
Jensen Huang observed in March 2026 that biology is transitioning from science to engineering through computation. This paper argues that the same transition applies to law. Legal systems, like biological organisms, exhibit phenotypic expression (institutional dynamics) driven by an underlying genotype (constitutional structure). Drawing on Extended Phenotype Theory (EPT) as formalized for legal-institutional dynamics in prior work (Lerer, 2026a), this paper treats legal norms as cultural replicators whose fitness determines survival in an institutional ecosystem. Building on the Constitutional Lock-in Index (CLI) developed in prior work (Lerer, 2026a), I validate this four-component metric of structural institutional rigidity against four jurisdictions: Argentina (0.89), Spain (0.51), Brazil (0.40), and Chile (0.24). I implement a multi-agent simulation engine adapting the OASIS framework (Yang et al., 2024) for institutional dynamics, with seven agent types, nine legal actions, and two novel theoretical mechanisms: Heteronomous Bayesian Updating (HBU) and the Coefficient of Resistance to Institutional Change (CRI). Monte Carlo validation against 23 Argentine labour reforms (1974-2024) produces emergent CLI of 0.92 (target 0.89, error 0.033) with 93.8% reform-blocking in adversarial scenarios. Leave-one-out cross-validation across 60 cases in four countries yields 56.7% accuracy (95% CI: 44.1-68.4%), above a 43.3% baseline. I submit the programme to Mario Bunge's demarcation criteria and identify both strengths and unresolved weaknesses, particularly regarding the measurability of utilities in game-theoretic components.
extended phenotype theory, evolutionary game theory, institutional dynamics, legal simulation, multi-agent systems, constitutional lock-in, regulatory hysteresis, synthetic populations
extended phenotype theory, evolutionary game theory, institutional dynamics, legal simulation, multi-agent systems, constitutional lock-in, regulatory hysteresis, synthetic populations
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
