Explanation of recidivismCost in IndisputableMonolith.CriminalJustice.RecidivismFromJCost
(1) In plain English, the declaration defines a function that takes two real numbers (a reoffense rate and a baseline rate), computes their ratio, and feeds that ratio into the J-cost function to produce a real-valued cost. This maps any recidivism ratio directly onto the recognition-cost scale.
(2) In Recognition Science this matters because it treats recidivism as a J-cost reading on the ratio r = reoffense_rate / baseline_rate. Equilibrium (r = 1) yields cost 0; effective rehabilitation that drives r below 1 raises the cost and restores the recognition floor. The module states that the minimum detectable reduction occurs at a one-φ-step departure.
(3) The formal statement is a noncomputable definition inside a noncomputable section: def recidivismCost (reoffense baseline : ℝ) : ℝ := Jcost (reoffense / baseline). The parameters are ordinary real numbers; the body applies division followed by the imported Jcost. Supporting results such as recidivismCost_at_equilibrium show the cost is exactly 0 when the inputs are equal and nonzero.
(4) Visible dependencies are the imports of Constants and Cost (supplying Jcost and its properties). The module supplies recidivismCost_nonneg, recidivismCost_reciprocal, and recidivismCost_phi_step. These are packaged in the structure RecidivismCert, realized by cert and shown inhabited by cert_inhabited.
(5) The declaration does not prove any empirical recidivism data, does not establish the uniqueness or explicit form of Jcost, and does not discharge the falsifier claims appearing only in the module docstring.