What type of scale is a researcher using when categorizing individuals by sex, race, and political party affiliation?

The scale utilized when categorizing individuals by attributes such as sex, race, and political party affiliation is known as a nominal scale. This type of scale is specifically designed for labeling variables without any quantitative value or order. In essence, it classifies data into distinct categories that do not have a particular sequence or ranking. Each category is exclusive, meaning that an individual can only belong to one category within a given characteristic at a time.

For example, when distinguishing between different political parties, an individual may identify as either a Democrat, Republican, or Independent, but not simultaneously as more than one. Similarly, when addressing race, categories such as Asian, Black, White, or Hispanic are determined separately without implying any hierarchy among them. The nominal scale is fundamental in demographic and social research, where the focus is on the grouping of individuals into characteristic-defined categories rather than measurement along a continuum.

The other scales mentioned serve different purposes: an ordinal scale would involve rankings where order matters, a Likert scale measures attitudes or opinions usually on a spectrum, and an interval scale incorporates both order and a consistent scale of measurement between values. These distinctions clarify how nominal scales play a crucial role in foundational data categorization in research.