We have shown the problems resulting by housing low-income families with children in high-rise buildings. But one should not conclude from this that high-rises are not suitable for other life-style groups. For instance, elderly people, even those of low income, do very well in high-rise buildings—as long as the buildings are kept exclusively for the elderly.
Elderly people do not like walking stairs, and so appreciate an elevator building. Retired elderly often live away from their children, and so their elderly neighbors become their new extended family. At the push of an elevator button, they can have access to a hundred other families within a high-rise building.
If we also design the ground floor of an elderly high-rise as a communal and recreation area, we can create a security station at the building entry door which can be manned by elderly volunteers. If a problem arises, a push of a button summons the police. With the use of gates and fencing, the grounds surrounding their building can also be secured and defined for their exclusive use.
The lesson we can learn from this is that some of the high-rise stock we have inherited because it has proven unusable for welfare families with children may lend itself to conversion for the exclusive use of elderly.
However, we should not jump for joy too quickly. Many of our high-rise public housing projects in large cities like New York, Chicago, and Boston were built as 1000 unit agglomerations, and the need for such a concentration of elderly is, at present, just not there. Also, the community surrounding such a 1000 unit agglomeration will have been devastated—no place to be putting elderly. It would not be wise to convert one of ten high-rise buildings for elderly, while keeping the adjacent nine buildings for families with children. The elderly would be victimized and refuse to live in such an environment.
Finally, even when high-rises exist in isolation, the cost of converting a building made up of three bedroom apartments into one-bedroom units may be prohibitive.
Our Institute’s study of the Factors Influencing Crime and Instability in Federally-Assisted Housing (Newman, Franck 1980) involved forty-four moderate-income housing sites and twenty-nine public housing sites in three cities: Newark, St. Louis, and San Francisco. It used a path analysis to take into account the influence of other factors, including: socioeconomic characteristics, management effectiveness, quality of city police and security services, and form of ownership.
The results showed that two physical factors and two social factors accounted for most of the variation. The two physical factors were: the size of the development; and the number of families sharing common entries into a building. The two social factors were: the percentage of families on AFDC (the welfare program Aid to Families with Dependent Children); and the ratio of teenagers to adults. As public housing has become housing for the poorest-of-the-poor, the only variables that lend themselves to modification are the physical: project size and the number of apartments sharing common entries.
Project size is a measure of the overall concentration of low-income families in a project or cluster of projects. We found that the larger the concentration, the more residents felt isolated from the rest of society, and the greater their perceived differences. Project size affects stigmatization—as perceived both by the outside world and by the project residents themselves. The apathy that comes with stigmatization leads to neglect and withdrawal—first on the part of the residents, then by housing management, and finally by the municipal agencies that service the project: police, education, parks and recreation, refuse collection, and social services. A large project provides a continuous area for gangs to operate in—allowing even one gang or group of drug dealers to contaminate all of its public space.
The larger the number of units sharing common entries is a measure of how public are the interior corridors, elevators, and stairs. The more residents there are who have to share common areas, the more difficult it is to lay claim to them; the more difficult it is to distinguish other residents from intruders; and the more difficult it is to agree with other residents on the care and control of these areas.
The numbers within the brackets below show the amount of variation in residents’ behavior that is explained by building size. If the number is preceded by a minus, it means that an increase in building size has a negative effect on that behavior. In the case of residents’ use of public areas, for instance, the numbers in brackets mean that an increase of one unit in building size will cause a reduction of .50 of a unit in residents’ use of public areas. This demonstrates that building form has a very strong predictive capacity on public area use, independent of other factors that are also likely to predict it.
Building size has a statistically significant direct causal effect on residents’ behavior as follows:
i) use of public areas in their development (-.50)
ii) social interaction with their neighbors (-.31)
iii) sense of control over the interior and exterior public areas of their development (-.29).
Further results of our path analysis showed that building size has important causal effects on fear of crime (.38) and on community instability (.39), independent of socioeconomic, managerial, ownership, police, and guard service factors. Community instability is measured by apartment turnover and vacancy rates and by residents’ desire to move. However, as in the 1970 New York City Public Housing study discussed earlier, the findings from our study of moderate-income developments showed that the socioeconomic characteristics of residents also have strong causal effects on fear, instability, and crime.
Independent of other factors, the socioeconomic characteristics of residents have a total causal effect on fear of crime of .59; on community instability of .51; and on crimes against persons of .32. These findings can be interpreted as follows: a unit increase in the percent of AFDC families living in a development will produce .59 of a unit increase in fear of crime, and so on.
The data from the above analysis can be summarized in still another way by looking at the results of the regression analysis. The R2 is a sign used to represent the percent of variance in one factor that is predicted by all other factors acting together. The effects of building size, socioeconomic characteristics of residents, management performance, form of ownership, and police and guard service together produce: an R2 =.69 for fear (p <.001); an R2 =.67 for community instability (p <.001); and an R2 =.39 for crimes against persons (p <.05). Another way of stating these findings is that the combination of these factors predicts 69 percent of the variation in fear, for instance. But more important still, of all the factors in the predictive model, it is the socio-economic characteristics of residents and building size which together predict most of the variation in fear, instability, and crime.
End of Chapter One