Segregation Model

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Thomas Schelling's model of segregation is a classic study of the effects of local decisions on the global dynamics of housing segregation patterns. It describes the emergence of segregated areas or "ghettos". In the model residents are described as agents. Agents with mild preferences for same-type neighbors, but without preferences for segregated neighborhoods, can end up producing complete segregation. A small preference for one's neighbors to be of the same color could lead to total segregation and ghetto formation.

It is one of the first agent-based models at all, where agents represent people and agent interactions represent a socially relevant process. In 1971, Thomas Schelling published an article dealing with racial dynamics called "Models of Segregation". In this paper he showed that a small preference for one's neighbors to be of the same color could lead to total segregation. He used coins on graph paper to demonstrate his theory by placing pennies and nickels in different patterns on the "board" and then moving them one by one if they were in an "unhappy" situation. The positive feedback cycle of segregation - prejudice - in-group preference can be found in most human populations, with great variation in what are regarded as meaningful differences – gender, age, race, ethnicity, language, sexual preference, religion, etc. Once a cycle of separation-prejudice-discrimination-separation has begun, it has a self-sustaining momentum.

In the model, agents interact only locally, with their direct neighbors. Each agent agrees to stay in a neighborhood with people that are mainly of another color, on condition that there are at least 37,5% with the same color in the neighborhood. More specifically, Schelling uses the following rules:

  • an agent with one or two neighbors will try to move if there is not at least one neighbor of the same color
  • an agent with three to five neighbors needs at least two like him
  • an agent with six to eight wants at least three agents of the same colour


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