Anthropometric within-country Inequality and the Estimation of Skill Premia with Anthropometric Indicators

Recently, a method to measure inequality has been proposed that is based on an- thropometric indicators. Baten (1999, 2000) argued that the coefficient of variation of human stature (henceforth ‘CV’) is correlated with overall inequality in a society, and that it can be used as indicator, especially where income inequality measures are lack- ing. This correlation has been confirmed in further analyses, for example by Pradhan et al. (2003), Moradi and Baten (2005), Sunder (2003), Guntupalli and Baten (2006), Blum (2010a), van Zanden et al. (2010), see also Figure 1 and Table 1. The idea is that average height reflects nutritional conditions during early childhood and youth. Since wealthier people have better access to food, shelter and medical resources, they tend to be taller than the poorer part of the population. Hence, the variation of height of a cer- tain cohort may be indicative of income distribution during the decade of their birth. The aim of this study is firstly to provide an overview of different forms of within- country height inequality. Previous studies on the aspects of height inequality are re- viewed. Inequalities between ethnic groups, gender, inhabitants of different regions and income groups are discussed. In the two final sections, we compare height CVs of anthropological inequality with another indicator of inequality, namely skill premia. We also present estimates of skill premia for a set of countries and decades for which “height CVs”, as they will be called in the following, are available.

Constructing random matrices to represent real ecosystems

Models of complex systems with n components typically have order n² parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.

'When I Look I am Seen, So I Exist to Change': Supplementing Honneth's Recognition Model for Social Work

The subject of identity continues to attract widespread interest and debate in the social sciences. The nature of who we are, our potential to be different, and our similarity with others, underpins many present-day social issues. This paper contributes to this debate by examining critically the work of Axel Honneth on optimal identity-formation. Although broadly supporting Honneth’s chief construct of inter-personal recognition, a gap in his thinking is highlighted and addressed through proffering a fourth dimension to his tripartite model. This additional dimension requires demonstrations of recognition that instil hope in the face of hardship and empower positive transformations in identity. The implications of this reworked model for social work are then considered in terms of a range of approaches that can be utilised to build flourishing identities characterised by self-esteem, self-confidence, self-respect and self-belief.

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.

Impact of biodiversity loss on production in complex marine food webs mitigated by prey-release

Public concern over biodiversity loss is often rationalized as a threat to ecosystem functioning, but biodiversity-ecosystem functioning (BEF) relations are hard to empirically quantify at large scales. We use a realistic marine food-web model, resolving species over five trophic levels, to study how total fish production changes with species richness. This complex model predicts that BEF relations, on average, follow simple Michaelis-Menten curves when species are randomly deleted. These are shaped mainly by release of fish from predation, rather than the release from competition expected from simpler communities. Ordering species deletions by decreasing body mass or trophic level, representing 'fishing down the food web', accentuates prey-release effects and results in unimodal relationships. In contrast, simultaneous unselective harvesting diminishes these effects and produces an almost linear BEF relation, with maximum multispecies fisheries yield at approximate to 40% of initial species richness. These findings have important implications for the valuation of marine biodiversity.

Structure and dynamics of aqueous 2-propanol: A THz-TDS, NMR and neutron diffraction study

Aqueous liquid mixtures, in particular, those involving amphiphilic species, play an important role in many physical, chemical and biological processes. Of particular interest are alcohol/water mixtures; however, the structural dynamics of such systems are still not fully understood. Herein, a combination of terahertz time-domain spectroscopy (THz-TDS) and NMR relaxation time analysis has been applied to investigate 2-propanol/water mixtures across the entire composition range; while neutron diffraction studies have been carried out at two specific concentrations. Excellent agreement is seen between the techniques with a maximum in both the relative absorption coefficient and the activation energy to molecular motion occurring at ∼90 mol% H₂O. Furthermore, this is the same value at which well-established excess thermodynamic functions exhibit a maximum/minimum. Additionally, both neutron diffraction and THz-TDS have been used to provide estimates of the size of the hydration shell around 2-propanol in solution. Both methods determine that between 4 and 5 H₂O molecules per 2-propanol are found in the 2-propanol/water clusters at 90 mol% H₂O. Based on the acquired data, a description of the structure of 2-propanol/water across the composition range is presented.