In this study, the process of burglars' specialisation was examined. 15 sub-categories of burglaries committed by 3,066 burglars were analysed, using a thematic approach. The result of an SSA-I showed that four themes existed in the structure of burglary: 'residential', 'commercial', 'public', and 'industrial/storage'. Also it was found that 'res- idential' and 'commercial' burglaries were the most distinct from each other, providing for two dominant foci for burglaries. The results of POSA also confirmed that most bur- glars specialised in either 'residential' or 'commercial' burglaries. Few were specialised in 'public' or 'industrial/storage' burglaries. In addition, the number of people who spe- cialised in commercial burglaries decreased with the increase of burgling experiences. The psychological processes underlying burglars' specialisation in one theme, or shift from one to another, are discussed. This study shows that the thematic approach offers a method of studying the multidimensional nature of burglars' psychological processes of specialisation.
This note examines the relationship between individual burglary and individual burglar characteristics. The primary contribution of this work is the development of a practical prediction model designed to assist in burglary investigations. By using various statistical techniques, a number of discriminating variables were identified, and subsequently clustered in such a fashion as to disclose a probability of occurrence figure based on ex post facto data. While the use of such a device may increase both the nature and extent of the information available to investigative officers, it is neither a substitute for the elements of probable cause nor a replacement for competent field investigation.
Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise".
For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid
measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities,
and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure
are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph
lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems
often require qualification because the test data on which they are based are of unsure quality. A common set of problems
in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the
degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.