party and alcohol

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ADDITIONS --------- This model was edited to add the effects of "alcohol" present at a party. Here, alcohol functions to lower inhibition and thus raise the tolarence level for members of the opposite sex. We add two variables: alcohol-amt and alcohol-consum. Alcohol-amt represents the total number of drinks available at the start of the party. Alcohol-consum represents the rate at which the drink are consumed. At each turn, if alcohol is available, each turtle will consume a set amount, ranging from 0 to 1, where 1 equals one drink. The tolarance level will then increase by 2*alcohol-consum. This is a rather arbitrary value I came up with, and one on which the model highly depends, so its something I will need to fine-tune. Once this happens, this model can be used to compare, say, a frat-party (very high consumption rate) to a more formal event, where the consumption is much lower. WHAT IS IT? ----------- This program models a cocktail party. The party is made up of groups of both men and women. The partygoers have a TOLERANCE that defines their comfort level with a group that has members of the opposite sex. If they are in a group that has a higher percentage of people of the opposite sex than their TOLERANCE allows, then they are considered "uncomfortable", and they leave that group to find another group. This action continues until everyone at the party is "comfortable" within their group. This model is based on the work of the pioneering economist Thomas Schelling. It is also described in: Resnick, M. & Wilensky, U. (1998). Diving into Complexity: Developing Probabilistic Decentralized Thinking through Role-Playing Activities. Journal of Learning Sciences, Vol. 7, No. 2. http://ccl.northwestern.edu/cm/papers/starpeople/ HOW TO USE IT ------------- To set the number of people at the party, use the NUMBER slider. To set the number of initial groups, use the NUM-GROUPS slider. To set the tolerance of the people for the opposite sex, use the TOLERANCE slider. If the TOLERANCE slider is set to 75, then each person will tolerate being in a group with less than or equal to 75% people of the opposite sex. If there are more than this, the person is uncomfortable, and he/she leaves the group and tries out an adjacent group. The SETUP button sets up all the people into random groups. The GO button sets the party in motion. You can use the STEP-ONCE button to make all uncomfortable partygoers move once. The SPEED slider can speed up or slow down the simulation. The MOVES monitor shows the number of times people move from their groups. The NUMBER-HAPPY monitor shows how many people are content and this value is dynamically graphed in the "happy partygoers" plot. The SHOW-COUNTS? switch displays (or hides) a turtle label which shows the number of people in the group. The counts are shown in gray for "single-sex" groups, white for mixed groups. The simulation ends when everyone is happy. The SINGLE-SEX-GROUPS monitor shows the number of single-sex groups and this value is dynamically plotted in the "single sex groups" plot. RUNNING the MODEL ----------------- THINGS TO NOTICE ---------------- At the end of the simulation (when everyone is happy), notice the number of single-sex groups. Is there an increase from their initial compositions? Is there a critical tolerance at which each group ends up being a single-sex group? Notice the difference in time it takes for all groups to be comfortable depending upon the tolerance. THINGS TO TRY ------------- See how many mixed groups (not a single-sex group) you can get. Use the STEP-ONCE button, and experiment with different tolerances. Watch how one unhappy person can disrupt the stability of other groups. Is it possible to have an initial grouping such that the party is never completely content? (i.e. the model never terminates) Observe real parties. Is this model descriptive of real social settings? What tolerances would model the people in the real party? EXTENDING THE MODEL ------------------- Add another dimension to the model. Instead of male/female, try a trait that has more than two types, like race or religion. You can use BREEDS to implement that. Allow each BREED of person to have their own tolerance. Complicate the tolerance rules: For example, the tolerance could go up as long as there are at least 2 of one BREED. Allow groups to subdivide, instead of finding new groups. Set a maximum group size, so that if there are too many people in the group, they become unhappy. NETLOGO FEATURES ----------------- Notice the use of the "mod" function with a portion of the "screen-size" to space out the groups evenly. Setting up the groups in this manner allows for easy movement from group to group. Note also the use of the seriality of turtle execution for spreading out the turtles. Knowing that lower numbered turtles execute first enables this code to align the labels in the SHOW-COUNTS option. RELATED MODELS --------------- Segregation CREDITS AND REFERENCES ---------------------- Schelling, T. (1978). Micro-motives and Macro-Behavior. New York: Norton. Resnick, M. & Wilensky, U. (1998). Diving into Complexity: Developing Probabilistic Decentralized Thinking through Role-Playing Activities. Journal of Learning Sciences, Vol. 7, No. 2. To refer to this model in academic publications, please use: Wilensky, U. (1997). NetLogo Party model. http://ccl.northwestern.edu/netlogo/models/Party. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.