Policy and service planning should require a standardized, public 'robustness map' (siblings, negative controls, E‑values, liability‑scale counterfactuals) before governments treat rising administrative autism counts as evidence for emergency funding or broad medical interventions. That rule would force transparent separation of ascertainment effects from true prevalence change and prevent overreaction or misdirected resources.
— Requiring pre‑policy robustness decomposition would improve allocation of special‑education, diagnostic, and research funds and reduce politicized swings based on preliminary or administrative series alone.
Paul Sagar
2026.01.14
90% relevant
Sagar’s central move is the same as this existing idea: observed diagnostic rises (here ADHD/anxiety/ASD among students) must be decomposed into ascertainment/diagnostic drift versus true incidence before policy or accommodation practices are locked in. He cites UK and elite‑college prevalence jumps (5→20% at Oxbridge, Stanford 38%), exactly the type of administrative trend this idea says needs a formal decomposition.
2024.10.30
100% relevant
The article cites exponential growth in California Developmental Services caseloads and international prevalence charts to argue for a 'true' epidemic—these are the exact administrative signals that a robustness‑map requirement would subject to sibling controls, cohort‑bias tests and liability decomposition.
2015.01.04
78% relevant
Hansen et al. operationalize the decomposition urged by the existing idea: they model time‑dependent registry changes and estimate the portion of prevalence increase attributable to reporting rather than true incidence — strengthening the argument that policy should wait for robustness maps before large program changes.
2012.05.04
90% relevant
This meta‑analysis supplies the kind of pooled epidemiological evidence that must be incorporated into any quantitative decomposition of rising autism counts (diagnostic drift vs true incidence). It underlines why policymakers need robustness maps—because maternal‑age effects are real and must be accounted for when estimating how much of observed prevalence change is due to shifting parental demographics versus ascertainment or environmental causes.
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