Temporal Patterns for Burglar Alarms and Police-coded Burglaries

Date

2020-08

Authors

Rothstein, Stephan J.

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Abstract

Burglary is one of the most feared crimes. In addition to the cost of the stolen property, burglary may be viewed by the victim as an invasion of their personal space. This causes more emotional trauma for the victim than the value of the items stolen can represent. Criminologists and police officers study burglaries to help reduce the number and their impact. Research has revealed several factors that can affect the odds of being burglarized. No one knows exactly when burglaries occur. The best current method for estimating when burglaries occur is to use the aoristic signature of a series of burglaries, imputing more specific times from time ranges. This allows a researcher to estimate when burglaries are actually occurring. Burglar alarms are also important as manifestations of the fear of crime and as attempts to reduce crime. As the fear of crime has increased the number of burglar alarms has increased also. Along with the increase in alarms came an increase in alarm calls to police, a significantly high number of which are probable false alarms. Some estimates state that 98% of the calls to police for burglar alarms were for false alarms. Police often know exactly when alarms occur even though they do not know exactly when the burglaries themselves occur. This dissertation considers that the timing patterns for alarm occurrence might provide a window into the timing patterns by which burglaries themselves occur. The researcher examines and compares detailed patterns for alarms as well as other evidence of burglary timing, including burglary events coded by police as having occurred. Our central goal is to learn the similarity or dissimilarity between temporal patterns in burglar alarms and coded burglaries.

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Keywords

Commercial burglary, Residential burglary, Burglar alarm, Temporal pattern, Occurrence time

Citation

Rothstein, S. J. (2020). Temporal patterns for burglar alarms and police-coded burglaries</i> (Unpublished dissertation). Texas State University, San Marcos, Texas.

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