A.19.USCM:8 - Common Anti‑Patterns and How to Avoid Them

• Hidden normalization inside scoring. Scoring silently normalizes or aligns measures. Avoid by making UNM explicit in choreography and keeping USCM’s Score admissibility‑only.

• Weighted sum across mixed or non-admissible scales. Treating “weights + sum” as universal. Avoid by requiring SCP+CSLC admissibility; if the scale operation is not scale-admissible, it is not admissible.

• Silent scalarization. Collapsing vector scores or partial orders into a single “overall score” via an untracked tie‑breaker. Avoid by leaving vector scores intact, and making scalarization an explicit declared commitment.

• Implicit scoring method (“we just use the standard formula”). The scoring method is assumed rather than declared and pinned. Avoid by requiring ScoringMethodDescriptionSlot and edition pinning in planned baseline; treat “identity scoring” (if ever needed) as an explicit method description, not a hidden default.

• Unknown → 0 coercion. Treating missing evidence as zero, false, or “good enough.” Avoid by tri‑state guards and explicit failure behavior, with auditable effective evidence policy.

• Shadow CG‑Spec. Hard‑coding admissibility rules inside a scoring method description instead of citing CGSpecSlot.SCP. Avoid by keeping admissibility in CG‑Spec and treating method details as wiring.

• Telemetry or publish leakage. Treating scoring as a reporting step. Avoid by keeping publish/telemetry outside suite closure and using the appropriate post-suite mechanisms.

• SlotKind drift. Renaming or re‑purposing slots across specializations or across mechanisms. Avoid by using the suite SlotKind lexicon and the ⊑/⊑⁺ discipline.