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This paper examines the relationship between perceived risk and experience. This research addresses the processes by which people learn about risk and choose among real life prospects with associated uncertainties, risks and benefits. By comparing the impact of acute risk events with that of chronic risk events on public perception of risk during and after the events, this research focuses on the learning processes that characterize what kinds of risk events alter the perception of risk. Comparing materialized hazards at existing facilities with the risks associated with potential facilities, this research addresses risk choices among real life prospects. This study uses a classic pre-post quasi-experimental design. Surveys conducted in the Spring of 1992 on perceived and acceptable risk in Odessa and La Porte, Texas were conducted prior to risk events. Respondents from that survey were re-interviewed in the Spring of 1993 after the risk events to form a panel design. This paper analyzes the affect of risk events on perceived risk and the implications of these experiences for public policy concerning technological risk. The empirical results suggest that the social processes that construct and maintain risk in the public eye are at least as important as, if not more important than, the physical and psychological dimensions of risk.

Neighborhood satisfaction is an important component of life satisfaction. As a contributor to life satisfaction, neighborhood satisfaction is influenced by individual and household background variables. However, there is limited understanding of how physical environments influence neighborhood satisfaction. This paper examines the effect of landscape components (structures, pavement, trees) and land use (residential, commercial, and open space) on neighborhood satisfaction. A survey of 276 respondents in College Station, Texas, was georeferenced and analyzed with landscape components and land-use GIS data. A structural equation model (SEM) examines the relationships among background variables, land use, landscape components, and neighborhood satisfaction simultaneously. Landscape components and land use were both found to play an important role in neighborhood satisfaction. Trees were found to have a positive effect on neighborhood satisfaction while structures were negative. Pavement, when commercial land use and structures in the SEM model were accounted for, shows a positive relationship with neighborhood satisfaction, suggesting that not all pavement is seen as undesirable. Commercial land use was also found to have a negative effect on neighborhood satisfaction, while background variables have no significant impact. The amount and arrangement of land uses and landscape components in neighborhoods may improve the well-being of residents by increasing their neighborhood satisfaction.

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