Mental Causal Models
Updated 2026-08-08
INTRODUCTION
English translation pending.
CORE DEFINITION
A concept from cognitive psychology associated with work by Philip Johnson-Laird and with the causal-model tradition in reasoning research. A mental causal model is a person's internal representation of which factors cause which outcomes and how strongly. These models support prediction, explanation, and intervention decisions, but they are often built from limited evidence, so they can encode spurious links or miss real ones. Because the model supplies the structure of the reasoning, errors in the model propagate into every conclusion drawn from it, even when the logic applied is sound.
SCAFFOLDING EFFECT
Reduce cognitive load
- Model drawing: write out the causal links you assume before reasoning from them. - Assumption testing: check each link against evidence rather than against plausibility. - Prediction check: use the model to forecast, then compare the forecast with what happens.
Anchor fast decisions
Reasoning operates on the model, not on the world, so the quality of the conclusion is bounded by the accuracy of the assumed causal structure. A missing link produces confident predictions that fail, and an added spurious link produces interventions that change nothing or make things worse. Because the model is rarely made explicit, its errors stay invisible and get reused across many decisions.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Causal_reasoningverified
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