| Summary |
This thesis examines the adaptive reuse of historic textile mills in North Carolina. The decline of the textile industry, which employed over 300,000 North Carolinians at its peak, has left scores of mills abandoned on the state's landscape. Many of these abandoned mills possess value that derives from a combination of their architectural splendor, their cultural significance, and their ability to reduce environmental impacts when creatively reused. Historic textile mills within North Carolina are inventoried. This unique inventory includes the precise location of 611 historic mills, their current uses, and a host of site and situational factors that might affect the probability of reuse. Reused mills are statistically contrasted against abandoned mills using logistic regression and key situational factors that could affect investment decisions. The model correctly predicts the reuse of 87 percent of abandoned mills. The key predictors of mill reuse are: local age, ethnicity, educational attainment, poverty, distance to nearest stream, and location within a historic district. Analysis of errors indicates a troublesome frequency of false negatives, i.e., reused mills that are predicted to be abandoned. This is attributed to a lack of key site variables in the logistic model, e.g., structure size, lot size, and architectural quality. The model is then used to guide selection of abandoned mills that are good candidates for reuse. Each of these five candidates is found to have considerable reuse potential and this emphasizes the need to consider preservation over demolition. The inventory suffers from errors of omission, i.e., 80 percent of all historic mills are included. The inventory also suffers from possible errors of commission, i.e., a few mills might be inaccurately located or their current use misclassified. However, the inventory is unique in terms of its scope and quality. The false negatives can be reduced with measurement and inclusion of appropriate site characteristics. In sum, the approach developed here is transferable in terms of geography (other states) and sectors (other industries such as tobacco). This research is devoted to preserving the value of historic mills through their adaptive reuse. The inventory assembled and the modeling applied should prove useful in assisting with that goal. |
