This article argues that the formation of a topological structure in the Luso-American postal system from 1800 to 1820 produced a form of spacetime compression: a temporal acceleration in communications achieved by the shrinking of distances and intensification of flows. This acceleration was closely tied to a revolutionary context that heightened the urgency of political communications. In particular, reforms prompted by the Portuguese throne’s migration to America instigated significant changes in postal networks. Drawing on a range of legal and administrative documents, letters, almanacs, and newspapers, the study highlights the expansion, diversification, and regularization of the network. It further underlines the links between communication infrastructure and social experiences of space and time, suggesting that a comprehensive postal network fostered a global experience of accelerated time. Using digital cartography alongside other sources, the article contends that the spatial dimension of modern accelerated temporality is rooted in topological space.

This article challenges the traditional view of the linear causality of technological globalization in the history of modern predictive meteorology. According to this linear narrative, telegraphy, by enabling near-instantaneous communication over vast distances, was the causa efficiens that directly and inevitably produced large-scale weather forecasting. However, the role of Jesuit scientists in East Asia as pioneers of cyclone warning systems not only demonstrates that the linear narrative is too simple but invites a rigorous examination of the relationships between prior knowledge networks and technological infrastructures. This article contends that the expansion of technological networks does not inexorably imply the expansion of knowledge networks. There was not, therefore, a unidirectional causal relationship but a concomitant two-way interaction; that is, there was a coextension of knowledge and technological networks, where both Jesuit scientists and telegraph companies benefited from each other and shared common goals confronting a global threat—cyclones. This offers a new perspective not only on the history of meteorological services but also of science globalization.

Partisan preferences usually stand out as the major driving force behind voters' expectations about election outcomes. Apart from partisan preferences, however, purely individual‐level factors appear to be only weakly associated with forecasting ability. Some studies argue that we need to move from the strictly personal sphere to the interpersonal one to better understand the underpinnings of individuals' forecasting ability. This paper leverages data from 77 elections at the district, municipal, regional, and/or national levels in 10 different countries to assess the impact of social networks and social interactions on the accuracy of citizens' electoral expectations. The results cast doubt on the capacity of social interactions to influence citizens' forecasting skills.

The FIND Integrated Biobank (FIB) network was established to address long-standing barriers in translational research, diagnostic development, and pandemic preparedness, particularly in low- and middle-income countries (LMICs). This article presents the FIB network as an innovative, contract-based model for equitable biobanking partnerships that support rapid, quality-assured access to clinical biospecimens for translational research and diagnostic evaluations. The FIB model offers a replicable and scalable approach to global diagnostic research and preparedness, anchored in equitable, legally binding partnerships. It advances the goals of the WHO Pandemic Agreement and provides a practical pathway for integrating LMIC institutions into global translational research ecosystems.

This paper aims to study the characteristics of the Social Impact Investment (SII) market in the absence of its enablers. After the first SII convention in 2007, SII practices have been diffusing especially in the Anglo-Saxon countries, which are often referred to as the pioneers in this field. In these countries, SII markets are small but rather advanced in comparison with the rest of the world, and some remarkable cases, such as the launch of the first social impact bond or the establishment of impact funds, have been taken as a reference model worldwide. The final result is an Anglo-Saxon paradigm for SII, which inspires the debate in other countries. The term “paradigm” refers to the presence of some factors that helped the development of the SII market, such as the commitment of highly capitalized foundations, the birth of specialized intermediaries and the endorsement of the state. However, the extent to which the absence of these facilitating factors prevent the SII diffusion or if an alternative to the Anglo-Saxon paradigm can exist is still a question, at the base of this paper. Thus, the objective of this research is to analyse who can play a role in the SII development and how players organize in such circumstances. The study looks at the Italian scenery, through the lens of the network theory. Results show that organizations do not renounce to SII and can play several roles to catalyse the market, using different collaborative configurations.

