Elitism vs. Checks and Balances in Communicating Scientific Information to the Public

The father of the Science Court describes his objective in proposing the institution as it has come to be known, his efforts to get a major public test of the concept, and insights gained since the initial proposal was made in 1967

Perceived efficacy and attitudes towards genetic science and science governance

This is the postprint version of the Article. The official published version can be obtained from the link below - © 2010 SAGE Publications.Arguments for public involvement in science and technology are often based on ideas of developing a more capable public and the assumed effects this may have for science. However, such a relationship is yet to be sufficiently explored and recent work indicates that a more involved public may have counterintuitive effects. Using nationally representative survey data for the UK and Northern Ireland, the effects of the public's own beliefs about involvement are explored. Developing the concept of "belief in public efficacy," findings suggest those who believe that the public might be able to affect the course of decision making have less approving attitudes towards future applications of genetic science; however, an individual's political efficacy does not significantly influence these attitudes. Furthermore, political efficacy and belief in public efficacy have some distinct and opposing relationships with the principles of governance people prefer. Overall, findings provide support for suggestions that it is simplistic to consider increasing public involvement as a way of increasing the approval of risky new technologies

Review of Metaheuristics and Generalized Evolutionary Walk Algorithm

Metaheuristic algorithms are often nature-inspired, and they are becoming very powerful in solving global optimization problems. More than a dozen of major metaheuristic algorithms have been developed over the last three decades, and there exist even more variants and hybrid of metaheuristics. This paper intends to provide an overview of nature-inspired metaheuristic algorithms, from a brief history to their applications. We try to analyze the main components of these algorithms and how and why they works. Then, we intend to provide a unified view of metaheuristics by proposing a generalized evolutionary walk algorithm (GEWA). Finally, we discuss some of the important open questions.Comment: 14 page

Ordoliberalism and the evolution of norms

The first part of the following paper deals with varying points of criticism forwarded against Ordoliberalism. Here, it is not the aim to directly falsify each argument on its own; rather, the author tries to give a precise overview of the spectrum of critique. The second section picks out one argument of critical review – namely that the ordoliberal concept of the state is somewhat elitist and grounded on intellectual experts. Based on the previous sections, the final part differentiates two kinds of genesis of norms: an evolutionary and an elitist one – both (latently) present within Ordoliberalism. In combination with the two-level differentiation between individual and regulatory ethics, the essay allows for a distinction between individual-ethical norms based on an evolutionary genesis of norms and regulatory-ethical norms based on an elitist understanding of norms. A by-product of the author’s argument is a (further) demarcation within neoliberalism

Fighting austerity: Why after 80 years the General Theory is still relevant today,

The guiding spirit of the Keynesian Revolution is that full employment is a goal which can be pursued not by following the free market rules, but by reshaping them by means of public intervention. This message was widely accepted for thirty years as from the end of the Second World War by all the advanced countries which actively engaged in full employment and welfare policies, and subsequently abandoned with the neo-liberal Restoration which saw the dogmas of individualism and de-regulation prevailing. In reclaiming the topical importance of the General Theory, we should take into consideration the changed circumstances of today’s world when compared to those of twenty – let alone eighty – years ago, although there are notable similarities between the Great Depression of the 1930s – Keynes’s world – and our contemporary crisis. However, his prescription for a better society is still relevant: it lies in setting rules and limitations in the market arena, not letting individual self-interest prevail, and putting some governing bodies in charge of filling the gap when deficient aggregate demand occurs, so that the acquisition of material goods and the fruition of the enjoyments of life be not a privilege of the few but the conquest of civilization

PonyGE2: Grammatical Evolution in Python

Grammatical Evolution (GE) is a population-based evolutionary algorithm, where a formal grammar is used in the genotype to phenotype mapping process. PonyGE2 is an open source implementation of GE in Python, developed at UCD's Natural Computing Research and Applications group. It is intended as an advertisement and a starting-point for those new to GE, a reference for students and researchers, a rapid-prototyping medium for our own experiments, and a Python workout. As well as providing the characteristic genotype to phenotype mapping of GE, a search algorithm engine is also provided. A number of sample problems and tutorials on how to use and adapt PonyGE2 have been developed.Comment: 8 pages, 4 figures, submitted to the 2017 GECCO Workshop on Evolutionary Computation Software Systems (EvoSoft

Landau Gauge Fixing supported by Genetic Algorithm

A class of algorithms for the Landau gauge fixing is proposed, which makes the steepest ascent (SA) method be more efficient by concepts of genetic algorithm. Main concern is how to incorporate random gauge transformation (RGT) %, mutation in genetic algorithm (GA) terminology, to gain higher achievement of the minimal Landau gauge fixing, and to keep lower time consumption. One of these algorithms uses the block RGT, and another uses RGT controlled by local fitness density, and the last uses RGT determined by Ising Monte Carlo process. We tested these algorithms on SU(2) lattice gauge theory in 4 dimension with small $\beta$s, 2.0, 1.75 and 1.5, and report improvements in hit rate and/or in time consumption, compared to other methods.Comment: 3 pages, 3 figures LATTICE'99(ALGORITHM