Portfolio of Compositions investigating ensemble improvisation, distributed and real-time scoring, and multi-nodal input and output

This output is a collection of compositions which explore issues of ensemble improvisation, ensemble management and orchestration, real-time and distributed scoring, multi-nodal inputs and outputs, and animated and graphic notation. Compositions include: Activities I; tutti, duet, trio, solo, quartet; Lewitt Notations I; Webwork I; and Sometimes I feel the space between people (voices) in terms of tempos. These compositions are presented in computer animated scores which are synchronized through the network and subject to real-time modification and control. They can be performed by ensembles distributed over large physical spaces connected by the network. The scores for these compositions include software which displays the animations to the performers, software to structure and disseminate score events, and triggering software that allows the control of a performance to be distributed. Scores can also include live electronics which are coordinated with graphic events.

Beyond the ideal free distribution: More general models of predator distribution

The ideal free distribution model which relates the spatial distribution of mobile consumers to that of their resource is shown to be a limiting case of a more general model which we develop using simple concepts of diffusion. We show how the ideal free distribution model can be derived from a more general model and extended by incorporating simple models of social influences on predator spacing. First, a free distribution model based on patch switching rules, with a power-law interference term, which represents instantaneous biased diffusion is derived. A social bias term is then introduced to represent the effect of predator aggregation on predator fitness, separate from any effects which act through intake rate. The social bias term is expanded to express an optimum spacing for predators and example solutions of the resulting biased diffusion models are shown. The model demonstrates how an empirical interference coefficient, derived from measurements of predator and prey densities, may include factors expressing the impact of social spacing behaviour on fitness. We conclude that empirical values of log predator/log prey ratio may contain information about more than the relationship between consumer and resource densities. Unlike many previous models, the model shown here applies to conditions without continual input. (C) 1997 Academic Press Limited.</p>

Explaining the relationship between ingroup identification and intergroup bias following recategorization: A self-regulation theory analysis

We tested the hypothesis that regulation of discrepancies between perceived actual and ideal differentiation between the ingroup and outgroup could help to explain the relationship between ingroup identification and intergroup bias when participants are recategorized into a superordinate group. Replicating previous findings, we found that following recategorization, identification was positively related to intergroup bias. No such differences emerged in a control condition. However, we also, in the recategorization condition only, observed a positive association between ingroup identification and the perceived discrepancy between actual and ideal degree of differentiation from the outgroup: at higher levels of identification, participants increasingly perceived the ingroup to be less differentiated from the outgroup than they would ideally like. This tendency mediated the relationship between identification and bias. We discuss the theoretical, methodological and practical implications of these findings.

Common Ingroups and Complex Identities: Routes to Reducing Bias in Multiple Category Contexts

We tested the hypothesis that evaluative bias in common ingroup contexts versus crossed categorization contexts can be associated with two distinct underlying processes. We reasoned that in common ingroup contexts, self-categorization, but not perceived complexity, would be positively related to intergroup bias. In contrast, in crossed categorization contexts, perceived complexity, but not self-categorization, would be negatively related to intergroup bias. In two studies, and in line with predictions, we found that while self-categorization and intergroup bias were related in common ingroup contexts, this was not the case in crossed categorization contexts. Moreover, we found that perceived category complexity, and not self-categorization, predicted bias in crossed categorization contexts. We discuss the implications of these findings for models of social categorization and intergroup bias.