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I develop a survey method for estimating social influence over individual political expression, by combining the content-richness of document scaling with the flexibility of survey research. I introduce the “What Would You Say?” question, which measures self-reported usage of political catchphrases in a hypothetical social context, which I manipulate in a between-subjects experiment. Using Wordsticks, an ordinal item response theory model inspired by Wordfish, I estimate each respondent’s lexical ideology and outspokenness, scaling their political lexicon in a two-dimensional space. I then identify self-censorship and preference falsification as causal effects of social context on respondents’ outspokenness and lexical ideology, respectively. This improves upon existing survey measures of political expression: it avoids conflating expressive behavior with populist attitudes, it defines preference falsification in terms of code-switching, and it moves beyond trait measures of self-censorship, to characterize relative shifts in the content of expression between different contexts. I validate the method and present experiments demonstrating its application to contemporary concerns about self-censorship and polarization, and I conclude by discussing its interpretation and future uses.
Viewed from the perspective of public policy, behavioural public policy (BPP) faces challenges in four main areas: Systems, Impatience, Nudging, and Scaling. To address these challenges, several suggestions are proposed. First, understanding how BPP interventions unfold in complex systems requires better diagnostics and the development of predictive and generative models of human behaviour. Second, the rapid pace of policy processes necessitates a shift towards generating timely and fit-for-purpose evidence. Third, maximising the opportunities presented by BPP, beyond merely ‘nudging’, demands the early and proactive application of behavioural science in the policy cycle. Fourth, achieving widespread impact in BPP initiatives means considering scale-up from the start. Lastly, the consistent and comprehensive integration of behavioural science into standard policymaking practices would support sustainable progress in addressing these challenges.
This chapter show how throughout millennia, philanthropy has served as a catalyst for change and as a vehicle for community transformation. While COVID-19 has forced philanthropists worldwide to take immediate action and mobilise billions of dollars to save lives, African philanthropy and the culture of ‘giving’ are not new phenomena but are ingrained in the fabric of African societies. Before the arrival of colonialism, aid agencies and development partners, grassroots philanthropists and associations mobilised resources to address development issues. Within this context, the chapter focuses on the role of multi-sector partnerships in Africa and how they arose out of the crisis of the pandemic to drive the efficiency of vital collaborations between the African Union (AU), local governments, and the private sector. It shows how these partnerships helped the continent curb the pandemic and prevented the massive spread of infections. This chapter highlights the uniqueness and significance of these partnerships at the local and continental levels and identifies some of the core values underpinning them. The chapter also explores the importance and the impact of the AU’s strategic leadership and multi-sectoral partnerships in advancing the continent’s health and economic agenda while deconstructing some of the inherent challenges that were faced when trying to scale these alliances in Africa.
Having examined the production, consumption, and valuation of information and data, we can start to design business models for information goods. We examine the fundamental characteristics of information and data goods that we need to consider. It is critical for a digital innovator to design mechanisms that allow users to discover their valuation and preferences, and that allow the innovator to discover users’ willingness to pay. Ideally, such mechanisms account for cognitive tendencies to prefer intuitive, familiar, simple, and quick solutions to our data and information needs.
The components or functions derived from an eigenanalysis are linear combinations of the original variables. Principal components analysis (PCA) is a very common method that uses these components to examine patterns among the objects, often in a plot termed an ordination, and identify which variables are driving those patterns. Correspondence analysis (CA) is a related method used when the variables represent counts or abundances. Redundancy analysis and canonical CA are constrained versions of PCA and CA, respectively, where the components are derived after taking into account the relationships with additional explanatory variables. Finally, we introduce linear discriminant function analysis as a way of identifying and predicting membership of objects to predefined groups.
The analysis of ice response to stress using finite elements is described, using multiaxial constitutive relationships, including damage, in a viscoelastic framework. The U-shaped relationship of compliance with pressure is part of this formulation. The results show that the layer of damaged ice adjacent to the indentor arises naturally through the formulation, giving rise to a peak load and subsequent decline. This shows that there can be “layer failure” in addition to failure due to fractures and spalling. Tests on extrusion of crushed ice are described together with a formulation of constitutive relationships based on special triaxial tests of crushed ice. The ice temperature measured during field indentation tests showed a drop in temperature during the upswings in load. This was attributed to localized pressure melting. Small scale indentor tests are described, which show clearly the difference between layer failure and spalling, as found using high-speed video and pressure-sensitive film. The question of scaling, as used in ice tanks, is addressed. Flexural failure can be scaled to some extent; scaling of high-pressure zones lies in the mechanics as developed in the book.
