Two unrelated motivations, fuzzy semantics and data outliers, converge on the same transformation.

Evidence

Interestingly enough, this outlier fix produces basically the S-curve default of fuzzy logic. The popular min-max standardization with “outlier correction” (i.e., cutting off the top and bottom 2–5 percent) produces the fuzzy-logic default S-curve transformation; however, the route to that transformation is radically different: it is not semantics but data outlier problems. — Gary Goertz, Social Science Concepts and Measurement, 881

Categorization

• XREF: Echoes the concept-measurement link running through this book: how you define a concept and how you fix a scale are supposed to be independent, yet here they intersect by accident.
• CANDY: A genuinely nerdy convergences fact: statisticians correcting outliers and fuzzy-logic theorists defining membership land on the same S-curve without ever talking.