Kahneman and Klein (2009) classify individual stock prediction and long-term political forecasting as zero-validity environments, unlike high-validity medicine and firefighting

kahnemankleinexpert-intuitionzero-validity-environmentforecastingtetlockstock-predictioncognitive-psychology

To make the abstract "validity" scale concrete, Kahneman and Klein name worked examples at both ends. At the low end: "[O]utcomes are effectively unpredictable in zero-validity environments. To a good approximation, predictions of the future value of individual stocks and long-term forecasts of political events are made in a zero-validity environment." At the high end, they name domains that support genuine skill: "Medicine and firefighting are practiced in environments of fairly high validity."

The paper attributes forecasting failure to the environment, not the forecaster's competence, citing Tetlock's (2005) finding that experienced political forecasters were no better than untrained newspaper readers at long-range prediction: "the problem is in the environment: Long-term forecasting must fail because large-scale historical developments are too complex to be forecast." This is the applied edge of the paper's general thesis — that skill cannot form where no learnable cue–outcome structure exists (claim-kahneman-klein-2009-skill-cannot-form-in-low-validity-confidence-does-not-signal-validity) — and the positive-condition counterpart is claim-kahneman-klein-2009-intuition-reliable-only-in-high-validity-environments. The naming of firefighting as high-validity connects directly to Klein's own recognition-primed decision research, the naturalistic-decision-making tradition this paper reconciles with the heuristics-and-biases program.