Underrepresent

To depict, portray, or account for something in an amount or proportion less than its true or expected significance, presence, or occurrence. This can apply to data, groups of people, ideas, or any element where the representation is not commensurate with its actual prevalence or importance. The act of underrepresenting often results in a skewed understanding, incomplete picture, or the marginalization of the subject in question, frequently occurring in statistical analysis, media, or political landscapes.

Underrepresent meaning with examples

• The study underrepresented the contributions of female scientists to the field, focusing primarily on male researchers, leading to a biased view of scientific progress. Consequently, the achievements and discoveries of many talented women were overshadowed, creating an incomplete and inaccurate record of historical developments. This imbalance prevented a complete understanding of how science evolved over time.
• The film, while attempting to be diverse, inadvertently underrepresented the nuance and depth of various cultures by relying on superficial stereotypes and tropes. This led to simplified portrayals and ultimately diminished the richness of the cultures it aimed to represent, thereby failing to accurately convey authentic cultural practices, history and experiences to audiences worldwide. This lack of complexity was a major criticism.
• The survey data underrepresented the opinions of rural communities, skewing the overall results and making it difficult to understand the national consensus on a particular policy. This oversight led to inaccurate conclusions and potentially flawed decision-making based on incomplete information about the attitudes of all relevant groups of people. Failing to account for this was problematic.
• The algorithm, designed to sort job applicants, underrepresented candidates from minority groups by inadvertently using biased parameters within the filtering process. Consequently, fewer qualified individuals from these backgrounds advanced in the application process. This discriminatory outcome highlights the need for fairness and transparency in automated decision-making and the evaluation of applicants.