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241.
While there are many studies of self-regulation, they have not yet systematically analyzed the very process by which rules are developed and implemented. This article treats self-regulation as a process with sufficient autonomy and functional coherence to display identifiable stages, each of which deserves independent attention in turn. It draws from the literature on the stages of public policy processes and uses this as a template to identify and analyze the unique properties of private rule-making, while acknowledging the criticisms that have been made of excessive determinism and simplicity in some applications of the general idea of stages. The article shows that our understanding of self-regulation is significantly advanced by examining it as a process with stages but it emphasizes that the different stages of the self-regulatory policy process (agenda-setting, problem identification, decision, implementation and evaluation) are criss-crossed in numerous and interesting ways. It also shows that private rule-making often seeks to solve societal problems in domestic and international settings and is an important alternative to public regulation but self-regulation is rarely completely de-coupled from public authority. Instead, public authority is activated to solidify self-regulatory arrangements across the different stages of the policy process. 相似文献
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Tony H. Grubesic 《Journal of Quantitative Criminology》2006,22(1):77-105
One of the fundamental challenges in crime mapping and analysis is pattern recognition. Efforts and methods to detect crime
hot-spots, or geographic areas of elevated criminal activity, are wide ranging. For aggregate data, such as total crime events
in a census tract(s), measures of spatial autocorrelation have proven useful. For disaggregate data (i.e. individual crime
events), kernel density smoothing and non-hierarchical cluster analysis (e.g. k-means), are widely used. Non-hierarchical techniques are particularly effective in delineating geographic space into areas
of higher or lower crime concentrations, because each observation is assigned to one and only one cluster. The resulting set
of partitions provides clear-cut spatial boundaries that can be used for hot-spot evaluation and interpretation. However,
the strength of non-hierarchical methods can also be viewed as a weakness. Although the hard-clustering of observations into
a set of discrete clusters is helpful, there are many cases where ambiguity exists in the data. In such cases, a more generalized
approach for hot-spot detection would be helpful. The purpose of this paper is to explore the use of a generalized partitioning
method known as fuzzy clustering for hot-spot detection. Functional and visual comparisons of fuzzy clustering and two hard-clustering
approaches (medoid and k-means), across a range of cluster values are analyzed. The empirical results suggest that a fuzzy clustering approach is
better equipped to handle intermediate cases and spatial outliers.
相似文献
Tony H. GrubesicEmail: |
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Tony Barnett 《公共行政管理与发展》1984,4(1):21-47
This paper identifies from studies made of specific schemes the major social and administrative problems confronting the improvement and extension of small-scale irrigation in Africa. The first section reviews the studies and notes the conclusions to be drawn from each separate one. Underlying these separate conclusions six general problems are identified and in the second section of the article each of these six is elaborated and discussed: the relation between the direct producer'S benefit and wider social benefits: problems of control, commitment to hierarchy, the working of production units, and how to learn from farmers in respect of water use; and finally the general problem of how to plan for the further change that follows after irrigation is introduced. 相似文献
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