Charting an intent driven network

The current strong divide between applications and the network control plane is desirable for many reasons; but a downside is that the network is kept in the dark regarding the ultimate purposes and intentions of applications and, as a result, is unable to optimize for these. An alternative approach, explored in this paper, is for applications to declare to the network their abstract intents and assumptions; e.g. "this is a Tweet", or "this application will run within a local domain". Such an enriched semantic has the potential to enable the network better to fulfill application intent, while also helping optimize network resource usage across applications. We refer to this approach as 'intent driven networking' (IDN), and we sketch an incrementally-deployable design to serve as a stepping stone towards a practical realization of the IDN concept within today's Internet

Impact Investing: a primer for family offices

The goal of this report is to help family offices ask the right questions as they contemplate their path into impact investing. It is important to recognize that impact investing may not suit all investors. There will be family offices which conclude impact investing is not appropriate at this stage for them. While we are passionate about the potential of impact investing, we acknowledge the best future for the sector is where each investor can make informed choices about their own best interest. Each investor and investment institution needs to evaluate if impact investing fits with its needs, interests and unique context. It is with that in mind that we offer this report as a resource and tool that family offices can use to begin the conversations internally, to craft and design their own engagement strategy on impact investing with family members, advisers and potential investees, as well as to ensure that not only is their wealth growing in value, but also that their wealth can reflect their values

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks

Despite the basic premise that next-generation wireless networks (e.g., 6G) will be artificial intelligence (AI)-native, to date, most existing efforts remain either qualitative or incremental extensions to existing ``AI for wireless'' paradigms. Indeed, creating AI-native wireless networks faces significant technical challenges due to the limitations of data-driven, training-intensive AI. These limitations include the black-box nature of the AI models, their curve-fitting nature, which can limit their ability to reason and adapt, their reliance on large amounts of training data, and the energy inefficiency of large neural networks. In response to these limitations, this article presents a comprehensive, forward-looking vision that addresses these shortcomings by introducing a novel framework for building AI-native wireless networks; grounded in the emerging field of causal reasoning. Causal reasoning, founded on causal discovery, causal representation learning, and causal inference, can help build explainable, reasoning-aware, and sustainable wireless networks. Towards fulfilling this vision, we first highlight several wireless networking challenges that can be addressed by causal discovery and representation, including ultra-reliable beamforming for terahertz (THz) systems, near-accurate physical twin modeling for digital twins, training data augmentation, and semantic communication. We showcase how incorporating causal discovery can assist in achieving dynamic adaptability, resilience, and cognition in addressing these challenges. Furthermore, we outline potential frameworks that leverage causal inference to achieve the overarching objectives of future-generation networks, including intent management, dynamic adaptability, human-level cognition, reasoning, and the critical element of time sensitivity

Energizing entrepreneurs: Resourceful communities and economic pathways

INTRODUCTION This paper illustrates the relevance for the non-profit sector of moving beyond its traditional roles into entrepreneurial community economic development. Its approach aligns with conceptualizations of sustainability through the self-help galvanization and development of enterprise opportunities, education pathways, and labour market outcomes for the community, by the community. METHOD It develops the concept of social entrepreneurship as a hybrid form between private, non-profit, and public sectors, in line with examples of non-profit organizations with entrepreneurial offshoots, generating revenue for the organization’s social objectives. ANALYSIS The article operationalizes these ideas through the design, creation, roll-out, and achievement of a community enterprise incubation program for urban Polynesians in Aotearoa/New Zealand. It examines the challenges, how they were resolved, and analyzes how both challenges and reforms contribution to the body of knowledge. RESULTS Through the project’s demonstrable initial successes, the authors argue that it offers clear signposts to government, the public sector, and the private sector in how to move beyond simple capacity building to sustainable enterprises and by entrepreneurs in the community who have been created, energized, and given experience by participation in the process. They present the project as a prototype on how to resource community groups and organizations embarking on their community economic development journeys and how to liberate the self-motivating entrepreneurial energies of communities

Digitalisation of Development and Supply Networks: Sequential and Platform-Driven Innovations