In this chapter, a concept known as scaling is introduced. Scaling (also known as nondimensionalization) is essentially a form of dimensional analysis. Dimensional analysis is a general term used to describe a means of analyzing a system based off the units of the problem (e.g. kilogram for mass, kelvin for temperature, meter for length, coulomb for electric change, etc.). The concepts of this chapter, while not entirely about the fluid equations per se, is arguably the most useful in understanding the various concepts of fluid mechanics. In addition, the concepts discussed within this chapter can be extended to other areas of physics, particularly areas that are heavily reliant on differential equations (which is most of physics and engineering).
The knowledge economy represents a new domination by a longstanding factor of production. New insights and technological innovation have always shaped economic activity, but the rate of technological change and the proportion of knowledge as a factor of production and as a product have grown greatly in recent decades. This chapter describes the knowledge economy and explains how it makes it more likely that producers will have postive returns to scale – in other words, that profits will increase as the level of production grows. These features have profound implications for the international dimensions of the knowledge economy, as illustrated by branding and supply chains.
Empirical equations of downstream hydraulic geometry, entailing width, depth, velocity, and bed slope, can be derived using the scaling theory. The theory employs the momentum equation, a flow resistance formula, and continuity equation for gradually varied open channel flow. The scaling equations are expressed as power functions of water discharge and bed sediment size, and are applicable to alluvial, ice, and bedrock channels. These equations are valid for any value of water discharge as opposed to just mean or bank-full values that are used in empirical equations. This chapter discusses the use of scaling theory for the derivation of downstream hydraulic geometry. The scaling theory-based hydraulic geometry equations are also compared with those derived using the regime theory, threshold theory, and stability index theory, and the equations are found to be consistent.
This chapter discusses the ways in which natural selection has acted on the animal and primate brain, demonstrating that the human brain is better at some tasks, whereas other animals are better at certain others (e.g. special memory and chimpanzees). Human brains are the results of selection for very specific tasks, largely relating to social information. It also discusses the role of metabolism in brain evolution, reviewing the ‘expensive tissue hypothesis’. It summarizes brain anatomy, and shows that, anatomically, the human brain is essentially a scaled-up primate brain. Finally, it discusses the idea of consciousness, the ways we evaluate it in other animals, and how it may have arisen.
AM-meso structures offer a high potential for adapted properties combined with lightweight design. To utilize the potential a purposeful design of the meso structures is required. Therefore, this contribution presents an approach for modelling their properties depending on design parameters by scaling relationships. The relationships are investigated based on grey box and axiomatic models of elementary cells. Exemplary the pressure stiffness is determined using FEM in comparison to an analytical approximation. The comparison reveals effects and influences occurring within the elementary cell.
This chapter includes transcriptions and translations of material on keyboard instruments found in the writings of Jakob Adlung, Marin Mersenne, and Michael Praetorius, as well as technical descriptions of the keyboard instruments used by Johann Sebastian Bach, members of the Couperin family, George Frederick Handel, Domenico Scarlatti, Padre Antonio Soler, and other composers of the period. This chapter provides explicit tuning instructions and analysis of temperaments used in the period, notably meantone, temperament ordinaire, and various circulating and so-called “well temperaments” that appear in treatises written by Denis, Corrette, Kirnberger, Mersenne, Marpurg, Neidhardt, Rameau, Werckmeister, and others.
This chapter deals with the design and construction of keyboard instruments and covers topics such as Mersenne’s Law, keyboard compass, scaling, plucking and striking points, string tension, case and soundboard proportion and structure, as well as technical descriptions of harpsichord, clavichord, and piano mechanisms, including the so-called “English” and “Viennese” hammer actions. Early English, Nuremberg, Berlin, and Vienna wire gauges are compared.
This essay describes how the HKW (Haus der Kulturen der Welt) in Berlin was been transformed through its exploration of the Anthropocene. Originally an institution dedicated to showcasing non-European cultures, it now focuses on the new relationship between culture and the planet. The “Anthropocene-Project” began by asking how a cultural institution might approach the large-scale transformation confronting our societies? It soon became clear that the HKW must change its methods and processes. Instead of approaching the world via representations in exhibitions and talks, the HKW developed an experimental mode of active cultural production that called “curating ideas in the making.” This method combines aesthetic with scientific approaches, and reflects the fact that in the Anthropocene, knowledge production has to change: the categorical frameworks developed during the last 200 years are no longer adequate to confront the problems of the radically altered situation we find ourselves in.
