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DOCA.1.CHR:6 - Bias-Annotation
- Score realism: a number can feel more objective than its method, scale, weighting, and uncertainty warrant.
- Maturity ladder bias: one ordered label invites a universal sequence and higher-is-better assumption.
- Human transfer bias: person learning and capability measures do not characterize organizations, AI arrangements, or engineered systems.
- Architecture projection: architecture characteristics are tempting general quality labels; use them only when architecture is the bearer.
- Available-data bias: easily measured coordinates can crowd out protected or distributional consequences that matter more.
- Benefit-only selection: desired result coordinates can hide resources, affected Systems, transition burdens, and option losses.
- Unknown-to-zero bias: missing evidence is neither absence nor a favorable baseline.
- Form completion bias: a full table does not supply qualified measurements or direct-owner conclusions.