S-Frame vs. I-Frame Interventions: The Transformation-Robustness Trade-Off in Behavioral Policy
When structural assumptions hold, targeted system-level seeding is markedly more transformative than individual-level nudges—yet the same reliance on social reinforcement makes it fragile.
Debate over whether behavioural policy should target individual-level (i-frame) or system-level (s-frame) interventions has been rich but largely qualitative. This article addresses that gap with an agent-based model, comparing i-frame interventions—nudges, information campaigns, rotating micro-targeting—with s-frame interventions—uniform structural levers and targeted seeding—across three sources of misspecification: imperfect structural knowledge, heterogeneous response, and external shocks. Two findings stand out. When structural assumptions are approximately correct, targeted s-frame seeding can trigger self-reinforcing diffusion and is markedly more transformative and cost-efficient than i-frame benchmarks. Yet that same reliance on social reinforcement creates fragility: targeting errors and backsliding shocks reduce s-frame performance more sharply. The contribution is a mechanism-oriented framework for comparing intervention families under uncertainty and for making the transformation–robustness trade-off explicit in behavioural policy design.
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