Aggregate uncertainty in the citizen candidate model yields extremist parties

We extend the citizen candidate model of electoral competition with sincere voting to allow for k ≥ 2 states of aggregate uncertainty. We discuss and characterize the equilibrium set in this framework. We provide conditions for the existence of two-party equilibria when k = 2 and show that the policies of the two parties in any such equilibrium are not only divergent but that the parties are extremist: when the political mood is left-wing, the left-wing party wins decisively with a platform that is to the left of the left-wing median voter, while when the political mood is right-wing, the right-wing party wins decisively with a platform that is to the right of the right-wing median voter. We then provide conditions under which such equilibria remain robust for an arbitrary value of k.

Heterogeneous cooperative co-evolution memetic differential evolution algorithms for big data optimisation problems

Evolutionary algorithms (EAs) have recently been suggested as candidate for solving big data optimisation problems that involve very large number of variables and need to be analysed in a short period of time. However, EAs face scalability issue when dealing with big data problems. Moreover, the performance of EAs critically hinges on the utilised parameter values and operator types, thus it is impossible to design a single EA that can outperform all other on every problem instances. To address these challenges, we propose a heterogeneous framework that integrates a cooperative co-evolution method with various types of memetic algorithms. We use the cooperative co-evolution method to split the big problem into sub-problems in order to increase the efficiency of the solving process. The subproblems are then solved using various heterogeneous memetic algorithms. The proposed heterogeneous framework adaptively assigns, for each solution, different operators, parameter values and local search algorithm to efficiently explore and exploit the search space of the given problem instance. The performance of the proposed algorithm is assessed using the Big Data 2015 competition benchmark problems that contain data with and without noise. Experimental results demonstrate that the proposed algorithm, with the cooperative co-evolution method, performs better than without cooperative co-evolution method. Furthermore, it obtained very competitive results for all tested instances, if not better, when compared to other algorithms using a lower computational times.

Victoria’s banning notice provisions: parliamentary, procedural and individual vulnerabilities

Purpose Alcohol-related disorder in Australia’s night-time economy has precipitated an expanding regulatory and legislative framework. A key feature is the growth of police-imposed discretionary justice, one example of which are Victoria’s banning provisions. Banning notices are imposed on-the-spot, may be issued pre-emptively, but permit no right of independent appeal. However, there has been little analysis of the enactment, implementation or use of police-imposed banning provisions. The paper aims to discuss these issues.

Design/methodology/approach This paper draws upon a detailed examination of the record of parliamentary debate of the banning notice legislation to document how the provisions, and their embedded procedural vulnerabilities, were legitimised. In addition, an analysis of Victoria Police data informs consideration of the ongoing scrutiny of the police power to ban.

FindingsThe absolute discretion afforded to police officers, and a lack of effective oversight, has created the potential for the disproportionate and discriminatory implementation of Victoria’s banning notice powers. The findings highlight procedural vulnerabilities within the provisions, and concern regarding the particular risk of banning notices for vulnerable recipients.

Research limitations/implications The nature of Victoria’s banning provisions created the circumstances for their inequitable imposition, but public scrutiny of their use and effect is limited. Omissions and deficiencies in the published data restricts meaningful analysis of how banning works in practice.

Originality/value The research underpinning this paper was the first detailed examination of the implementation and ongoing scrutiny of Victoria’s banning notice provisions. The findings presented in this paper highlight key procedural vulnerabilities resulting from the passage of the legislation and the absence of effective oversight.