Once the relational cut between model and world vanishes, the structural pattern repeats across multiple domains. Models begin to be treated as the phenomena themselves, conferring authority and guiding decisions independently of empirical instantiation.
Physics: String theory, cosmology, and dark matter models illustrate the phenomenon. Theories generate complex mathematical structures that are treated as factual accounts, despite limited empirical access. Authority arises from internal coherence, elegance, and predictive plausibility rather than direct engagement with phenomena.
Climate Science: Earth system and general circulation models are often read as literal projections of the world’s future. Policy and planning decisions sometimes rely on these outputs as if they were the world itself, with uncertainty and conditionality underemphasised.
Economics: Macroeconomic models simulate national economies, yet forecasts are frequently treated as prescriptive. Parameters are tuned, scenarios projected, and policy recommendations derived as if the model were reality rather than a structured theory of possible outcomes.
AI and Cognitive Modelling: Alignment models, neural simulations, and behavioural predictions are sometimes interpreted as literal descriptions of agent reality. The relational cut is overlooked, leading to overconfidence in predictions and structural misalignment between model and environment.
Across domains, structural reification produces a common pattern: authority is conferred internally, the cut with actual phenomena is obscured, and critiques that appeal to empirical limitations often fail to land. Recognising this pattern allows us to diagnose the broader consequences and prefigure the structural hazards we will examine in the next part.
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