We examine local government response to the COVID-19 pandemic in the United States utilizing a unique dataset created by the National League of Cities. The most common action by local governments was changing administrative procedures and implementing policies aimed at prevention or “flattening the curve”. The general public was the most common population target. In addition to detailing the most common local action types, policy areas, and population targets, we analyze local response based on the autonomy granted to local governments by states. We expected local governments with greater levels of autonomy would have a greater level of response; however, some local governments did not ‘behave’ as expected based on their degree of policymaking autonomy granted by state governments. Some states with higher levels of autonomy enacted relatively few local actions in response to the pandemic, whereas some with little autonomy engaged in considerable activity to address COVID-19.
A computer program to be used in interpreting factor analysis results has been written. Given a factor matrix and item descriptions, the program will produce, for each factor, a printed display of the factor loadings and descriptions of items which load significantly on the factor. The display for each factor may also include, for each item listed, a summary of the other factors on which the item loads significantly.MosT available factor analysis computer programs limit final output to a (rotated) factor matrix and, possibly, factor scores. One of the main deterrents to examining the many possible factor analysis solutions for a group of data is the clerical support required to consolidate the descriptions of the items loading on the factors. The purpose of this program is to eliminate the necessity for that type of support and to enable the user to interpret the factor matrix and name the factors with a minimum of time and effort.
InputInput for this program consists of the following three parts: 1. A title card and a control card describing the characteristics of the factor matrix and item descriptions. 2. Item descriptions.3. Factor matrix.
OutputOutput includes, for each factor, a list of the items which load significantly on that factor, i.e., with a factor loading greater in
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