threeclass

Threeclass is a term used across disciplines to denote a three-category classification scheme. It can describe a tri-partite social stratification, a three-label data classification, or a market segmentation approach, depending on context.

In sociology and political economy, threeclass refers to a tripartite model of social stratification consisting of upper, middle, and lower classes. Proponents argue that this framework captures important gradations in wealth, education, occupation, and life chances beyond a simple two-class dichotomy. Class boundaries are influenced by mobility, institutions, and historical period, and the model is used in empirical studies to analyze inequality, political behavior, and social reproduction. Critics contend that real societies exhibit more complex stratification, with subgroups and fluid boundaries, and that class identity is entangled with race, gender, and ethnicity.

In data science and machine learning, threeclass denotes a multiclass classification task with three distinct labels. It contrasts with binary classification and with higher-order multi-class problems. Common algorithms include logistic regression, support vector machines, decision trees, and neural networks, often evaluated with metrics such as accuracy, precision, recall, and F1 score. The concept is illustrated by datasets that inherently have three outcomes, such as ternary sentiment classes or the iris dataset.

In marketing and demographic analysis, threeclass can denote a tri-level segmentation such as high-, middle-, and low-income groups or consumer classes. This framing is used to tailor products, pricing, and communications and may be derived from clustering analyses, income data, or psychographic indicators. Critics warn that segmentation can oversimplify behavior and that labels may stigmatize groups.