Constructing Ethical Patterns in Times of Globalization : Hans Küng's Global Ethic Project and Beyond

The purpose of this study is to evaluate contemporary philosophical models for global ethics in light of the Catholic theologian Hans Küng s Global Ethic Project (Projekt Weltethos). Küng s project starts with the motto, No survival without world ethos. No global peace without peace between religions. I will use the philosophically multidimensional potential of Projekt Weltethos in terms of its possible philosophical interpretations to evaluate the general discussion of global ethics within political philosophy today. This is important in its own right, but also because through it, opportunities will emerge to articulate Küng s relatively general argument in a way that leaves less room for mutually contradictory concretizations of what global ethics ultimately should be like. The most important question in this study is the problem of religious and ideological exclusivism and its relation to the ethically consistent articulation of global ethics. I will first explore the question of the role of religion as the basis for ethics in general and what Küng may mean by his claim that only the unconditional can oblige unconditionally. I will reconstruct two different overall philosophical interpretations of the relationship between religious faith and human rationality, each having two different sub-divisions: a liberal interpretation amounts to either a Kantian-Scheiermacherian or a Jaspersian view, whereas what I call postliberal interpretation amounts to either an Aristotelian-Thomistic or an Augustinian view. Thereafter, I will further clarify how Küng views the nature of ethics beyond the question of its principal foundation in religious faith: Küng searches for a middle way between consequentialist and non-consequentialist ethics, a way in which the latter dimension has the final stake. I will then set out to concretize further this more or less general notion of the theoretical potential of Projekt Weltethos in terms of certain precise philosophico-political models. I categorize these models according to their liberal or postliberal orientation. The liberal concretization leads me to consider a wide spectrum of post-Kantian and post-Hegelian models from Rawls to Derrida, while the alternative concretization opens up my ultimate argument in favor of a postliberal type of modus vivendi. I will suggest that the only theoretically and practically plausible way to promote global ethics, in itself a major imperative today, is the recognition of a fundamental and necessary contest between mutually exclusive ideologies in the public sphere. On this basis I will proceed to my postliberal proposal, namely, that a constructive and peaceful encountering of exclusive difference as an ethical vantage point for an intercultural and inter-religious peace dialogue is the most acute challenge for global ethics today.

Drug cultures in Estonia : contexts, meanings and patterns of illicit drug use.

In Estonia, illicit drug use hardly existed before the social changes of the 1990s when, as a result of economic and cultural transformations, the country became part of a world order centred in the West. On the one hand, this development is due to the spread of international youth culture, which many young people have perceived as being associated with drugs; on the other hand, it results from the marginalisation of a part of the population. The empirical part of the study is based mostly on in-depth interviews with different drug users conducted during between 1998 and 2002. Complementary material includes the results of participant observations, interviews with key experts, and the results of previous quantitative studies and statistics. The young people who started experimenting with illicit drugs from the 1990s and onwards perceived them as a part of an attractive lifestyle - a Western lifestyle, a point which is worth stressing in the case of Estonia. Although the reasons for initiation into drug use were similar for the majority of young people, their drug use habits and the impact of the drug use on their lives began to differ. I argue that the potential pleasure and harm which might accompany drug use is offset by the meanings attached to drugs and the sanctions and rituals regulating drug use. In the study both recreational and problem use have been analysed from different aspects in seven articles. I have investigated different types of drug users: new bohemians, cannabis users, in whose case partying and restrictive drug use is positively connected to their lives and goals within established society; stimulant-using party people for whom drugs are a means of having fun but who do not have the same restrictive norms regulating their drug use as the former and who may get into trouble under certain conditions; and heroin users for whom the drug rapidly progressed from a means of having fun to an obligation due to addiction. The research results point at the importance not only of the drug itself and the socio-economic situation of the user, but also of the cultural and social context within which the drug is used. The latter may on occasions be a crucial factor in whether or not initial drug use eventually leads to addiction.

