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WHAT IS IT?
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How does one go about trying to reduce gun-related crime in society? This model shows that figuring out the way forward is not at all simple because society is a complex system. Both the pro and anti-gun lobbies have been known to fall into single-factor thinking and other fallacies in trying to win over public opinion. Classic examples are "guns do not kill people, people kill people" and "ban guns and the crime rate will go down." Both claims downplay important ingredients in the criminal mix. Guns _and_ human aggression and a lot else besides affect crime. There are no quick fixes. In this model the user can play the role of the State or social engineer and even God to see what effect varying about a dozen factors and sub-factors has on homicide levels. Even with all these factors I hesitate to call "Guns and Moses" a model because it is too simple. Perhaps "dynamic illustration" would be better. The point is that if single-factor thinking is so demonstrably inadequate here, how much more so is it in trying to understand society and how to fix its problems.
HOW IT WORKS
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This section could explain what rules the agents use to create the overall behavior of the model.
There are two kinds of agents - citizens and gunshops. Citizens acquire guns from gunshops. Gunshops are of two sorts - legal and illegal (the blackmarket). Two citizens that land on the same patch will engage each other. The outcome of their engagement depends on several variables as outlined in the next section.
HOW TO USE IT
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Pretend you are the state or a social engineer. Your job is to try and reduce the homicide levels in a population of citizens by moving the various sliders. There are some trivial (and impractical solutions in real life) such as eliminating all weapons. Make the task challenging for yourself by allowing a supply of legal and illegal guns.
Here are descriptions of the sliders:
mean-gun-competence - ability to use a gun follows a normal curve. This slider sets the mean.
gun-competence-spread - sets the standard deviation.
mean-agression - how trigger-happy the population is follows a normal curve.
aggression-threshold - determines who are baddies and goodies. If a citizen's aggression is greater than this threshold it is a baddy. If it is less than or equal to this threshold it is a goody. Goodies never attack goodies or baddies without a gun. Baddies will attack anyone.
attack-threshold - if the square root of the product of the aggression of the two citizen is equal to or above this threshold then the citizens will attack each other. The citizen with the greater product of gun-competence (ability to use a gun) and aggression (willingness to use it) is the winner. Bad citizens can steal guns from their victims. Good citizens can confiscate guns from bad citizens.
intelligence - when set high baddies are aware of the proportion of initial legal guns and are less likely to attack citizenss.
demand-for-guns - sets the proportion of citizens that want a gun.
gun-competence-threshold - If the appropriate gun-eligibility-criterion is set the gun-competence of a citizen must be equal to or greater than this threshold for a good-citizen to be able to acquire a gun from a legal gunshop. Any bad citizens can acquire guns from illegal gunshops.
show-citizen-parameter - agents are colour-coded to reflect the magnitude of various variables. The darker the colour the higher the value of the variable.
police-mean-aggression - how trigger-happy the police are. Note: police never shoot unarmed bad citizens.
legal-gun-availability - sets the number of legal gunshops. Good citizens deposit extra guns here. If legal-gun-availability is greater than the number of legal guns, the number of legal guns is automatically reset to legal-gun-availability.
illegal-gun-availability - sets the number of illegal gunshops. Bad citizens deposit extra guns here. If illegal-gun-availability is greater than the number of illegal guns, the number of illegal guns is automatically reset to illegal-gun-availability.
initial-legal-guns - sets the number of legal guns.
initial-illegal-guns - sets the number of illegal guns
firepower - sets the calibre of the gun. At 100 a single gunshot kills. At 1 it takes 100 shots to kill. At the lower end of this spectrum the "gun" acts more like a knife.
illegal-guns-destroyed - if set police destroy the guns they acquire from bad citizens. Otherwise the guns are deposited at legal gunshops.
gun-eligibility-criterion - sets the conditions under which a _good_ citizen can own a gun.
