numerilization
Numerilization is a term used in data science and qualitative research to describe the process of converting qualitative, symbolic, or non-numeric information into numerical form suitable for quantitative analysis. The term is not standardized and may be used differently across disciplines, but the core idea is to render information amenable to mathematical methods without necessarily changing its meaning.
Methods of numerilization vary with context. Common approaches include assigning ordinal ranks to ordered categories (for
Applications of numerilization include enabling statistical modeling, hypothesis testing, and machine learning across fields such as
Critics warn that numerilization can obscure meanings, introduce bias through arbitrary scales, and reduce subtle qualitative
See also: quantification, measurement theory, data encoding, feature engineering, ordinal scales, and sentiment analysis.