Traditional patterns and textures as values for meaningful automatization in music

This contribution focuses on the accelerated loss of traditional sound patterning in music, parallel to the exponential loss of linguistic and cultural variety in a world increasingly 'globalized' by market policies and economic liberalization, in which scientific or technical justification plays a crucial role. As a suggestion to an alternative trend, composers and music theorists are invited to explore the world of design and patterning by grammar rules from non-dominant cultures, and to make an effort to understand their contextual usage and its transformation, in order to appreciate their symbolism and aesthetic depth. Practical examples are provided.

Maximum Loss Calculation using Scenario Analysis, Heavy Tails and Implied Volatility Patterns

The objective of this paper is to improve option risk monitoring by examining the information content of implied volatility and by introducing the calculation of a single-sum expected risk exposure similar to the Value-at-Risk. The figure is calculated in two steps. First, there is a need to estimate the value of a portfolio of options for a number of different market scenarios, while the second step is to summarize the information content of the estimated scenarios into a single-sum risk measure. This involves the use of probability theory and return distributions, which confronts the user with the problems of non-normality in the return distribution of the underlying asset. Here the hyperbolic distribution is used to describe one alternative for dealing with heavy tails. Results indicate that the information content of implied volatility is useful when predicting future large returns in the underlying asset. Further, the hyperbolic distribution provides a good fit to historical returns enabling a more accurate definition of statistical intervals and extreme events.

Intraday and Weekend Volatility Patterns- Implications for Option Pricing

This study examines the intraday and weekend volatility on the German DAX. The intraday volatility is partitioned into smaller intervals and compared to a whole day’s volatility. The estimated intraday variance is U-shaped and the weekend variance is estimated to 19 % of a normal trading day. The patterns in the intraday and weekend volatility are used to develop an extension to the Black and Scholes formula to form a new time basis. Calendar or trading days are commonly used for measuring time in option pricing. The Continuous Time using Discrete Approximations model (CTDA) developed in this study uses a measure of time with smaller intervals, approaching continuous time. The model presented accounts for the lapse of time during trading only. Arbitrage pricing suggests that the option price equals the expected cost of hedging volatility during the option’s remaining life. In this model, time is allowed to lapse as volatility occurs on an intraday basis. The measure of time is modified in CTDA to correct for the non-constant volatility and to account for the patterns in volatility.

Patterns in permuted binary matrices

Reorganizing a dataset so that its hidden structure can be observed is useful in any data analysis task. For example, detecting a regularity in a dataset helps us to interpret the data, compress the data, and explain the processes behind the data. We study datasets that come in the form of binary matrices (tables with 0s and 1s). Our goal is to develop automatic methods that bring out certain patterns by permuting the rows and columns. We concentrate on the following patterns in binary matrices: consecutive-ones (C1P), simultaneous consecutive-ones (SC1P), nestedness, k-nestedness, and bandedness. These patterns reflect specific types of interplay and variation between the rows and columns, such as continuity and hierarchies. Furthermore, their combinatorial properties are interlinked, which helps us to develop the theory of binary matrices and efficient algorithms. Indeed, we can detect all these patterns in a binary matrix efficiently, that is, in polynomial time in the size of the matrix. Since real-world datasets often contain noise and errors, we rarely witness perfect patterns. Therefore we also need to assess how far an input matrix is from a pattern: we count the number of flips (from 0s to 1s or vice versa) needed to bring out the perfect pattern in the matrix. Unfortunately, for most patterns it is an NP-complete problem to find the minimum distance to a matrix that has the perfect pattern, which means that the existence of a polynomial-time algorithm is unlikely. To find patterns in datasets with noise, we need methods that are noise-tolerant and work in practical time with large datasets. The theory of binary matrices gives rise to robust heuristics that have good performance with synthetic data and discover easily interpretable structures in real-world datasets: dialectical variation in the spoken Finnish language, division of European locations by the hierarchies found in mammal occurrences, and co-occuring groups in network data. In addition to determining the distance from a dataset to a pattern, we need to determine whether the pattern is significant or a mere occurrence of a random chance. To this end, we use significance testing: we deem a dataset significant if it appears exceptional when compared to datasets generated from a certain null hypothesis. After detecting a significant pattern in a dataset, it is up to domain experts to interpret the results in the terms of the application.