We draw from an eight-year dataset of 98 organisational entities involved in pre-competitive innovation networks across the UK pharmaceutical sector. These data map into three networks that are representative of: (i) a product development-led sequential pathway that begins with digitalised product development, followed by digitalisation of supply networks, (ii) a supply network-led sequential pathway that starts with digitalised supply networks, followed by digitalisation of product development, and (iii) a parallel — platform-driven — pathway that enables simultaneous digitalisation of development, production, and supply networks. We draw upon extant literature to assess these network structures along three dimensions — strategic intent, the integrative roles of nodes with high centrality, and innovation performance. We conduct within-case and cross-case analyses to postulate 10 research propositions that compare and contrast modalities for sequential and platform-based digitalisation involving collaborative innovation networks. With sequential development, our propositions are congruent with conventional pathways for mitigating innovation risks through modular moves. On the other hand, we posit that platform-based design rules, rather than modular moves, mitigate the risks for parallel development pathways, and lead to novel development and delivery mechanisms

‘A double-edged sword. This is powerful but it could be used destructively’: Perspectives of early career education researchers on learning analytics

Learning analytics has been increasingly outlined as a powerful tool for measuring, analysing, and predicting learning experiences and behaviours. The rising use of learning analytics means that many educational researchers now require new ranges of technical analytical skills to contribute to an increasingly data-heavy field. However, it has been argued that educational data scientists are a ‘scarce breed’ (Buckingham Shum et al., 2013) and that more resources are needed to support the next generation of early career researchers in the education field. At the same time, little is known about how early career education researchers feel towards learning analytics and whether it is important to their current and future research practices. Using a thematic analysis of a participatory learning analytics workshop discussions with 25 early career education researchers, we outline in this article their ambitions, challenges and anxieties towards learning analytics. In doing so, we have provided a roadmap for how the learning analytics field might evolve and practical implications for supporting early career researchers’ development

The views of general practitioners and practice nurses towards the barriers and facilitators of proactive, internet-based chlamydia screening for reaching young heterosexual men

Background: Chlamydia trachomatis is a common bacterial sexually transmitted infection (STI), which disproportionately affects young people under 25 years. Commonly, more women are offered screening than men. This study obtained the views of general practitioners and practice nurses towards Internet-based screening and assessed levels of support for the development of proactive screening targeting young heterosexual men via the Internet. Methods: Semi-structured telephone interviews with 10 general practitioners and 8 practice nurses, across Central Scotland. Topics covered: experience of screening heterosexual men for chlamydia, views on the use of the Internet as a way to reach young men for chlamydia screening, beliefs about the potential barriers and facilitators to Internet-based screening. Transcripts from audio recordings were analysed with Framework Analysis, using QSR NVivo10. Results: Experiences of chlamydia screening were almost exclusively with women, driven by the nature of consultations and ease of raising sexual health issues with female patients; few practice nurses reported seeing men during consultations. All participants spoke in favour of Internet-based screening for young men. Participants reported ease of access and convenience as potential facilitators of an Internet-based approach but anonymity and confidentiality could be potential barriers and facilitators to the success of an Internet approach to screening. Concerns over practical issues as well as those pertaining to gender and socio-cultural issues were raised. Conclusions: Awareness of key barriers and facilitators, such as confidentiality, practicality and socio-cultural influences, will inform the development of an Internet-based approach to screening. However, this approach may have its limits in terms of being able to tackle wider social and cultural barriers, along with shifts in young people's and health professionals' attitudes towards screening. Nevertheless, employing innovative efforts as part of a multi-faceted approach is required to ensure effective interventions reach the policy agenda

Managing Up in Down Times

Examines issues confronting foundation senior management during both up and down economic cycles. Focuses on the concepts of resource stewardship, change management, and achieving successful results

The Role and Relevance of Rankings in Higher Education Policymaking

Explores the rise of college rankings, similarities and differences from postsecondary assessment efforts, and factors behind their limited relevance to policy such as their effect on institutional behaviors. Recommends ways to enhance policy relevance