Andrew Heathcote

Cognitive psychologist and quantitative modeller of learning and response time. In the vault he anchors the averaging-artifact cluster: with Scott Brown and D.J.K. Mewhort he authored The Power Law Repealed (Psychonomic Bulletin & Review, 2000), which showed that the celebrated power law of practice fits worse than an exponential in every unaveraged dataset and appears only after linear averaging over learners with heterogeneous rate parameters. He matters to this vault because that single finding turns a supposed universal law into a property of how data is aggregated — a reflex the vault then tracks recurring across fields and decades.

References

• claim-heathcote-2000-power-law-of-practice-is-an-averaging-artifact — the core repeal: individuals speed up exponentially, only the group mean looks like a power law.
• claim-heathcote-2000-averaging-distortion-requires-rate-parameter-variability — the precise algebraic condition: distortion requires, and is proportional to, variability in individual rate parameters (after Myung, Kim & Pitt 1998).
• claim-averaging-artifact-across-practice-and-scaling-laws-is-analogous-symptom-not-same-mechanism — his mechanism vs. the 2026 neural-scaling-law critique: analogous symptom, distinct process.
• observation-averaging-heterogeneous-learners-manufactures-a-power-law-no-individual-obeys — the cross-domain bridge his 2000 result forms with Hu et al. (2026).