Regional sustainability networks in the Netherlands are rooted in regionalculture and have an emphasis on social learning and effective collaboration between multiple actors. The national ‘Duurzaam Door’ (Moving Forward Sustainably) Policy Programme regards these networks as generative governance arrangements where new knowledge, actions and relations can co-evolve together with new insights in governance and learning within sustainability transitions. In order to understand the dynamics of the learning in these networks we have monitored emergent properties of social learning between 2014 and 2016. Our focus is particularly on the interrelated role of trust, commitment, reframing and reflexivity. Our aim is to better understand the role and the dynamics of these emergent properties and to see which actors and roles can foster the effectiveness of social learning in regional transitions towards more sustainable ways of living. We used a retrospective analysis with Reflexive Monitoring in Action (RMA), which we combined with the Most Significant Change approach. We found that reflexivity in particularis a critical property at moments that can make or break the process.
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Many transitions scholars underscore the importance of learning in sustainability transitions, but the associated learning processes have hardly been conceptualised. The diverse, well-established research fields related to learning are broadly ignored or loosely applied. In this paper, we systematically explore four interesting learning traditions in terms of their value for gaining an in-depth understanding of learning in sustainability transitions and their relevance for fostering learning, by connecting them to key features of transitions. The selected learning traditions from different disciplinary backgrounds provide valuable insights. None of them sufficiently addresses the complexity of transitions. They include, however, a diversity of relevant learning contexts. We conclude that they have value for investigating new areas such as learning in socio-technological regimes and in later phases of a transition, while enlightening forms of learning that have not yet been fully recognised in transition studies, such as superficial learning, unlearning, and learning to resist change.
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Sustainability transition research seeks to understand the patterns and dynamics of structural societal change as well as unearth strategies for governance. However, existing frameworks emphasize innovation and build-up over exnovation and break-down. This limits their potential in making sense of the turbulent and chaotic dynamics of current transition-in-the-making. Addressing this gap, our paper elaborates on the development and use of the X-curve framework. The X-curve provides a simplified depiction of transitions that explicitly captures the patterns of build-up, breakdown, and their interactions.Using three cases, we illustrate the X-curve’s main strength as a framework that can support groups of people to develop a shared understanding of the dynamics in transitions-in-the-making. This helps them reflect upon their roles, potential influence, and the needed capacities for desired transitions. We discuss some challenges in using the X-curve framework, such as participants’ grasp of ‘chaos’, and provide suggestions on how to address these challenges and strengthen the frameworks’ ability to support understanding and navigation of transition dynamics. We conclude by summarizing its main strength and invite the reader to use it, reflect on it, build on it, and judge its value for action research on sustainability transitions themselves.
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The challenges we collectively face, such as climate change, are characterized by more complexity, interdependence, and dynamism than is common for educational practice. This presents a challenge for (university) education. These transition challenges are often described as wicked or VUCA (Volatile, Uncertain, Complex, and Ambiguous) problems. In response, educational innovations that are inspired by ecology such as living labs are starting to emerge, but little is known about how learners engage within and with these more ecological forms of education. This work is an exploratory study into how learners navigate VUCA learning environments linked to tackling sustainability transition challenges, with a focus on the positive qualities of these experiences. This is done through interpretative phenomenological analysis (IPA) of seven students (using semi-structured interviews) of the MSC Metropolitan Analysis, Design and Engineering program, a joint degree from Wageningen University and Delft University of Technology in the Netherlands. The main findings, which are both psychological and educational, of this exploration include openness to new experiences (1), flexibility (2), a process appreciation of learning (3), a desire to create a positive impact on one’s direct biophysical environment (4) and society (5). In addition, we discuss the potential limitations of the malleability of these different qualities and propose future avenues for research into ecological learning for universities. This work closes by highlighting recommendations for educators to consider when designing or engaging in ecological forms of higher education that connect students to sustainability transitions.
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Introduction: People on the autism spectrum often struggle to transition smoothly between occupations in daily life. Objective: This qualitative inquiry aimed to understand the human and non-human factors that influence occupational transitions from the perspectives of adults on the autism spectrum. Method: Using a constructivist grounded theory design, this study purposively gathered data from eight adults on the autism spectrum who shared their viewpoints via semi-structured interviews and self-produced written texts. Framed by the Cultural Historical Activity Theory, an iterative process of constant comparative analysis was employed, yielding six categories that constituted the assembly of a working theory on occupational transitions among adults on the autism spectrum. Results: Drawn from eight participants, the six categories were: 1) getting ready, 2) the attributes of the occupation, 3) the others, 4) strategies of the moment, 5) cumulative stress, and 6) possible ends of the process. Conclusion: Our findings revealed a nuanced understanding on occupational transitions for adults with autism. First, materiality (non-human entities) serves various purposes in occupational transitions, implying that in some cases, intangible materials (tacit knowledge) would be enough to initiate, aid, or terminate occupational transitions. Second, doing transitions together through the optimization of social support and resources can make occupational transitions more meaningful for adults in the autism spectrum. It is our ambition that these propositions be tested and emphasized in occupational therapy, healthcare, and social care practices.
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This study evaluates the effectiveness of the European Union's Corporate Sustainability Reporting Directive (CSRD) in quantitatively measuring the transition of companies to a circular economy. First, using the most recent literature review on circularity metrics, a complete overview of the currently available circularity metrics is developed. Subsequently, it is determined which circularity metrics can be generated with the available quantitative datapoints of CSRD. The metrics that can be generated were analyzed on their ability to cover all circular strategies, to represent different Product-as-a-Service systems and to acknowledge the key role of Critical Raw Materials in a circular economy. The study finds that, with data disclosed under CSRD, metrics can be generated to cover all circular strategies. However, gaps remain in representing pay-per-use and pay-perperformance systems and the use of Critical Raw Materials. Recommendations are to include ‘Product utilization’ and ‘Mass of Critical Raw Materials used’ in the data disclosed under CSRD and to have an independent institution report data to enable benchmarking of performances. Finally, this study concludes with an overview of the metrics which enable to measure circular transitions using data disclosed by CSRD
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This special issue was initiated to contribute to an in-depth debate on the issue of learning in transitions, specifically by integrating concepts from the learning and transition domains.
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