ENVIRONMENTAL-POLICY INDICATORS - A SYSTEMS-MODEL

被引:3
作者
CUMMINGS, LE [1 ]
CAYER, NJ [1 ]
机构
[1] ARIZONA STATE UNIV,SCH PUBL AFFAIRS,TEMPE,AZ 85287
关键词
ENVIRONMENTAL POLICY; POLICY INDICATORS; POPULATION CHANGE; PROBLEM SEVERITY; SOLID WASTE MANAGEMENT; SYSTEMS MODEL;
D O I
10.1007/BF02393727
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This article describes and tests a systems theory-based policy indicators model. The framework is used to examine propositions about linkages between states' ecological-spatial characteristics and subsequent selected solid waste management (SWM) -related environmental policies. It was hypothesized that state characteristics of: (1) population density (used as a garbage-per-land area index), (2) population convergence within urban areas, and (3) percent population change in the interval 1980-1985, could jointly explain state variation in both the number and the vigor of SWM policy outputs. Greater levels of spatial pressure were proposed to be related directly to more numerous, more convincing policies. Proposals are grounded in the literature of organizational search theory, crisis stimulation, and technological pressure. Results revealed that the sociospatial model in fact could explain a reasonable proportion of policy variation across states. However, not all hypotheses are supported. Population change shows an indirect, rather than the anticipated direct, relationship with policy output levels. In addition, when used in the model as a pollution intensity index, population density failed to contribute significantly to an explanation of differences in state SWM policy levels. The analysis raises questions about changes occurring over time in the nature and direction of linkages between sociospatial measures and policy responses. This study suggests that strengthening policy indicator models may require questioning key assumptions and theoretical bases, conducting longitudinal studies, and factoring in political, economic, and other policy environment forces.
引用
收藏
页码:655 / 667
页数:13
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