Binary Evaluation

Binary evaluation judges something as pass (1) or fail (0) rather than scoring its degree of goodness. CF reaches this from a math problem: combining factors from different dimensions. You cannot add unlike terms (3 acres + 8 hours has no sum), and multiplying arbitrary factors yields meaningless multi-dimensional units like gram-second-meter. The exception is binary factors. Multiply 1s and 0s and the result is meaningful: every factor passed, or at least one failed. No quantity of passes cancels a single zero — exactly the multiplication of binaries that captures how a decisive flaw sinks an option.

The conversion step is the leverage. For any analog dimension you ask a yes/no question — chiefly “is it good enough for my goal?” — which locates a breakpoint and collapses the spectrum to pass/fail. This loses information deliberately; it is one-way simplifying, not the symmetric, made-up unit conversion that weighted scoring requires.

CF’s specific take ties this to epistemology. A passing factor means no known error against the goal; the idea is non-refuted rather than scored. This is CF’s replacement for strong-vs-weak argument strength, extending binary epistemology into decision-making and rooted in Popper’s Critical Rationalism. It opposes the maximizer’s drive to optimize every detail; instead it is a satisficer stance — most factors carry excess capacity and only need to clear a breakpoint. CF rejects the pro/con list habit of summing pluses and minuses, while embracing Goldratt’s variant: solve every con, then go.