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The "controversy over the Yanomami" has affected central issues, both epistemological and ethical and political, for the discipline and practice of anthropology, particularly concerning the ethics of field research; the way to use research data to support certain theoretical hypotheses; the relationships between popularization and politicization of research and, more generally, the responsibility of anthropologists with respect to both the uses of their studies in the public sphere and towards the human subjects with whom they work. In this article, I examine some key moments of the "controversy". In particular, I try to reconstruct the way in which the image of the Yanomami as the "last primitive society" was initially consolidated, inside and outside anthropology, and, in this sense, I compare the ethnographies of Chagnon and Lizot. In the paper, I also place particular emphasis on the different ways in which ethnographers have textually marked their positioning in the field as "proof" of the "authenticity" of their representations of the Yanomami world. In the last part, I summarize the effects of the "media storm" on American anthropology, which were caused by the accusations of ethically inappropriate, if not completely execrable, behavior addressed to Chagnon and Lizot in Darkness in El Dorado, the book-report by journalist Patrick Tierney.

In this paper I propose a critical examination of the ways in which the intersections between violence, suffering and domination in some of the main new directions of the anthropological study of the relationships between humans and other animals, notably Ingold's approach, Descola's theory of "schemas of the practice", and multispecies ethnography. Apparently, and despite the emphasis given to the sentience and forms of agency of non-human animals, as well as to their being active coparticipants, together with humans, in the construction of social networks and the habitats that bind both, these intersections do not occupy a prominent place in these approaches, both from the point of view of their theoretical framework and from that of the ethnographic descriptions. The elusive place that the intersections between violence, suffering and domination occupies in contemporary approaches to humans/ other animals relationships has an important consequence in the the lack of a mutually constructive confrontation with animal advocacy's movements and with the ethical and political theories to which these movements are inspired. It seems desirable and urgent to consider today the issues of suffering and violence inflicted on non-human animals assuming a careful listening posture at positions other than one's own. Such pluralism, to be adopted both on the level of scientific debate and on that of dialogue between different ethical options, is pointed to by some important proposals developed both in other fields of contemporary anthropology and in the reflection on future prospects for the development of an "ecological justice"

AbstractCritical infrastructures are increasingly reliant on information and communications technology (ICT) for more efficient operations, which, at the same time, exposes them to cyber threats. As the frequency and severity of cyberattacks are increasing, so are the costs of critical infrastructure security. Efficient allocation of resources is thus a crucial issue for cybersecurity. A common practice in managing cyber threats is to conduct a qualitative analysis of individual attack scenarios through risk matrices, prioritizing the scenarios according to their perceived urgency and addressing them in order until all the resources available for cybersecurity are spent. Apart from methodological caveats, this approach may lead to suboptimal resource allocations, given that potential synergies between different attack scenarios and among available security measures are not taken into consideration. To overcome this shortcoming, we propose a quantitative framework that features: (1) a more holistic picture of the cybersecurity landscape, represented as a Bayesian network (BN) that encompasses multiple attack scenarios and thus allows for a better appreciation of vulnerabilities; and (2) a multiobjective optimization model built on top of the said BN that explicitly represents multiple dimensions of the potential impacts of successful cyberattacks. Our framework adopts a broader perspective than the standard cost–benefit analysis and allows the formulation of more nuanced security objectives. We also propose a computationally efficient algorithm that identifies the set of Pareto–optimal portfolios of security measures that simultaneously minimize various types of expected cyberattack impacts, while satisfying budgetary and other constraints. We illustrate our framework with a case study of electric power grids.

| openaire: EC/H2020/740920/EU//CYBECO Funding Information: The research was partly developed in the Young Scientists Summer Program at the International Institute for Applied Systems Analysis, Laxenburg (Austria) with financial support from the Academy of Finland. The research was partly supported by the European Union's Horizon 2020 Project 740920 CYBECO. Publisher Copyright: © 2022 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis ; Critical infrastructures are increasingly reliant on information and communications technology (ICT) for more efficient operations, which, at the same time, exposes them to cyber threats. As the frequency and severity of cyberattacks are increasing, so are the costs of critical infrastructure security. Efficient allocation of resources is thus a crucial issue for cybersecurity. A common practice in managing cyber threats is to conduct a qualitative analysis of individual attack scenarios through risk matrices, prioritizing the scenarios according to their perceived urgency and addressing them in order until all the resources available for cybersecurity are spent. Apart from methodological caveats, this approach may lead to suboptimal resource allocations, given that potential synergies between different attack scenarios and among available security measures are not taken into consideration. To overcome this shortcoming, we propose a quantitative framework that features: (1) a more holistic picture of the cybersecurity landscape, represented as a Bayesian network (BN) that encompasses multiple attack scenarios and thus allows for a better appreciation of vulnerabilities; and (2) a multiobjective optimization model built on top of the said BN that explicitly represents multiple dimensions of the potential impacts of successful cyberattacks. Our framework adopts a broader perspective than the standard cost–benefit analysis and allows the formulation of more nuanced security objectives. We also propose a computationally efficient algorithm that identifies the set of Pareto–optimal portfolios of security measures that simultaneously minimize various types of expected cyberattack impacts, while satisfying budgetary and other constraints. We illustrate our framework with a case study of electric power grids. ; Peer reviewed