Evidence-based national infrastructure development

Abstract: A more strategic approach to infrastructure requires that we take account of the requirements of sustainability, not only in terms of the SDGs, but also to ensure that the infrastructure built in developing countries is truly sustainable and effective. Infrastructure and its associated planning must therefore undertake a fundamental shift in thinking

Applying a constructivist approach to the assessment of compositions in a secondary technology-based music classroom

The purpose of this case study was to explore the perspectives and reflections of students and an educator who engaged in the assessment techniques of versioning and critique in a high school classroom employing Technology-Based Music Instruction (TBMI). The use of versioning (whereby students saved projects daily with a different file name), and critique was supported by and chosen based on a constructivist perspective of learning and assessment (Fosnot, 2005; Jonassen, 1992; Scott, 2012). I sought to document what students expressed about their experiences with versioning and critique in a TBMI classroom in relation to their learning process. I also explored the ways students constructed meaning and understanding through the process of reflection and discourse while using versioning and critique in a TBMI setting, as well as the ways their experiences with versioning and critique influenced their views of growth and self-expression. I presented one educator’s impressions regarding how the use of versioning and critique influenced his view of assessment in a TBMI setting. Study participants included a teacher and four students engaged in composition as part of an Introduction to Music Technology class at a private high school. Over a three-month period, I conducted three observations and two interviews with each study participant. Data included transcriptions of interviews, student journals, videos of the classroom, and fieldnotes. For data analysis, I employed an iterative coding process, which included a deductive and inductive application of codes. Data were then sorted thematically and summarized. Analysis revealed that the educator and students found both versioning and critique to be helpful and valuable in a number of ways. The students and teacher reported that versioning provided information about each student’s individual productivity level and unique compositional process. Students found that sharing their music and providing feedback with their peers through the critique process enabled them to interact with a community of musicians who had varying musical tastes and backgrounds. Future research could expand on this study by implementing daily student reflections and replicating aspects of this study in other classroom settings

The need for better statistical testing in data-driven energy technology modeling

Technology modeling is a vital part of developing and understanding energy system scenarios and policy, but it is challenging due to data limitations, deep uncertainty, and the complex social and technological dynamics involved in the evolution of energy systems. These difficulties are often compounded by unsound technology forecasting practice, including overfitting, data selection bias, and ad hoc assumptions, leading to unreliable conclusions. We flag several cases where this has been problematic and analyze in detail a recent model for predicting the pace of solar photovoltaic and wind energy deployment. We discuss general takeaways and provide suggestions for how statistical testing should be conducted to avoid such problems in the future and to quantify the reliability of forecasts

Challenges and innovations in the economic evaluation of the risks of climate change

A large discrepancy exists between the dire impacts that most natural scientists project we could face from climate change and the modest estimates of damages calculated by mainstream economists. Economic assessments of climate change risks are intended to be comprehensive, covering the full range of physical impacts and their associated market and non-market costs, considering the greater vulnerability of poor people and the challenges of adaptation. Available estimates still fall significantly short of this goal, but alternative approaches that have been proposed attempt to address these gaps. This review seeks to provide a common basis for natural scientists, social scientists, and modellers to understand the research challenges involved in evaluating the economic risks of climate change. Focusing on the estimation processes embedded in economic integrated assessment models and the concerns raised in the literature, we summarise the frontiers of research relevant to improving quantitative damage estimates, representing the full complexity of the associated systems, and evaluating the impact of the various economic assumptions used to manage this complexity

Model-based financial regulations impair the transition to net-zero carbon emissions

Investments via the financial system are essential for fostering the green transition. However, the role of existing financial regulations in influencing investment decisions is understudied. Here we analyse data from the European Banking Authority to show that existing financial accounting frameworks might inadvertently be creating disincentives for investments in low-carbon assets. We find that differences in the provision coverage ratio indicate that banks must account for nearly double the loan loss provisions for lending to low-carbon sectors as compared with high-carbon sectors. This bias is probably the result of basing risk estimates on historical data. We show that the average historical financial risk of the oil and gas sector has been consistently estimated to be lower than that of renewable energy. These results indicate that this bias could be present in other model-based regulations, such as capital requirements, and possibly impact the ability of banks to fund green investments

Model-based financial regulations impair the transition to net-zero carbon emissions

Investments via the financial system are essential for fostering the green transition. However, the role of existing financial regulations in influencing investment decisions is understudied. Here we analyse data from the European Banking Authority to show that existing financial accounting frameworks might inadvertently be creating disincentives for investments in low-carbon assets. We find that differences in the provision coverage ratio indicate that banks must account for nearly double the loan loss provisions for lending to low-carbon sectors as compared with high-carbon sectors. This bias is probably the result of basing risk estimates on historical data. We show that the average historical financial risk of the oil and gas sector has been consistently estimated to be lower than that of renewable energy. These results indicate that this bias could be present in other model-based regulations, such as capital requirements, and possibly impact the ability of banks to fund green investments

phyr: Anrpackage for phylogenetic species-distribution modelling in ecological communities

Model-based approaches are increasingly popular in ecological studies. A good example of this trend is the use of joint species distribution models to ask questions about ecological communities. However, most current applications of model-based methods do not include phylogenies despite the well-known importance of phylogenetic relationships in shaping species distributions and community composition. In part, this is due to a lack of accessible tools allowing ecologists to fit phylogenetic species distribution models easily. To fill this gap, therpackagephyr(pronounced fire) implements a suite of metrics, comparative methods and mixed models that use phylogenies to understand and predict community composition and other ecological and evolutionary phenomena. Thephyrworkhorse functions are implemented in C++ making all calculations and model estimations fast. phyrcan fit a variety of models such as phylogenetic joint-species distribution models, spatiotemporal-phylogenetic autocorrelation models, and phylogenetic trait-based bipartite network models.phyralso estimates phylogenetically independent trait correlations with measurement error to test for adaptive syndromes and performs fast calculations of common alpha and beta phylogenetic diversity metrics. Allphyrmethods are united under Brownian motion or Ornstein-Uhlenbeck models of evolution, and phylogenetic terms are modelled as phylogenetic covariance matrices. The functions and model formula syntax we propose inphyrprovide an easy-to-use collection of tools that we hope will ignite the use of phylogenies to address a variety of ecological questions