The uneven impact of recession on the voluntary and community sectors:Bristol and Liverpool

There has been much debate about the impact of recession and austerity on the voluntary and community sector over recent years. Using secondary data from the 2008 National Survey of Third Sector Organisations, Clifford et al. (2013), writing in this journal, have argued that voluntary sector organisations located in more deprived local authorities are likely to suffer most due to the combined effect of cuts in government funding in these areas and their greater dependency on statutory funding. This paper develops this argument by exploring the sector’s changing relationship with the state through an empirical analysis of the differential impact of recession and austerity on voluntary and community organisations involved in public service delivery in the two English core cities of Bristol and Liverpool. This paper highlights how the scale and unevenness of public spending cuts, the levels of voluntary sector dependency on statutory funding and the rising demands for the sector’s services in a period of recession and austerity are being experienced locally. It portrays a sector whose resilience is being severely tested and one that is being forced rapidly to restructure and reposition itself in an increasingly challenging funding environment. </jats:p

Properties of Gamma-Ray Burst Classes

The three gamma-ray burst (GRB) classes identified by statistical clustering analysis (Mukherjee et al. 1998) are examined using the pattern recognition algorithm C4.5 (Quinlan 1986). Although the statistical existence of Class 3 (intermediate duration, intermediate fluence, soft) is supported, the properties of this class do not need to arise from a distinct source population. Class 3 properties can easily be produced from Class 1 (long, high fluence, intermediate hardness) by a combination of measurement error, hardness/intensity correlation, and a newly-identified BATSE bias (the fluence duration bias). Class 2 (short, low fluence, hard) does not appear to be related to Class 1.Comment: 5 pages, 4 imbedded figures, presented at the 5th Huntsville Gamma-Ray Burst Symposiu

AI Gamma-Ray Burst Classification: Methodology/Preliminary Results

Artificial intelligence (AI) classifiers can be used to classify unknowns, refine existing classification parameters, and identify/screen out ineffectual parameters. We present an AI methodology for classifying new gamma-ray bursts, along with some preliminary results.Comment: 5 pages, 2 postscript figures. To appear in the Fourth Huntsville Gamma-Ray Burst Symposiu

How Sample Completeness Affects Gamma-Ray Burst Classification

Unsupervised pattern recognition algorithms support the existence of three gamma-ray burst classes; Class I (long, large fluence bursts of intermediate spectral hardness), Class II (short, small fluence, hard bursts), and Class III (soft bursts of intermediate durations and fluences). The algorithms surprisingly assign larger membership to Class III than to either of the other two classes. A known systematic bias has been previously used to explain the existence of Class III in terms of Class I; this bias allows the fluences and durations of some bursts to be underestimated (Hakkila et al., ApJ 538, 165, 2000). We show that this bias primarily affects only the longest bursts and cannot explain the bulk of the Class III properties. We resolve the question of Class III existence by demonstrating how samples obtained using standard trigger mechanisms fail to preserve the duration characteristics of small peak flux bursts. Sample incompleteness is thus primarily responsible for the existence of Class III. In order to avoid this incompleteness, we show how a new dual timescale peak flux can be defined in terms of peak flux and fluence. The dual timescale peak flux preserves the duration distribution of faint bursts and correlates better with spectral hardness (and presumably redshift) than either peak flux or fluence. The techniques presented here are generic and have applicability to the studies of other transient events. The results also indicate that pattern recognition algorithms are sensitive to sample completeness; this can influence the study of large astronomical databases such as those found in a Virtual Observatory.Comment: 29 pages, 6 figures, 3 tables, Accepted for publication in The Astrophysical Journa

Collaborative care : primary health workforce and service delivery in Western New South Wales - a case study

Objective: To explore how four small towns in rural New South Wales known as the 4Ts are addressing challenges accessing quality care and sustainable health services through a collaborative approach to workforce planning using the collaborative care framework. Design: Descriptive case study approach. Setting: The collaborative care project was developed as a result of ongoing partnerships between 2 rural Local Health Districts, 2 Primary Health Networks and a non-governmental health workforce organisation. The collaboration works with 5 subregions each comprising 2 or more rural communities. This paper focuses on the 4Ts subregion. Participants: Stakeholders of the collaborative design including organisations and the community. Intervention: A place-based approach to co-designing health services with community in one sub-region of Western New South Wales. Main outcome measures: A synthesis of field observations and experiences of community and jurisdictional partners in implementation of the 4Ts subregional model. Mapping of implementation processes against the collaborative care framework. Results: The collaborative care framework is a useful planning and community engagement tool to build health workforce literacy and to impact on system change at the local level. We identify key elements of effectiveness in establishing the 4Ts model, including the need for coordinated health system planning, better integrating existing resources to deliver services, community engagement, building health workforce literacy and town-based planning. Conclusion: This study adds to the body of knowledge about how to successfully develop a collaborative primary health care workforce model in practice. The findings demonstrate that the implementation of a collaborative primary health care workforce model using the collaborative care framework can improve service access and quality, which in turn might facilitate workforce sustainability

'Country life'? Rurality, folk music and 'Show of Hands'

This paper examines the contribution of folk music to understanding the dynamic, fluid and multi-experiential nature of the countryside. Drawing from literature on the geographies of music, it examines the work of 'Show of Hands', a contemporary folk band from Devon in England. Three areas are studied. First, the paper examines the musical style of Show of Hands in order to explore how hybridised, yet distinctive, styles of music emerge in particular places. Second, it demonstrates how Show of Hands' hybrid musical style has become closely associated with the Southwest of England. Finally, within these spatial and hybrid contexts, attention is given to the ways in which their music represents the 'everyday lives of the rural'. Taken together these themes assess the relevance of music in the understanding of rurality as hybrid space. © 2008 Elsevier Ltd. All rights reserved