THINGS TO TRY
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Set the sliders to the following values. Record the non-aggressive-deaths and the number of illegal guns. Now repeat the experiment but set the gun-elegibility-criterion to "both." What do expect to find regarding non-aggressive-deaths and the number of illegal guns? Can you explain the results?
gun-competence-spread 10
no-of-police 0
police-gun-competence n/a
aggression-spread 10
mean-gun-competence 50
initial-illegal-guns 50
illegal-guns-destroyed? FALSE
demand-for-guns 100
end-experiment 100
mean-aggression 49
initial-legal-guns 50
show-citizen-parameter "guns"
aggression-threshold 50
legal-gun-availability 20
no-of-citizens 600
firepower 25
police-aggression-spread n/a
attack-threshold n/a
illegal-gun-availability 20
gun-competence-threshold n/a
police-mean-aggression n/a
gun-elegibility-criterion "none"
How should one reduce the homicide rate against law-abiding citizens? Ban legal guns? If you try this and set intelligence to moderate you will see that law-abiding citizens are disadvantaged. Why? On the other hand if you allow just any law-abiding citizen to have a gun, law-abiding citizens are again disadvantaged? Why? A good citizen that is unable or unwilling to use a gun makes the gun potentially more available for bad citizens to use on other citizens. There is a conflict of interest between the good citizen who wants the freedom to own a gun to protect himself or herself but cannot and the state that has the responsibility to protect citizens in general. Should this individual's right to own a gun be curtailed for the greater good?
There are some important factors that you, the user, representing the state have control over such as the size and competence of the police force and the conditions under which legal guns can be sold. These are not the only factors there are. After setup there are other very important matters the state has little or no control such as human aggression and demand for guns. Rabbi Jonathon Sacks puts it way. "The more law is inscribed upon our hearts, the less it needs to be policed in the streets." (Ignoring the spiritual is also a kind of single-factor thinking). What could be done to motivate the agents against aggression without violating their independence as agents? Somehow you would need to persuade them without any coercion that non-aggression is the better way. Since the agents are not conscious this is not really open to us. However, we could model this as best we can by giving each agent a variable "openness" which determines how easily the agent can be persuaded into non-aggression and becoming a persuader. We can also allow chance to play a role in determining how successful a particular encounter is. Then, the most coercive thing you would need to do as the user is to take an agent and convert them into a persuader. You can do this by left clicking on an individual. To simplify things in this model police cannot become persuaders.
In doing this you are "playing God" much as God did in giving Moses the Ten Commandments on Mount Sinai. As great a leader as Moses was, he was still human and flawed. He had murdered an Egyptian and God forbade him from entering the promised land because of a lack of trust in Him (Numbers 20:12). The world had to wait for a better way and it came when the God the Perfect Persuader injected Himself into the world as Jesus. Jesus Christ's greatest act of persuasion came when He died on the cross. He showed that the greatest act of power was not through a gun, but through the powerlessness of death on the cross. This great love-act has melted the hearts of millions and converted them into pursuing change through love rather than power. There is no question that a gun can stop a bad citizen from hurting you - but Jesus stops bad citizens by making them into good citizens. Actually the Jesus way is superior because converted bad citizens can spiritually reproduce good citizens. Jesus does better than eliminating the bad; He produces the good. Of course the Jesus way is not coercive; it depends on the willingness of agents to respond and they may not. For those that do not we still need the State. The Jesus way does not do away with the need for the State. The Jesus way shows us a better way that will be fully realised in the next life when God's kingdom is fully come. The Jesus way can be activated by simply injecting the Persuader into the model. Then sit back and watch how the Persuader persuades other agents to become persuaders.
THINGS TO NOTICE
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The steeper the curve in the aggressive-deaths vs non-aggressive-deaths graph, the greater the overall homicide rate. This can be used to guage the effectiveness of your homicide-reducing strategies. Becoming a persuader does not guarantee the agent's personal safety. What it does is help the community become a little safer. Despite persuaders being individually imperfect (becoming a persuader leads to a reduction not an elimination of aggression) having persuaders in the model does reduce the overall homicide rate.
RELATED MODELS
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MetemorphoGenesis also shows how counter-intuitive phenomena can emerge out of a complex system. In this case the apparent design of metamorphosis as a successful strategy for finding rich but ephemeral food sources emerges quite naturally through evolution - natural selection acting upon inheritable variation. Metamorphosis is written in Starlogo.
Michael D Makowsky argues that history may be a very important factor in crime. His CAMSIM is a very interesting Netlogo model that shows how simulations can integrate theory across disciplines.
CREDITS AND REFERENCES
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Guns and Moses can be found on my website: www.mikelanderson.com
Special thank-you to Uri Wilensky and his team for Netlogo. See Wilensky, U. (1999). NetLogo. http:// ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. for information and download.