Name your model explicitly

Make the map visible by articulating your current model of the situation in plain language.

Why it works

Implicit models are invisible and therefore unfalsifiable — you cannot update what you cannot see. Making the model explicit converts it from background assumption to foreground hypothesis, which is the minimal condition for evaluating or revising it. The act of articulation also surfaces gaps and inconsistencies that feel invisible when the model operates below awareness.

How to do it

1. Write a two-to-four sentence description of how you currently think a situation works.
2. Include the key causal claims: "X causes Y because Z."
3. Identify one thing the model predicts that you could check.
4. Note what the model does not explain — the residual — as a flag for future investigation.

Evidence

Externalizing mental models is a core step in cognitive science and decision-analysis traditions. Writing down beliefs before evaluating them reduces hindsight bias and makes overconfidence more detectable — consistent with work on forecasting calibration. (mechanistic)

Specific studies on "name your model" as a practice are sparse; the value is principled from research on explicit vs. implicit reasoning and on forecasting calibration.

Common mistake

Naming the model in jargon that sounds precise but is actually too vague to generate predictions — a model that can explain anything explains nothing.