meadows/docs/adr/0001-detected-feedback-loops.md

Feedback loops are detected from a polarity-annotated graph, not stored

Part of meadows · see DESIGN.md.

A Feedback Loop in a Model is a cycle in the wiring (Stock → Information Link(s)/Flow → same Stock). We chose to derive loops by detecting cycles and classifying each as Reinforcing (even number of − polarities) or Balancing (odd), rather than storing them as first-class objects the user hand-labels. This makes loops discovered insight that can never disagree with the actual structure — the point of a systems-thinking tool.

Considered Options

• Hand-labeled annotation — user drops a loop badge and tags it R/B. Simplest, but the label carries no structural truth and can contradict the wiring.
• Hybrid — app detects the cycle exists; user assigns R/B. Removes the inconsistency risk only partially and makes the user do reasoning the app can do.
• Detected from structure (chosen) — app finds cycles and classifies them.

Consequences

• Every Information Link must carry a Polarity (+/−); inflows/outflows carry inherent polarity. This is a required field from the diagram phase on.
• There is no Loop entity in the data model — loops are computed, not persisted. A future reader seeing polarity on every link and no stored loop should look here.
• Requires cycle-detection + sign-product logic. The same polarity data is reused when numeric simulation is added later.