New Mexico Supercomputing Challenge

The Spread of Gang Activity in a Typical High School

Team: 97

School: Miyamura High

Area of Science: Social Science


Interim: Problem Definition:
Gang activity is a growing problem in middle to low income towns. If we can predict the growth and susceptibility of the student body, we may be able to find a pattern in gang affiliation which would allow us to prevent the growth and spread of such gangs. Over-all, we want a safe , education-based school for our fellow students across the state.
The goal of the project is to use real world statistics that have been taken from high schools across the state to ensure that the data is as accurate as it can be for the socio-economic system of New Mexico. Many sophisticated factors such as social groups, family affiliation, and peer-pressure will go into the code. Some factors may be left out, as we are trying to be very abstract in our programming while obtaining realistic results.
Problem Solution:
We will first find the ratio of gang member to non-gang in the school and use that to determine the amount of turtles needed to facilitate an accurate representation for gang members. We will then find a viable way to correlate the susceptibility to grades. After successfully representing the student body as a whole, we will create a model that shows how gangs can start with relatively small numbers, but can quickly spread, much like a disease, throughout a student body.
Progress to Date:
Data has been collected from our school, and requests are being prepared for others. We are in progress of writing a code which we can plug the numbers into later. Progress has been slow due to lack of resources and student confidentiality, which made us rethink our pre-write of the code itself. We expect progress to pick up after the semester, when resources become more available to us.
Expected Results:
We expect to see an initial rise in gang activity, followed by a general stability of the gang to non-gang ratio. Monitors and a plot will be used to track the data. Based on human behavioral patters, we expect to see a drop in activity over time as each individual grows to fit society. Our hypothesis may prove to be incorrect as gang membership is not completely predictable in this situation due to student confidentiality.

Team Members: Sean Campos-Jaramillo, Andres Escamilla, Jeremy Cadman, Aaron Wilson, TyNolan Martinez


Team Members:

  Sean Campos-Jaramillo
  TyNolan Martinez
  Aaron Wilson
  Andres Escamilla
  Jeremy Cadman

Sponsoring Teacher: Rowena Fiona Dolino

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