CJ 340 Module Four Journal
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Southern New Hampshire University *
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340
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Law
Date
Jan 9, 2024
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docx
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"Predictive Policing: Leveraging Criminological Theories for Proactive Law Enforcement
Strategies"
The real-life example of predictive policing illustrates the application of criminological
theories in law enforcement, specifically the Routine Activity Theory. Predictive policing, as
discussed in the NIJ Journal’s article “Predictive Policing: The Future of Law Enforcement?” by
Beth Pearsall, involves taking data from various sources, analyzing it, and using the results to
anticipate, prevent, and respond more effectively to future crime.
With this technology, law enforcement agencies are becoming less reactive and more
proactive, shifting their focus from what has happened to what will happen. This aligns with the
principles of the Routine Activity Theory, which emphasizes the convergence of a motivated
offender, a suitable target, and the absence of a capable guardian.
The Los Angeles Police Department (LAPD), in collaboration with the National Institute
of Justice (NIJ), held a Predictive Policing Symposium in November 2009 to explore the policy
implications, privacy issues, and technology of predictive policing. Chief Charlie Beck of the
LAPD highlighted that predictive policing’s greatest benefit is the discovery of new or
previously unknown patterns and trends, analogous to Walmart identifying increased demand for
specific items before major weather events.
Two practical examples of predictive policing in action demonstrates its effectiveness:
1.
Reducing Random Gunfire in Richmond:
By analyzing historical data on random gunfire during New Year’s Even celebrations, the
Richmond, VA, police anticipated the time, location, and nature of future incidents.
Placing officers strategically resulted in a 47% decrease in random gunfire and a 246%
increase in weapons seized, saving $15,000 in personnel costs.
2.
Connecting Burglaries and Code Violations in Arlington, Texas:
The Arlington Police Department used data on residential burglaries to identify hot spots
and correlated them with areas exhibit code violations. This analysis revealed a
correlation between physical decay and residential burglaries. The department developed
a formula to identify characteristics of “fragile neighborhoods,” leading to more efficient
crime prevention efforts.
The effectiveness of these examples in preventing or reducing crime is evident through
the documented decreases in criminal activities and associated costs. Predictive policing,
informed by the Routine Activity Theory, allows law enforcement to allocate resources more
efficiently, improving safety outcomes.
However, it’s essential to consider potential concerns regarding privacy, civil rights, and
community trust. Transparency and community involvement are crucial aspects of successful
predictive policing implementations. As law enforcement agencies continue to refine their
approaches and addresses these concerns, predictive policing remains a powerful tool in the
evolution of policing strategies for the greater good.
Resources:
Pearsall, B. (2009, November). Predictive Policing: The Future of Law Enforcement?
NIJ
Journal
, Issue No. 266, 17-19.
https://mediaweb.saintleo.edu/courses/CRJ570/PredictivePolicing_Pearsall.pdf
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