus on correlation over causation. In particular, the author focusses on questions of legitimacy of data collection, the embedding of persistent bias, and the implications of future predictions. Such concerns are vital for understanding the ethical implications of, for example, the collection and use of ‘big data’ or the covert access to ‘secondary’ information ostensibly ‘publicly available’. The author’s conclusion is that by failing to consider causation, the short-term benefits of speed and cost may be countered by ethically problematic scenarios in both the short and long term.

Although management scholars have embraced grand challenges research, in many cases, grand challenges have been treated as merely a context for exploring extant theoretical perspectives. By comparison, our approach – robust action – provides a novel theoretical framework for tackling grand challenges. In this invited article, we revisit our 2015 model, clarifying and elaborating its key elements and taking stock of subsequent developments. We then identify three promising directions for future research: scaffolding, future imaginaries, and distributed actorhood. Ultimately, our core message is remarkably simple: robust action strategies – participatory architecture, multivocal inscription and distributed experimentation – jointly provide a means for tackling grand challenges that is well matched to their complexities, uncertainties, and evaluativities.

The received wisdom underlying many guides to ethical research is that information is private, and research is consequently seen as a trespass on the private sphere. Privacy demands control; control requires consent; consent protects privacy. This is not wrong in every case, but it is over-generalised. The distorted perspective leads to some striking misinterpretations of the rights of research participants, and the duties of researchers. Privacy is not the same thing as data protection; consent is not adequate as a defence of privacy; seeking consent is not always required or appropriate. Beyond that, the misinterpretation can lead to conduct which is unethical, limiting the scope of research activity, obstructing the flow of information in a free society, and failing to recognise what researchers’ real duties are.