Underrepresent

Underrepresent is a verb meaning to represent or include a proportion of a group or attribute that is smaller than its share in the relevant population or dataset. It is used in statistics, political science, and sociology to describe mismatches between actual presence and representation in surveys, samples, decision-making bodies, media, or other domains.

In data and research, underrepresentation can distort findings, bias estimates, and lead to decisions that do not reflect the needs of all groups. Causes include sampling bias, nonresponse, exclusion criteria, and insufficient data collection for certain populations. In governance, underrepresentation refers to groups having greater shares in the population than in elected or appointed positions, such as women, ethnic minorities, or people with disabilities, which can affect policy outcomes and legitimacy. In media, underrepresentation occurs when groups receive limited or narrow portrayals, reinforcing stereotypes and neglecting diverse perspectives.

Addressing underrepresentation involves methodological and structural approaches. Methodological measures include oversampling, weighting, stratified sampling, and targeted recruitment to ensure proportional or meaningful inclusion. Structural approaches include inclusive institutions, complementary data collection, and policies aimed at improving access and opportunities for underrepresented groups. Critics note that efforts like quotas or weighting can introduce new biases if not carefully designed, so transparency and ongoing evaluation are important.