In this study, we present a new granular rock-analogue material (GRAM) with a dynamic scaling suitable for the simulation of fault and fracture processes in analogue experiments. Dynamically scaled experiments allow the direct comparison of geometrical, kinematical and mechanical processes between model and nature. The geometrical scaling factor defines the model resolution, which depends on the density and cohesive strength ratios of model material and natural rocks. Granular materials such as quartz sands are ideal for the simulation of upper crustal deformation processes as a result of similar nonlinear deformation behaviour of granular flow and brittle rock deformation. We compared the geometrical scaling factor of common analogue materials applied in tectonic models, and identified a gap in model resolution corresponding to the outcrop and structural scale (1–100 m). The proposed GRAM is composed of quartz sand and hemihydrate powder and is suitable to form cohesive aggregates capable of deforming by tensile and shear failure under variable stress conditions. Based on dynamical shear tests, GRAM is characterized by a similar stress–strain curve as dry quartz sand, has a cohesive strength of 7.88 kPa and an average density of 1.36 g cm−3. The derived geometrical scaling factor is 1 cm in model = 10.65 m in nature. For a large-scale test, GRAM material was applied in strike-slip analogue experiments. Early results demonstrate the potential of GRAM to simulate fault and fracture processes, and their interaction in fault zones and damage zones during different stages of fault evolution in dynamically scaled analogue experiments.
The concepts of fluid dynamic and thermodynamic similarity are introduced. The key nondimensional parameters of relevance to radial compressors, such as flow coefficient, work coefficient, pressure coefficient and the blade tip-speed Mach number are explained. The appropriate nondimensional parameters allow the preliminary design of a new machine to be based on features of an existing machine, even one designed for a different size, a different fluid, other flow conditions or rotational speed. Its performance can also be estimated from that of a similar machine, even though it may be larger or smaller. The principle of similarity and the associated nondimensional parameters provide an invaluable aid to the design and testing of all turbomachinery and to the proper understanding of their performance maps and stage characteristics. A good grasp of these is an excellent basis for rationalising compressor performance in different applications. Deviations from similarity in real machines are considered leading to performance corrections for changes in Reynolds number and isentropic exponent.
Salt marshes are valuable but complex biophysical systems with associated ecosystems. This presents numerous challenges when trying to understand and predict their behaviour and evolution, which is essential to facilitate their continued and sustainable use, conservation and management1. Detailed understanding of the hydrodynamics, sediment dynamics, and ecology that control the system is required, as well as their numerous interactions2,3, but is complicated by spatial and temporal heterogeneity at a range of scales4,5. These complex interactions and feedbacks between the physical, biological, and chemical processes can be investigated in situ following natural, unintentional, or intentional manipulation6, but the mechanistic basis of any observations are confounded by the presence of collinear variables. Hence, laboratory investigations can be beneficial, as they provide the opportunity for systematic testing of subsets of coastal processes, mechanisms, or conditions typical of salt marsh systems, in the absence of confounding variables. With appropriate scaling, this allows a better understanding of the overall function of the salt marsh, and better predictions of their evolution.
The Conclusion uses Karl N. Llewellyn’s“What Price Contract? – An Essay in Perspective” to bring together many of the dominant themes discussed in the book. For three-dimensional law to arise legal scholars must be more refined in their perception of ideas – civilized growth, in Holmes’s view, depended on that. Holmes’s sensitivity to multivalency becomes then the leading goal of a well-wrought legal pedagogy. The more law could muster feeling, the more civilized the nation would grow. At least that was Holmes’s hope as he expressed it to Harold J. Laski.
We propose a new methodology for inferring political actors’ latent memberships in communities of collective activity that drive their observable interactions. Unlike existing methods, the proposed Bipartite Link Community Model (biLCM) (1) applies to two groups of actors, (2) takes into account that actors may be members of more than one community, and (3) allows a pair of actors to interact in more than one way. We apply this method to characterize legislative communities of special interest groups and politicians in the 113th U.S. Congress. Previous empirical studies of interest group politics have been limited by the difficulty of observing the ties between interest groups and politicians directly. We therefore first construct an original dataset that connects the politicians who sponsor congressional bills with the interest groups that lobby on those bills based on more than two million textual descriptions of lobbying activities. We then use the biLCM to make quantitative measurements of actors’ community memberships ranging from narrow targeted interactions according to industry interests and jurisdictional committee membership to broad multifaceted connections across multiple policy domains.
With the onset of the COVID-19 pandemic in the United States, many state and local governments were forced to implement necessary policies to contain transmission of the deadly virus. These policies ranged from closing most businesses to more controversial proposals, such as postponing primary elections. In this research note, we examine the role that scientific knowledge and gender played in citizen perceptions of these virus containment policies, both in the general population and among partisans. We find that while a gender gap persists in scientific knowledge, both in the general population and within the parties, women are generally more likely to use this knowledge to inform their policy views on necessary government action during the COVID-19 pandemic. These findings shed light on how knowledge and gender intersect to drive support for government intervention during the time of a severe public health crisis in a partisan America.