NetLogo User Community Models
Local Policing and Colorism, Bi-directional Influence
by Henry Smart, III (Submitted: 10/26/2017)
Note: This is a second version of the "Local Policing and Colorism" model which simulates the uni-directional influence (infection) of colorism. In this version of the model, the influence of colorism is bi-directional.
## WHAT IS IT?
This project models the policing behavior of two types of local-level police-agents based on the phenomena of colorism. Colorism is the preferential treatment of people with light skin and discrimination against people with dark skin (Russell et al 2013). The red police-agents (c-police) represent police officers whose policing decisions are influenced by colorism. The green police-agents (police) represent police officers whose policing decisions are not influenced by colorism. The three breeds of citizen-agents (darks, mediums, and lights) represent the complete skin color spectrum of the citizenry. The patch space is divided into three zones. The top zone, represented by white patches, is the ideal space-free society. The middle zone, represented by orange patches, is the detainment space. The detainment space represents all criminal justice functions except for incarceration. The bottom zone, represented by red patches, is the incarceration space. The incarceration space represents imprisonment. The simulation demonstrates how individual policing decisions, biased or not, might impact long-term incarceration outcomes. In addition, the simulation demonstrates the role that organizational socialization plays in the transference of colorism. The project draws from several streams of logic, which include colorism, risk perception and organizational socialization.
## HOW IT WORKS / HOW TO USE IT
Click the SETUP button to stage the model. Adjust the number of c-police, police, darks, mediums and lights to a preferred number. Ticks represent an abstract unit of time. Click the GO button to start the simulation with one time tick. Click the GO - continuous button to start the simulation with continuous time ticks. There are two major functions of the model, policing and the transfer of biased decision-making models.
At each tick, police randomly patrol the free space with an attempt to make an arrest. If there are no available citizens to arrest (citizens located one patch away from the officer in all four directions-north, south, east and west), the police officer will move to the next random patch/cell in the free space. At the time of an arrest, the citizen-agents that reside on the four neighboring patches (north, south, east and west) of the arresting officer will receive a charge. A (biased) c-police adds two (2) charges to a dark citizen's rap-sheet, one and a half (1.5) charge to a medium citizen's rap-sheet and one (1) charge to a light citizen's rap-sheet. A (fair) police adds one (1) charge to all four surrounding citizen-agents regardless of their skin color. Each time a citizen is arrested they will move to the detainment area for one tick and immediately return to a random patch/cell in the free space. Once a citizen's rap-sheet is equal to or goes beyond three (3) charges, the citizen will be permanently placed in the incarceration space.
TRANSFER OF BIASED ROUTINES / SOCIALIZATION
STOPPING THE MODEL
The model will stop running if the Go - continuous button is pressed a second time, or when the free space no longer contains citizen-agents.
## THINGS TO NOTICE
There are four plots to the right of activity area. The top plot tracks the number of (biased) c-police to (fair) police. As police-to-c-police conversion [transference] takes place, pay attention to what happens in the plight plots. You should see a strong correlation between the conversions and the plight of dark citizens and a moderate correlation between the conversions and medium citizens. However, this may not occur if some of the initial slider settings are skewed too far to the left or right.
The plight plot comparisons enable the detection of shifts in the free population and the incarcerated population. Take notice of the varied results.
## THINGS TO TRY
MODELING BASED ON THE U.S. POPULATION
THE TRANSFERENCE OF COLORISM
To model an equal starting point of fair and biased policing, set the c-police and police sliders to the same number (e.g., c-police = 20 and police = 20). Transference of colorism is somewhat easier to observe when there is an equal number of c-police and police.
## EXTENDING THE MODEL
This model was developed by a novice coder, so there is plenty of opportunity to extend the model. Firstly, coders are encouraged to flatten the code. In its current state, no bugs were detected, but a more concise code-set may add validity to the model.
In its current state, the model can only simulate a few theories. Coders should consider other theories, such as the effects of the "return to free society", the outcomes of fair policing but biased "return to free society" or any combination of the available policing and justice theories.
## RELATED MODELS
Those interested in the topic of colorism or population outcomes should also review the segregation model (http://ccl.northwestern.edu/netlogo/models/Segregation).
## CREDITS AND REFERENCES
Credit: Reese, Dean. YouTube, (2014) if then 3 in NetLogo.
Credit: Reese, Dean. YouTube, (2014) in-radius die in NetLogo.
Credit: Rand, W., Wilensky, U. (2007). NetLogo El Farol model.
Credit: Wilensky, U. (1997). NetLogo Segregation model.
Reference: Russell, K., Wilson, M., & Hall, R. (2013). The color complex (revised): The politics of skin color in a new millennium. Anchor.
Reference: Van Maanen, J. (1975). Police socialization: A longitudinal examination of
Reference: Lupton, D. (1999). Risk: key ideas. Risk: key ideas. Routledge.
Creation Date: 4/9/16
Notes: This model was designed using NetLogo 5.3.1. This second version of the model was created in response to feedback about the likelihood of fair-minded officers having a positive influence on affected police officers. If you use any portion of this model, please properly site the project and the author.
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