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The purpose of this study was twofold: (a) to disentangle patterns of change and stability in self-concept clarity (SCC) in adolescents and in their parents and (b) to examine processes of intergenerational transmission of SCC in families with adolescents. Participants were 497 Dutch families including the father (baseline Mage = 46.74), the mother (baseline Mage = 44.41), and their adolescent child (56.9% males; baseline Mage = 13.03). Each family member completed the SCC scale for six waves, with a one-year interval between each wave. Latent growth curve analyses indicated that adolescent boys reported higher SCC than girls. Furthermore, fathers and mothers reported higher SCC than their children, and it increased over time. Indices of SCC rank-order stability were high and increased from T1 to T2, T2 to T3, etc., for each family member, especially for adolescents. Multivariate latent growth curve analyses and cross-lagged models highlighted a unidirectional transmission process, with fathers' and mothers' SCC influencing adolescents' SCC. This result was not moderated by adolescent gender. These findings indicate that self-concept clarity is transmitted from parents to children.

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N2 - The development of new renewable energy technologies is generally perceived as a critical factor in the fight against climate change. However, significant difficulties arise when estimating the future performance and costs of nascent technologies such as wave energy. Robust methods to estimate the commercial costs that emerging technologies may reach in the future are needed to inform decision-making. The aim of this paper is to increase the clarity, consistency, and utility of future cost estimates for emerging wave energy technologies. It proposes a novel three-step method: (1) using a combination of existing bottom-up and top-down approaches to derive the current cost breakdown; (2) assigning uncertainty ranges, depending on the estimation reliability then used, to derive the first-of-a-kind cost of the commercial technology; and (3) applying component-based learning rates to produce the LCOE of a mature technology using the upper bound from (2) to account for optimism bias. This novel method counters the human propensity toward over-optimism. Compared with state-of-the-art direct estimation approaches, it provides a tool that can be used to explore uncertainties and focus attention on the accuracy of cost estimates and potential learning from the early stage of technology development. Moreover, this approach delivers useful information to identify remaining technology challenges, concentrate innovation efforts, and collect evidence through testing activities.The development of new renewable energy technologies is generally perceived as a critical factor in the fight against climate change. However, significant difficulties arise when estimating the future performance and costs of nascent technologies such as wave energy. Robust methods to estimate the commercial costs that emerging technologies may reach in the future are needed to inform decision-making. The aim of this paper is to increase the clarity, consistency, and utility of future cost estimates for emerging wave energy technologies. It proposes a novel three-step method: (1) using a combination of existing bottom-up and top-down approaches to derive the current cost breakdown; (2) assigning uncertainty ranges, depending on the estimation reliability then used, to derive the first-of-a-kind cost of the commercial technology; and (3) applying component-based learning rates to produce the LCOE of a mature technology using the upper bound from (2) to account for optimism bias. This novel method counters the human propensity toward over-optimism. Compared with state-of-the-art direct estimation approaches, it provides a tool that can be used to explore uncertainties and focus attention on the accuracy of cost estimates and potential learning from the early stage of technology development. Moreover, this approach delivers useful information to identify remaining technology challenges, concentrate innovation efforts, and collect evidence through testing activities.

