This article develops a Digital Capital Index by adopting the definition provided by Ragnedda, who defines Digital Capital as the accumulation of digital competencies and digital technologies, and the model for measuring it developed by Ragnedda and Ruiu. It aims to develop a measure that can be replicated for comparison in different contexts. This article contributes both theoretically and empirically to the literature by (a) consolidating the concept of Digital Capital as a specific capital and (b) empirically measuring it. A Digital Capital Index is developed through an exploratory factor analysis (EFA) and validated with a representative sample survey of 868 UK citizens. The validation procedure shows that the Digital Capital Index is associated with socioeconomic and sociodemographic patterns, such as age, income, educational level and place of residence, while it appears not to be related to gender.

In this article, we argue that new kinds of risk are emerging with the COVID-19 virus, and that these risks are unequally distributed. As we expose to view, digital inequalities and social inequalities are rendering certain subgroups significantly more vulnerable to exposure to COVID-19. Vulnerable populations bearing disproportionate risks include the social isolated, older adults, penal system subjects, digitally disadvantaged students, gig workers, and last-mile workers. Therefore, we map out the intersection between COVID-19 risk factors and digital inequalities on each of these populations in order to examine how the digitally resourced have additional tools to mitigate some of the risks associated with the pandemic. We shed light on how the ongoing pandemic is deepening key axes of social differentiation, which were previously occluded from view. These newly manifested forms of social differentiation can be conceived along several related dimensions. At their most general and abstract, these risks have to do with the capacity individuals have to control the risk of pathogen exposure. In order to fully manage exposure risk, individuals must control their physical environment to the greatest extent possible in order to prevent contact with potentially compromised physical spaces. In addition, they must control their social interactional environment to the greatest extent possible in order to minimize their contacts with potentially infected individuals. All else equal, those individuals who exercise more control over their exposure risk — on the basis of their control over their physical and social interactional environments — stand a better chance of staying healthy than those individuals who cannot manage exposure risk. Individuals therefore vary in terms of what we call their COVID-19 exposure risk profile (CERPs). CERPs hinge on preexisting forms of social differentiation such as socioeconomic status, as individuals with more economic resources at their disposal can better insulate themselves from exposure risk. Alongside socioeconomic status, one of the key forms of social differentiation connected with CERPs is digital (dis)advantage. Ceteris paribus, individuals who can more effectively digitize key parts of their lives enjoy better CERPs than individuals who cannot digitize these life realms. Therefore we believe that digital inequalities are directly and increasingly related to both life-or-death exposure to COVID-19, as well as excess deaths attributable to the larger conditions generated by the pandemic.

This paper has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Mismanagement of 2019-nCoV. Lessons learned from ItalyThis paper analyses the first phases of the 2019-nCoV outbreak management in Italy by exploring the combination of political, scientific, media and public responses. A fragmented communication between national and local governments, the presence of mixed scientific voices, a lack of coordination between political and scientific levels and between institutional claim-makers and the media suggest a mismanagement of the crisis during the first phases of the outbreak. The outbreak management suffered from the five communication weaknesses identified by Reynolds ( 2005), related to i) mixed messages from multiple messengers; ii) delay in releasing information; iii) paternalistic attitudes; iv) not responding to rumours in real time; and v) political confusion. This suggests that the communication of uncertainty around an unknown threat should be accompanied by both political and scientific cohesion. However, both political and scientific dysfunctions caused the failure of several government efforts to contain the outbreak. This paper contributes towards informing policymakers on the lessons learned from the management of the 2019-nCoV in one of the most affected countries in the world. The Italian case study offers the opportunity for other countries to improve the management of the outbreak by limiting the spread of both chaos and panic.

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On the basis of the literature (produced mainly by sociologists, architects, and geographers) about gated and cohousing communities, this work analyzes how these communities differ from each other. The analysis suggests that cohousing and gated communities are different in the nature of relationships between residents and in the reasons why they arise, even if there are some points of similarity. The risk of a degeneration of cohousing in the gated type is linked in particular with a complete transformation of the grass-roots model (typical of cohousing) to the top-down speculative scheme (typical of gated communities).