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Mariano Devoto

Publications and source records attributed to Mariano Devoto.

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Mapping Responsibility Attribution in the Grenfell Tower Inquiry: A Network Analysis

After major disasters, formal inquiries become arenas where responsibility is publicly contested. While extensive research has examined blame attribution through qualitative and actor-centred approaches, the relational structure of blame within formal accountability processes remains poorly understood. Using evidence from the Grenfell Tower Inquiry, this study analyses the web of blame presented during the Phase 2 closing proceedings, in which Counsel to the Inquiry synthesised how core participants publicly attributed responsibility to one another. We represent this synthesis as a directed network and examine its structural properties using standard tools from network analysis. The resulting configuration is interconnected, with pronounced reciprocity and local clustering, indicating that responsibility claims were articulated within a dense institutional environment rather than as isolated, one-to-one accusations. Comparisons with neutral benchmark models show that several observed features depart from expectations based on simple structural constraints alone, revealing patterned organisation in the public articulation of blame within the Inquiry. By applying network-analytic methods to an institutionalised representation of blame attribution, this study provides a systematic structural account of responsibility relations in a major public inquiry. The findings contribute to research on crisis governance and blame avoidance by demonstrating how accountability processes generate patterned distributions of responsibility that reflect institutional arrangements and governance contexts.

physics.soc-ph

Two classes of bipartite networks: nested biological and social systems

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given Contact Preference Rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in great detail, and it is found that the model provides a very good quantitative fitting of its properties. The model also provides a proper qualitative description of the statistical features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

physics.soc-ph

Analysis and Assembling of Network Structure in Mutualistic Systems

It has been observed that mutualistic bipartite networks have a nested structure of interactions. In addition, the degree distributions associated with the two guilds involved in such networks (e.g. plants & pollinators or plants & seed dispersers) approximately follow a truncated power law. We show that nestedness and truncated power law distributions are intimately linked, and that any biological reasons for such truncation are superimposed to finite size effects . We further explore the internal organization of bipartite networks by developing a self-organizing network model (SNM) that reproduces empirical observations of pollination systems of widely different sizes. Since the only inputs to the SNM are numbers of plant and animal species, and their interactions (i.e., no data on local abundance of the interacting species are needed), we suggest that the well-known association between species frequency of interaction and species degree is a consequence rather than a cause, of the observed network structure.

q-bio.PE