C.2.2:8 - Common Anti-Patterns and How to Avoid Them
Informative; non-binding.
| Anti-pattern | Symptom | Why it fails | How to avoid / repair |
|---|---|---|---|
| Unsupported assurance fold | A mean, minimum, maximum, or weighted sum is reported as confidence without its model | Boundedness and monotonicity do not warrant the input scale or dependency interpretation | Identify support roles and a justified receiving model; otherwise return separate support and a bounded synthesis. |
| Truth-by-score | R=0.9 is treated as “the claim is true.” | R is warrant strength, not ontological truth. | Require explicit evidence links and scope; treat R as decision warrant only. |
| Scope laundering | The claim’s applicability grows by wording changes while G is unchanged. | It silently widens scope, making comparisons meaningless. | Use A.2.6 operators and treat scope changes as explicit revisions. |
| Relation laundering | A claim or its evidence is reused after a changed scope, kind, plane, notation, local meaning, model use, or evidence basis, while R is carried over unchanged. | It hides the actual change and its relation-specific loss. | Name the direct relation or scope operation and recompute R_eff from its declared loss; stop if that relation is missing. |
| DesignRunTag chimera | Design-time proofs and run-time telemetry are mixed as if they were the same evidence object. | Evidence belongs to different stances and decays differently. | Separate lanes and validity windows; treat crossings explicitly. |
| Ordinal arithmetic | F or CL ranks become a probability or loss merely by tagging, tabulating, or rescaling them | Ordered categories are not calibrated ratio quantities | Retain the ordinal meaning; any receiving conversion needs its actual model, meaning, scale, and assumptions. |
| Counting support labels | More reports are treated as independent confirmation, or one weak additional study automatically defeats the whole | Duplicates, shared bias, complementary information, and counterevidence contribute differently | Recover their actual dependencies and effects on the claim; use neither study count nor a universal min/max fallback. |