Causal Loop Diagram
Updated 2026-08-13
INTRODUCTION
English translation pending.
CORE DEFINITION
A causal loop diagram represents a system as variables connected by arrows whose polarity shows whether the linked variables move in the same direction or in opposite directions, while closed chains of arrows form reinforcing loops that amplify change or balancing loops that seek a target. The core proposition is that a system's behavior over time comes from its feedback structure rather than from the individual variables, so drawing that structure makes behavior that seems puzzling become predictable. The key qualification is that loop polarity and delays must be identified correctly, since a mislabeled link or an ignored delay inverts the conclusion, and correlation between two variables does not establish a causal arrow between them.
SCAFFOLDING EFFECT
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- Loop inventory: list the closed chains of causation before judging any single variable. - Polarity labeling: mark each arrow as same-direction or opposite-direction and check the loop type. - Delay marking: note where effects arrive late, since delays convert balancing loops into oscillation.
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Reinforcing loops generate exponential growth or collapse, while balancing loops pull a system toward a target; when a delay sits inside a balancing loop, the correction arrives after the system has overshot, producing oscillation. Reading behavior off the loop structure therefore explains dynamics that a list of variables cannot, and identifies where a small intervention changes the whole pattern.
MINIMUM ACTION
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Causal_loop_diagramverified
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