"Distinctive types of mobility are identified for the [U.S.] elderly, many of whom also move for traditional reasons. Using a longitudinal data set from adult residents in Rhode Island, univariate, chi square, and logit analyses indicate associations between sociodemographic characteristics of the elderly and their mobility behavior. Mobility for assistance reasons is associated with older age, unmarried status, higher previous mobility, and renter status. Mobility in preparation for aging (e.g., to an elderly complex) is more likely for unmarried, previously mobile residents. Out-of-state mobility to amenity destinations is not limited to the elderly, but younger, married, more affluent elderly were more likely to make such moves."
Using data from the 1983 Annual Housing Survey, we identified four reasons for moving, which corresponded to changes in later life and which were much more frequently mentioned by movers aged 55 and older than by younger movers. These included moves made for reasons of amenity, kinship, retirement, or widowhood. The rates at which elderly persons engaged in these different types of mobility varied with age, household composition, and other characteristics. Amenity and retirement moves most often ended in destinations in the South and the West, whereas kinship and widowhood moves occurred in all regions, but were more common among those moving to nonmetropolitan than to metropolitan areas.
Two qualitative case studies, one focusing on K‐12 teachers and the other on middle school students, explore key factors associated with using Geographic Information Systems in the classroom. In both studies, access to appropriate hardware is a critical barrier. Time is another critical barrier—time to learn the GIS software and time in the curriculum to incorporate GIS as a learning experience. In both case studies, learning the technology at the expense of learning spatial analysis was a danger, suggesting the need for conscious focus on the goal of using GIS to learn how to “do geography.”
Due to limited resources, publicly funded service programs need to operate efficiently. This paper demonstrates how a Spatial Decision Support System (SDSS) can be used to evaluate and enhance the performance of an existing service delivery program. Elements critical to the efficiency of service programs are enumerated. A meals-on-wheels (MOW) program in Connecticut is used as a case study to demonstrate the utility of the SDSS approach. Practical issues related to data sources and system adoption are discussed.
New England counties are grouped into categories using graphic displays of five decades of net migration rates for young and old elderly persons. Linear functions composed of social, economic, and geographic variables discriminate among the categories, yielding the following associations: positive rate counties are long-standing retirement and recreation areas; negative rate counties have large, old, declining cities; turnaround counties are nonmetropolitan counties with recently developed retirement/recreation facilities; miscellaneous counties include suburban counties with a temporary peak in net migration rates. The counties' patterns are relatively similar for young-old and old-old persons over the five decades.
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