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A knowledge creation perspective on âLEANâ approaches to policing in England and Wales
The police service in England and Wales continue to face intense pressures to manage and reduce budgets while simultaneously maintaining and improving levels of service. In achieving reform, attention has been directed towards the implementation of proven operational improvement frameworks, such as âlean thinkingâ taken from the automotive industry. However, the qualitatively different contexts have resulted in âleanâ interventions making only limited contribution to police reform. This research draws on contemporary views of âleanâ as a knowledge creation process to assess how such a reconceptualization may contribute to more successful police transformation
Tensor Spectral Clustering for Partitioning Higher-order Network Structures
Spectral graph theory-based methods represent an important class of tools for
studying the structure of networks. Spectral methods are based on a first-order
Markov chain derived from a random walk on the graph and thus they cannot take
advantage of important higher-order network substructures such as triangles,
cycles, and feed-forward loops. Here we propose a Tensor Spectral Clustering
(TSC) algorithm that allows for modeling higher-order network structures in a
graph partitioning framework. Our TSC algorithm allows the user to specify
which higher-order network structures (cycles, feed-forward loops, etc.) should
be preserved by the network clustering. Higher-order network structures of
interest are represented using a tensor, which we then partition by developing
a multilinear spectral method. Our framework can be applied to discovering
layered flows in networks as well as graph anomaly detection, which we
illustrate on synthetic networks. In directed networks, a higher-order
structure of particular interest is the directed 3-cycle, which captures
feedback loops in networks. We demonstrate that our TSC algorithm produces
large partitions that cut fewer directed 3-cycles than standard spectral
clustering algorithms.Comment: SDM 201
Employment conditions in the scottish social care voluntary sector : impact of public funding constraints in the context of economic recession
This report uses data to assess the impact of public funding constraints on employment conditions in the Scottish social care voluntary sector, in the context of the recent economic recessionand future public expenditure cuts
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