Subsequent work has demonstrated that positive testing is not inherently irrational [austerweil2011seeking, perfors2009confirmation, oeberst_toward_2023]; for instance, when target phenomena are relatively rare, positive testing approximates optimal information gathering [klayman_confirmation_1987]. Bias emerges not from the strategy itself, but from the interaction between the search strategy and the environment [klayman_varieties_1995]. When a learner’s hypothesis is a subset of, or embedded within, the truth, positive testing yields “ambiguous verifications” that the learner mistakes for strong evidence for their hypothesis [klayman_confirmation_1987]. This creates a feedback loop where the search strategy retrieves only confirming data, and the learner fails to account for the fact that they are sampling from a biased subset of reality.
MIM is not revolutionary. It’s just a Modular Design married with a simplification of Clean/Hex/Onion Architectures (i.e. elevated DIP). It’s also influenced by the “Imperative Shell, Functional Core” pattern and James Shore’s A-Frame. You can also find it similar to J.B.Rainsberger’s “Universal Architecture” (although it uses circular-layers, its simplicity is refreshing).
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