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Quetelet, Adolphe: Explaining Crime Through Statistical and Cartographic Techniques

Adolphe Quetelet was one of the first to explore official data on populations and crime. He is best known in criminology for his application of statistics and maps to describe crime patterns and trends in locations and the characteristics of offenders (using the term social mechanics). His important findings regarding the spatiotemporal distribution of crime provide the foundation for criminologist's interest in crime and place. Finally, as Terence Morris notes, his shift in emphasis from criminal motivation to crime as primarily a socioeconomic phenomenon with individual behavior as one element set the stage for the development of opportunity-based theories of crime such as routine activity theory and environmental criminology.

Quetelet in Context

Quetelet made his contributions to criminology before the discipline officially existed. He was born in Belgium and worked in 1820s France/Belgium during a period of social unrest that culminated in the French Revolution. When he began his career, information on social phenomena was almost nonexistent. Paul Lazarsfeld notes that two major barriers to coordinated, state-sponsored data collection existed: a populace who viewed attempts to conduct a census as precursors to increased taxes, and governments who treated any data about their population as a military secret. The French Revolution served as a turning point for these concerns. As some of the revolutionary governments came into power, the public was given access to census data. The application of statistics to social data was in its infancy in the social sciences, and research on criminal behavior was conducted via description rather than measurement. This was the context in which Quetelet's ideas were formed.

As a young man, Quetelet was interested in the arts and literature. At approximately 20, his interests took an abrupt turn when he met a mathematician who influenced him to study mathematics. After receiving his doctorate, Quetelet began to teach mathematics and became interested in starting an astronomical observatory in Brussels. In 1923, he was sent to Paris to learn what equipment would be needed for the observatory. While in Paris, he met Joseph Fourier and Pierre-Simon Laplace, two French mathematicians, and learned of their work with probability theory. Both these mentors had previously worked with social data in addition to astronomical data. Quetelet immediately began to think about how he could apply statistics to the measurement of the human body. From these efforts, he developed the body mass index (BMI) for measuring obesity which is still used today. The finding of a regularity measure across individuals set the stage for his application of statistics to social data.

Applying Statistics to Social Phenomena

Quetelet believed that general causes could be identified for human behavior just as they were used to identify laws for physical behavior. His involvement in the planning of the Belgian population census provided the basis for his explorations of population and crime statistics. In the course of investigating social data from the census, he began to notice patterns in both the rates and the distribution of characteristics across a population. The distribution closely resembled the error distributions that he had learned about from Fourier and Laplace. He began to apply the law of error being used to measure physical phenomena in astronomy to social characteristics. In doing so, he became the first to apply probability theory to social phenomena. As a result of this application he also recognized the power of using the normal curve to understand empirical distributions rather than as only an error law.

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