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Within sociology, there are two kinds of aggregates that are commonly used: the social aggregate and aggregate data. The first is simply a collection of people who happen to be in the same place at the same time, and the second refers to when we use summary statistics like averages to show something about a population or a social trend.
The Social Aggregate
A social aggregate is a collection of people who are in the same place at the same time, but who otherwise do not necessarily have anything in common, and who may not interact with each other. A social aggregate is different from a social group, which refers to two or more people who interact regularly and who have things in common, like a romantic couple, a family, friends, classmates, or coworkers, among others. A social aggregate is also different from a social category, which refers to a group of people defined by a shared social characteristic, like gender, race, ethnicity, nationality, age, class, etc.
Every day we become part of social aggregates, like when we walk down a crowded sidewalk, eat in a restaurant, ride public transit with other passengers, and shop in stores. The only thing that binds them together is physical proximity.
Social aggregates sometimes figure into sociology when researchers use a convenience sample to carry out a research project. They are also present in the work of sociologists who conduct participant observation or ethnographic research. For example, a researcher studying what happens in a particular retail setting might take note of the customers present, and document their demographic makeup by age, race, class, gender, etc., in order to provide a description of the social aggregate that shops at that store.
Using Aggregate Data
The more common form of an aggregate in sociology is aggregate data. This refers to when social scientists use summary statistics to describe a group or a social trend. The most common type of aggregate data is an average (mean, median, and mode), which allows us to understand something about a group, rather than considering data that represents specific individuals.
Median household income is among the most commonly used forms of aggregate data within the social sciences. This figure represents the household income that sits exactly in the middle of the household income spectrum. Social scientists often look at changes in median household income over time in order to see long-term economic trends at the household level. We also use aggregate data to examine differences among groups, like the change over time in median household income, depending on one's level of education. Looking at an aggregate data trend like this, we see that the economic value of a college degree relative to a high school degree is much greater today than it was in the 1960s.
Another common use of aggregate data in social sciences is tracking income by gender and race. Most readers are probably familiar with the concept of the wage gap, which refers to the historical fact that women on average earn less than men and that people of color in the U.S. earn less than white people. This type of research is produced using aggregate data that shows averages of hourly, weekly, and annual earnings by race and gender, and it proves that despite legalized equality, interpersonal discrimination on the basis of gender and race still works to create an unequal society.
Updated by Nicki Lisa Cole, Ph.D.