The purpose of this paper is to demonstrate and explain how a Norwegian voluntary, faith-based organization—the Gospel Centre of Norway (Pinsevennenes Evangeliesenter)—successfully substituted a “network” for “market” strategy vis-à-vis the public sector in order to obtain organizational legitimacy and financial security. During the first decade of its existence it obtained a unique position in its relationship with the state, as a separate item in the budget of the Ministry of Health and Social Affairs. The organization operates in the field of substance abuse rehabilitation, i.e., in a situation where instrumental effectiveness is difficult to assess. In such a situation ritual or other institutional criteria may replace effectiveness criteria and impression management is shown to be a successful strategy. Attention is paid to the relevant environmental conditions under which this organizational change of strategy was successful.

Health Technology Assessment (HTA) informs resource allocation and policy decisions, particularly to achieve Universal Health Coverage (UHC). Recognizing the increasing demand for evidence-informed decision-making, the HTAsiaLink network was established in 2011 as a regional platform to strengthen individual and institutional capacity in HTA research and facilitate the integration of HTA evidence into policy decisions across the Asia-Pacific.

Over the years, HTAsiaLink has expanded to over fifty members from twenty economies. In 2024, a structured strategic planning process was undertaken to ensure its continued growth and strengthen its impact on HTA development and implementation. This process involved a targeted review of strategic plans from international networks, alongside comprehensive member engagement, to develop a data-driven and adaptable plan responsive to the evolving healthcare landscape and member needs. As a result, five strategic priorities, corresponding action items, and success indicators were identified.

This commentary outlines the needs and processes involved in developing the network’s first-ever strategic plan, emphasizing the critical role of member engagement in shaping its future direction. We believe that this experience offers transferable insights for other HTA networks, particularly those operating in low- and middle-income country contexts, on the collaborative development of strategic plans that are responsive to shared objectives, accommodate varying institutional capacities, and align with regional priorities.

Many empirical systems contain complex interactions of arbitrary size, representing, for example, chemical reactions, social groups, co-authorship relationships, and ecological dependencies. These interactions are known as higher-order interactions, and the collection of these interactions comprise a higher-order network, or hypergraph. Hypergraphs have established themselves as a popular and versatile mathematical representation of such systems, and a number of software packages written in various programming languages have been designed to analyze these networks. However, the ecosystem of higher-order network analysis software is fragmented due to specialization of each software’s programming interface and compatible data representations. To enable seamless data exchange between higher-order network analysis software packages, we introduce the Hypergraph Interchange Format (HIF), a standardized format for storing higher-order network data. HIF supports multiple types of higher-order networks, including undirected hypergraphs, directed hypergraphs, and abstract simplicial complexes, while actively exploring extensions to represent multiplex hypergraphs, temporal hypergraphs, and ordered hypergraphs. To accommodate the wide variety of metadata used in different contexts, HIF also includes support for attributes associated with nodes, edges, and incidences. This initiative is a collaborative effort involving authors, maintainers, and contributors from prominent hypergraph software packages. This project introduces a JSON schema with corresponding documentation and unit tests, example HIF-compliant datasets, and tutorials demonstrating the use of HIF with several popular higher-order network analysis software packages.

Political ideology has regained prominence in political science and psychology. On the one hand, most of the literature recognizes that ideology is not characterized by a single dimension. On the other hand, recent scholarship has returned to Converse's classic conceptualization of ideology as a belief system: a network of interconnected political beliefs. Using survey data collected after the 2022 Italian general elections, I examine the dimensionality of political attitudes and compare latent and network conceptualizations. Results confirm that Italian political attitudes are bidimensional, and that a partial correlation network model captures their structure very well. I then apply Correlational Class Analysis to identify three distinct belief system types. Political orientations (left-right self-placement and vote) emerge as the strongest individual-level predictors of class membership. I explain these findings through an extension of Converse's theory: while he argued that belief systems primarily vary in tightness (internal consistency), I show that conflicting partisan cues might foster low belief consensus: disagreement over which attitudes should be held together.