AB - The development of new renewable energy technologies is generally perceived as a critical factor in the fight against climate change. However, significant difficulties arise when estimating the future performance and costs of nascent technologies such as wave energy. Robust methods to estimate the commercial costs that emerging technologies may reach in the future are needed to inform decision-making. The aim of this paper is to increase the clarity, consistency, and utility of future cost estimates for emerging wave energy technologies. It proposes a novel three-step method: (1) using a combination of existing bottom-up and top-down approaches to derive the current cost breakdown; (2) assigning uncertainty ranges, depending on the estimation reliability then used, to derive the first-of-a-kind cost of the commercial technology; and (3) applying component-based learning rates to produce the LCOE of a mature technology using the upper bound from (2) to account for optimism bias. This novel method counters the human propensity toward over-optimism. Compared with state-of-the-art direct estimation approaches, it provides a tool that can be used to explore uncertainties and focus attention on the accuracy of cost estimates and potential learning from the early stage of technology development. Moreover, this approach delivers useful information to identify remaining technology challenges, concentrate innovation efforts, and collect evidence through testing activities.The development of new renewable energy technologies is generally perceived as a critical factor in the fight against climate change. However, significant difficulties arise when estimating the future performance and costs of nascent technologies such as wave energy. Robust methods to estimate the commercial costs that emerging technologies may reach in the future are needed to inform decision-making. The aim of this paper is to increase the clarity, consistency, and utility of future cost estimates for emerging wave energy technologies. It proposes a novel three-step method: (1) using a combination of existing bottom-up and top-down approaches to derive the current cost breakdown; (2) assigning uncertainty ranges, depending on the estimation reliability then used, to derive the first-of-a-kind cost of the commercial technology; and (3) applying component-based learning rates to produce the LCOE of a mature technology using the upper bound from (2) to account for optimism bias. This novel method counters the human propensity toward over-optimism. Compared with state-of-the-art direct estimation approaches, it provides a tool that can be used to explore uncertainties and focus attention on the accuracy of cost estimates and potential learning from the early stage of technology development. Moreover, this approach delivers useful information to identify remaining technology challenges, concentrate innovation efforts, and collect evidence through testing activities.

This article makes a conceptual and theoretical contribution to the study of diffusion. The authors suggest that the concept of diffusion be reserved for processes (not outcomes) characterized by a certain uncoordinated interdependence. Theoretically, the authors identify the principal sources of clustered policy reforms. They then clarify the characteristics specific to diffusion mechanisms and introduce a categorization of such processes. In particular, they make a distinction between two types of diffusion: adaptation and learning. They argue that this categorization adds conceptual clarity and distinguishes mechanisms with distinct substantive consequences.

Like its predecessor, Great Divergence and Great Convergence, written by the first two authors, Grinin and Korotayev (2015), the focus of this book is based on world-system theory and is in fact an extension of the thesis of that book, that the world-system is now in a process of convergence, so the periphery of the system is catching up with the leading core, the West. And also like good science, hypothetical prediction is amenable to being tested with available evidence. The book is organized into six focused chapters; the first introduces the concept of economic cycles and describes the various extant cyclical models used to analyze economic change, chief among these are Kondratieff long waves, Juglar cycles, and the models of Akamatsu and Arrighi. The second chapter provides a detailed historical analysis of Kondratieff cycles and also at length discusses obstinate data, data that do not completely fit the expectations of the model. This chapter also addresses the significance of understanding Core-Periphery interaction within the context of Kondratieff cycles. Chapter 3 treats Juglar cycles and their relationship with and motivation of Kon-dratieff cycles. Chapter 4 introduces the Flying Geese model of Akamatsu and focuses on the current process of world-system convergence. Reference is also made of the commonality between Ak-amatsu's work and that of Giovanni Arrighi and of Robert J. Barro. The analysis in Chapter 5 centers on the relationship between technological paradigm shifts and Kondratieff waves, and a very sobering Chapter 6 addresses the impact of global population aging on the future structure of the world-system.

cy toward increasing world-system complexity over time will require simplifying models; Kondratieff and company as referenced by the authors supply those models. The necessary and sufficient conditions for evolution to occur were first developed for biological systems, and while the world-system is a biological system, the evidence and sources of variation, the mechanism of selection and other attendant mechanisms, that is drift, and the means of sustaining what has been selected are not on the surface obvious for a system as complex and the world-system. Variation within the world-system, specifically the variation of economic mechanisms, is created by the recombination of extant mechanisms with the invention of new ones, a process that is intimately tied to Kondratieff long waves (see, e.g., Grinin and Korotayev 2014b). Selection occurs as a result of competition within and between various economic mechanisms. (It should be kept in mind that cooperation as an economic strategy can also be selected for.) Penultimate, the maintenance of what has been selected depends on the appropriate functioning of economic, social, and political institutions, entities which are themselves subject to selection. Finally, it should be kept clearly in mind that evolving systems may and in fact do exhibit punctuated change, thus, the pace of change is certainly not constant and may exhibit stasis, escape from which can be abrupt. This transcription of evolutionary mechanisms to the world-system stage should be kept in mind throughout the rest of this review and certainly while directly digesting the book being reviewed. e24fc04721