Abstract

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The purpose of this quasi-experimental study was to determine whether the ratio of police safety incidents to the number of total police officers is greater for states that have a low ratio of police officers to citizens. An analysis of covariance (ANCOVA) approach was applied to answering this research question. The dichotomous independent variable of the study was officer location (high police-officer-to-citizen ratio state versus low police-officer-to-citizen ratio state); the dependent variable was the ratio of officer safety to the number of total police in a state; and the covariate was the rate of violent crime in the state.

Different states have different ratios of police officers to citizens. One possible consequence of fielding a relatively small number of police officers, relative to the size of a state’s population, is that officer safety will decline (Liederbach & Frank, 2006; Mastrofski, 1981; Parks, Mastrofski, DeJong, & Gray, 1999; Vila, 1996; Vila, Morrison, & Kenney, 2002; Violanti et al., 2012). When the ratio of police officers to citizens is lower, two natural consequences are for police officers to (a) work longer shifts and (b) cover larger areas. Both of these consequences are associated with decreased officer safety. Officers who work long shifts are likely to accumulate fatigue that could prevent them from exercising their best judgment in avoiding dangerous situations (Vila, 1996; Vila et al., 2002; Violanti et al., 2012), while officers who cover larger areas (whether in terms of geography or the number of citizens in a designated coverage area) also incur risk, because they are less likely to be highly familiar with the safety dynamics of their beats (Liederbach & Frank, 2006; Mastrofski, 1981; Parks et al., 1999). The purpose of this quasi-experimental study is to determine whether the ratio of police safety incidents to the number of total police officers is greater for states that have a low ratio of police officers to citizens.

Review of the Literature
Several empirical studies (Vila, 1996; Vila et al., 2002; Violanti et al., 2012) have found that (a) longer shifts are necessary when there are fewer available police officers; and (b) longer shifts are associated with consequences such as increased tiredness, decreased concentration, and decreased decision-making capabilities. Each of these consequences is associated with a heightened risk of danger to the police officer (Vila, 1996; Vila et al., 2002; Violanti et al., 2012). The empirical literature also contains numerous findings indicating that (a) when fewer police officers are available, each police officer has to cover larger beats; and (b) covering larger beats is associated with increased danger to the police officer, who is less able to develop familiarity with an enlarged beat (Liederbach & Frank, 2006; Mastrofski, 1981; Parks et al., 1999). Familiarity with a beat is needed to improve decision-making, which is an important component of police officer safety (Liederbach & Frank, 2006; Mastrofski, 1981; Parks et al., 1999).

Problem. Theory, Variables, and Hypothesis

Problem Statement
The practical problem addressed in the study is the large number of officer safety incidents in the United States. The academic problem addressed in the study is the lack of knowledge about whether—and to what extent—officer safety can be improved through increasing the ratio of police officers to citizens.

Theoretical Framework
The theoretical framework for the study consists of two theories. The fatigue theory suggests that officer safety incidents can be caused by the kind of tiredness that results when police officers have to work long shifts, as is more likely in states with a low ratio of police to citizens (Vila, 1996; Vila et al., 2002; Violanti et al., 2012). The familiarity theory suggests that officer safety incidents can be caused by assigning police officers to larger beats, which is more likely to happen in states with a low ratio of police to citizens (Liederbach & Frank, 2006; Mastrofski, 1981; Parks et al., 1999).

Independent Variable
The dichotomous independent variable of the study is officer location (high police-officer-to-citizen ratio state versus low police-officer-to-citizen ratio state). A high police-officer-to-citizen ratio state will be designated as a state that is at or above the 75th percentile for the ratio of police officers to citizens. A low police-officer-to-citizen ratio state will be designated as a state that is at or below the 25th percentile for the ratio of police officers to citizens. The independent variable will be named the police officer ratio.

Covariate
The covariate of the study is the violent crime ratio of a state, calculated as the number of violent crimes per 100,000 people in that state for 2015. The covariate will be named the violent crime ratio.

Dependent Variable
The dependent variable of the study is the ratio of officer safety to the number of total police in a state. The dependent variable will be named the officer safety ratio.

Hypothesis
The hypotheses of the study are as follows:
H10: There is not a statistically significant relationship between the police officer ratio and the officer safety ratio, after controlling for the violent crime ratio.
H10: There is a statistically significant relationship between the police officer ratio and the officer safety ratio, after controlling for the violent crime ratio.
The level of significance is .05. The hypothesis will be tested by running an ANCOVA including the variables listed above and determining whether the p value associated with the grouping variable (that of high police-officer-to-citizen ratio states versus low police-officer-to-citizen ratio states) is below .05. if the p value is below .05, then the null hypothesis of the study will be rejected, and the mean officer safety ratios of high police-officer-to-citizen ratio states and low police-officer-to-citizen ratio states will be compared to determine which is higher.

Research Design
The research design of the study is quasi-experimental. There is no random assignment in the study. The assignment is based on existing, real-world criteria—specifically, on the police officer ratio variable. As explained above, any state with a police-officer-to-citizen ratio at or above the 75th percentile will be assigned to the high police-officer-to-citizen ratio group, whereas any state with a police-officer-to-citizen ratio at or below the 25th percentile will be assigned to the low police-officer-to-citizen ratio group. An ANCOVA will be applied in the study because of the existence of a covariate (violent crime ratio).

Population and Sample
The population consists of all U.S. states. The sample will consist of all states’ police officer ratios, violent crime ratios, and officer safety ratios for 2015.

Data Collection
The data collection will for the study will be based on publically available records provided by the Federal Bureau of Investigation (FBI) (FBI, 2015). The FBI’s datasets include violent crime ratios for state. The FBI’s datasets also include information on the number of police officers per state and the number of police safety incidents by state, information that can be used to calculate the officer safety ratio. The U.S. Census Bureau (USCB, 2015) provides information on population by state, which, in conjunction with the FBI’s data on the number of police officers by state, can be used to calculate the police offer ratio. Once collected, the data will be analyzed in SPSS 20.0 statistical software.

    References
  • FBI. (2015). Police employee data. Retrieved from https://ucr.fbi.gov/crime-in-the-u.s/2011/crime-in-the-u.s.-2011/police-employee-data
  • Liederbach, J., & Frank, J. (2006). Policing the big beat: An observational study of county level patrol and comparisons to local small town and rural officers. Journal of Crime and Justice, 29(1), 21-44.
  • Mastrofski, S. (1981). Policing the beat: The impact of organizational scale on patrol officer behavior in urban residential neighborhoods. Journal of Criminal Justice, 9(5), 343-358.
  • Parks, R. B., Mastrofski, S. D., DeJong, C., & Gray, M. K. (1999). How officers spend their time with the community. Justice Quarterly, 16(3), 483-518.
  • USCB. (2015). Population and housing unit estimates. Retrieved from https://www.census.gov/programs-surveys/popest.html
  • Vila, B. (1996). Tired cops: Probable connections between fatigue and the performance, health and safety of patrol officers. American Journal of Police, 15(2), 51-92.
  • Vila, B., Morrison, G. B., & Kenney, D. J. (2002). Improving shift schedule and work-hour policies and practices to increase police officer performance, health, and safety. Police Quarterly, 5(1), 4-24.
  • Violanti, J. M., Fekedulegn, D., Andrew, M. E., Charles, L. E., Hartley, T. A., Vila, B., & Burchfiel, C. M. (2012). Shift work and the incidence of injury among police officers. American Journal of Industrial Medicine, 55(3), 217-227.