Research of non-contact anterior cruciate ligament (ACL) inj1ury risk aims to identify modifiable risk factors that are linked to the mechanisms of injury. Information from these studies is then used in the development of injury prevention programmes. However, ACL injury risk research often leans towards methods with three limitations: 1) a poor preservation of the athlete-environment rela- tionship that limits the generalisability of results, 2) the use of a strictly biomechanical approach to injury causation that is incom- plete for the description of injury mechanisms, 3) and a reductionist analysis that neglects profound information regarding human movement. This current opinion proposes three principles from an ecological dynamics perspective that address these limitations. First, it is argued that, to improve the generalisability of findings, research requires a well-preserved athlete-environment relation- ship. Second, the merit of including behaviour and the playing situation in the model of injury causation is presented. Third, this paper advocates that research benefits from conducting non- reductionist analysis (i.e., more holistic) that provides profound information regarding human movement. Together, these princi- ples facilitate an ecological dynamics approach to injury risk research that helps to expand our understanding of injury mechan- isms and thus contributes to the development of preventative measures.
While the notion of autarky is often contested in terms of feasibility and desirability, art and design projects that deal with autarky seem to moreover suggest positive socio-cultural and ecological effects of autarkic living. A social network model of autarky is introduced to unify these seemingly opposing views.
Recently several attempts were undertaken to unite the field of metaphor studies, trying to reconcile the conceptual/cognition and linguistic/discourse approaches to metaphor (Hampe, 2017b). The dynamic view of metaphor espoused by amongst others Gibbs (2017a) as a way to unify the field of metaphor studies is said to converge on findings and theoretical predictions found in cognition and discourse approaches. The author argues this focus on dynamical models to explain the multi-scale socio-cognitive aspects of metaphor as an emergent phenomenon is not robust enough. Complexity and dynamical systems are merely a modelling technique to deploy theory for empirical testing of hypotheses; a dynamic view of metaphor needs a coherent background theory to base its dynamic modelling of metaphor in action on (Chemero, 2009). I argue that it can be successfully based on the ecological-enactive framework available within the modern paradigm of 4E cognitive science. This framework makes possible explanation of both 'lower' cognition and 'higher' cognition emerging in the interaction of an organism with its environment. In addition, I sketch how recent theoretical insights from ecological-enactivism (Baggs and Chemero, 2018) concerning Gibson's notion of environment apply to the attempted unification of the field of metaphor studies. I close by suggesting how an understanding of metaphor as an ecological affordance of the socio-cultural environment can provide a rich basis for empirical hypotheses within a dynamical science of metaphor.
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Collaborative networks for sustainability are emerging rapidly to address urgent societal challenges. By bringing together organizations with different knowledge bases, resources and capabilities, collaborative networks enhance information exchange, knowledge sharing and learning opportunities to address these complex problems that cannot be solved by organizations individually. Nowhere is this more apparent than in the apparel sector, where examples of collaborative networks for sustainability are plenty, for example Sustainable Apparel Coalition, Zero Discharge Hazardous Chemicals, and the Fair Wear Foundation. Companies like C&A and H&M but also smaller players join these networks to take their social responsibility. Collaborative networks are unlike traditional forms of organizations; they are loosely structured collectives of different, often competing organizations, with dynamic membership and usually lack legal status. However, they do not emerge or organize on their own; they need network orchestrators who manage the network in terms of activities and participants. But network orchestrators face many challenges. They have to balance the interests of diverse companies and deal with tensions that often arise between them, like sharing their innovative knowledge. Orchestrators also have to “sell” the value of the network to potential new participants, who make decisions about which networks to join based on the benefits they expect to get from participating. Network orchestrators often do not know the best way to maintain engagement, commitment and enthusiasm or how to ensure knowledge and resource sharing, especially when competitors are involved. Furthermore, collaborative networks receive funding from grants or subsidies, creating financial uncertainty about its continuity. Raising financing from the private sector is difficult and network orchestrators compete more and more for resources. When networks dissolve or dysfunction (due to a lack of value creation and capture for participants, a lack of financing or a non-functioning business model), the collective value that has been created and accrued over time may be lost. This is problematic given that industrial transformations towards sustainability take many years and durable organizational forms are required to ensure ongoing support for this change. Network orchestration is a new profession. There are no guidelines, handbooks or good practices for how to perform this role, nor is there professional education or a professional association that represents network orchestrators. This is urgently needed as network orchestrators struggle with their role in governing networks so that they create and capture value for participants and ultimately ensure better network performance and survival. This project aims to foster the professionalization of the network orchestrator role by: (a) generating knowledge, developing and testing collaborative network governance models, facilitation tools and collaborative business modeling tools to enable network orchestrators to improve the performance of collaborative networks in terms of collective value creation (network level) and private value capture (network participant level) (b) organizing platform activities for network orchestrators to exchange ideas, best practices and learn from each other, thereby facilitating the formation of a professional identity, standards and community of network orchestrators.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
Entangled Machines is a project by Mariana Fernández Mora that interrogates the colonial and extractive legacies underpinning artificial intelligence (AI). By introducing slowness and digital kinship as critical frameworks, the project reconceptualises AI as embedded within intricate social and ecological networks, thereby contesting dominant narratives of efficiency and optimisation. Through participatory, practice-based methodologies such as the Material Playground, the project integrates feminist and non-Western epistemologies to articulate alternative models for ethical, sustainable, and equitable AI practices. Over a four-year period, Entangled Machines develops theory, engages diverse communities, and produces artistic outputs to reimagine human-AI interactions. In collaboration with partners including ARIAS Amsterdam, Archival Consciousness, and the Sandberg Institute, the research seeks to foster decolonial and interdisciplinary approaches to AI. Its culmination will be an “Anarchive” – a curated assemblage of artistic, theoretical, and archival outputs – that serves as a resource for rethinking AI’s socio-political and ecological impacts.
