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United States

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ABOUT MEASURES OF EXPOSURE

Exposure is an additional way of describing the relationship between races. Unlike the dissimilarity index , which is a comparison of the degree of segregation between two groups, when we consider exposure we examine how the composition of the average metro area (or city) resident's neighborhood varies according to that person's race. Broadly speaking, exposure measures a given group's exposure to all racial groups, including itself, in the form a weighted average depicting the racial composition of the neighborhood of the average person of a given race. This can then be compared to the racial distribution for the city or metro area as a whole in order to examine whether races are relatively evenly spread out over the city or, conversely, clustered into neighborhoods where one racial group tends to be disproportionately represented while others are underrepresented.

In the table below, the first five columns represent the average racial composition of the neighborhood of a person of a given race. The rightmost column shows the racial composition of the metro area or city as a whole.

Under conditions of perfect integration, the racial distribution for a given neighborhood or census block will be the same as for the city as a whole. Typically, however, this is not the case. A more likely scenario is the one described in the graphic above, where white residents tend to live in neighborhoods in which there are a disproportionate number of whites, black residents tend to live in neighborhoods where there are disproportionate numbers of blacks and so on. This means that, in most cases, the exposure of whites to whites and of blacks to blacks will be higher than the degree of exposure suggested by the total metro racial distribution. At the same time, the exposure of whites to blacks and other minorities will often be lower than the degree suggested by the total metro racial distrubution.

For example, consider a hypothetical city that has 1500 white residents and 500 black residents for a racial distribution of 75% white and 25% black.

The city is then divided into two equally sized neighborhoods. 900 whites and 100 blacks live in the first neighborhood, while 600 whites and 400 blacks live in the second neighborhood. The racial composition of the first neighborhood is 90% while and 10% black, and the racial composition of the second neighborhood is 60% white and 40% black.

The exposure measures used on CensusScope.org take into account two factors: first, what portion of the metropolitan area's total population of a given racial group lives in a specific neighborhood, and second, the racial makeup of that neighborhood. The concentration of the given racial group in a neighborhood affects how heavily the racial composition of that neighborhood will be weighted when calculating the exposure index for the metro as a whole.

In our example, 60% of the total white population has the experience of living in a neighborhood that is 10% black, and 40% of the white population has the experience of living in a neighborhood that is 40% black.

To calculate exposure, we take into account the experiences of the entire white population, while weighting the experiences according to what percent of the white population has them. The more people who have a given experience, the more strongly it will be weighted in the exposure index. In our instance, since fully 60% of the white population lives in a neighborhood that is 10% black, that will be weighted more heavily in the index than the experience of the other 40% of the white population who live in a neighborhood that is 40% black. The average white person (who represents no single individual, but rather a composite of the total white population) in our hypothetical city lives in a neighborhood that is 22% black.

Since exposure paints a complete picture of the racial makeup of a neighborhood, they will always sum to 100%, and can include as many racial or ethnic groups as desired.

Exposure between two groups can be derived using the following formula:


where P1 = city -wide population of Group 1
P1i = neighborhood i population of Group 1
P2i = neighborhood i population of Group 2
Ti = neighborhood i total population
n = number of neighborhoods in city