Discipline‑level False‑Discovery Dashboards

Publishers, funders and professional societies should maintain public dashboards that aggregate reported test statistics and p‑value distributions across a discipline to track changes in statistical power, selection bias signals (e.g., p‑curve anomalies), and estimated false discovery rates in near real time. These dashboards would use standardized, machine‑readable submissions or automated extraction from articles and transparently show trends to guide policy, preregistration enforcement, and funding priorities. — A continuous, public metric would give policymakers, journals, and funders an evidence base to calibrate reproducibility interventions and to hold institutions accountable for improving research reliability.