Human motivation and professional practice: of knights, knaves and social workers

Efforts to improve the efficiency and responsiveness of public services by harnessing the self-interest of professionals in state agencies have been widely debated in the recent literature on welfare state reform. In the context of social services, one way in which British policy-makers have sought to effect such changes has been through the "new community care" of the 1990 NHS and Community Care Act. Key to this is the concept of care management, in which the identification of needs and the provision of services are separated, purportedly with a view to improving advocacy, choice and quality for service users. This paper uses data from a wide-ranging qualitative study of access to social care for older people to examine the success of the policy in these terms, with specific reference to its attempts to harness the rational self-interest of professionals. While care management removes one potential conflict of interests by separating commissioning and provision, the responsibility of social care professionals to comply with organizational priorities conflicts with their role of advocacy for their clients, a tension rendered all the more problematic by the perceived inadequacy of funding. Moreover, the bureaucracy of the care management process itself further negates the approach's supposedly client-centred ethos. The definitive version is available at www.blackwell-synergy.com

Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.