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Explain the Lean theorem `recidivismCost_reciprocal` in module `IndisputableMonolith.CriminalJustice.RecidivismFromJCost`. Write for an educated reader who knows science and programming but may not know Lean. Cover: (1) what the declaration says in plain English, (2) why it matters in Recognition Science, (3) how to read the formal statement, (4) visible dependencies or certificates in the supplied source, and (5) what this declaration does not prove. Cite only declarations present in the supplied Recognition source.

Big AI job. Grok 4.3 reads the canon and writes a Lean-grounded derivation; usually 20 seconds to 2 minutes. Your answer will appear below.
confidence: high in recognition cached

Plain English: recidivismCost_reciprocal states that for any two positive real numbers (reoffense rate and baseline rate), the recidivism cost of their ratio equals the cost of the inverted ratio.

Relevance in Recognition Science: The result applies the reciprocal symmetry of the underlying J-cost to recidivism ratios. This symmetry is a structural feature of the recognition ledger: deviations above or below equilibrium incur identical recognition costs, restoring the cost floor symmetrically.

Reading the formal statement: The declaration takes two positive reals reoffense and baseline (witnessed by hr and hb), defines recidivismCost as Jcost (reoffense / baseline), and concludes equality after invoking the reciprocal property of Jcost and simplifying the division.

Visible dependencies and certificates: The proof unfolds recidivismCost and is bundled into the RecidivismCert structure (field cost_reciprocal) whose inhabitant is cert. The module also records the equilibrium and non-negativity properties as sibling theorems.

What it does not prove: The theorem establishes only the symmetry property; it supplies no numerical recidivism values, no empirical falsifiers, and no derivation of the J-cost function itself.

cited recognition theorems

outside recognition

Aspects Recognition does not yet address:

  • Definition or proof of Jcost_reciprocal (imported from Cost but absent from this module slice)
  • Empirical recidivism data or specific falsifying trials

recognition modules consulted

The Recognition library is at github.com/jonwashburn/shape-of-logic. The model is restricted to the supplied Lean source and instructed not to invent theorem names. Treat output as a starting point, not a verified proof.