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We treat “the average human” as if it were a real, measurable entity —
a statistical center, a bell-shaped curve, a stable point around which everything clusters. But this assumption comes from our models, not from the world itself. Nearly all real-world systems — biological, cognitive, economic, technological, and computational — follow heavy-tailed distributions, not Gaussian ones.
Variance doesn’t contract toward the middle; it expands outward.
Outliers are not “rare exceptions.”
They are the structure. The belief in an “average human” emerged because Gaussian models are mathematically convenient, politically comfortable, and easy to teach —
not because they describe reality. When a system is embedded inside a larger uncontrolled environment, collapse and extreme dispersion are required, not accidental.
This is the foundation of RCC:
a geometric explanation for why long-range planning fails,
why drift accumulates,
and why human and model behavior doesn’t converge toward a center. If someone knows an actually embedded system that maintains stability without external scaffolding, I’m interested. |