The claim

The system is CASE-124:

J₃ = | α  β  ν |
     | γ  δ  μ |
     | 0  ε  λ |

with all entries nonnegative and 0 ≤ α, δ, λ < 1.

  1. The threshold. det(I − J₃) = (1 − λ)[(1 − α)(1 − δ) − βγ] − ε[νγ + μ(1 − α)]. For a nonnegative matrix, the spectral radius is below one exactly when I − J₃ is a nonsingular M-matrix, that is, when its leading principal minors are positive. Where the two-variable loop is itself stable (βγ < (1 − α)(1 − δ)), instability therefore comes to det(I − J₃) < 0. With μ = 0 this is the review’s form, γ(β + νε/(1 − λ)) > (1 − α)(1 − δ).
  2. The reduction. Dividing by 1 − λ, det(I − J₃) / (1 − λ) = (1 − α)(1 − δ_eff) − β_eff γ, with β_eff = β + νε/(1 − λ) and δ_eff = δ + με/(1 − λ). That is CLAIM-330’s expression for a two-variable system with those couplings, and J₃ is unstable exactly when that two-variable system is, whether or not the original loop was stable. The regime’s contribution is its steady-state gain: authority’s effect on r, times r’s effect, divided by how fast r forgets.
  3. The mode. Away from the threshold, J₃ has three eigenvalues and the projection on (m, a) is not a closed first-order two-variable system. In CASE-124’s second witness, the impulse response of m has Hankel rank 3, and a lean in r keeps m and a off symmetry long after the two-variable system would have returned.

How it was checked

  • The determinant identity and the reduction, symbolically (sympy).
  • The equivalence of “spectral radius > 1” with the reduced two-variable condition, on 200,000 random draws with α, δ, λ uniform on [0, 0.99) and β, γ, ν, μ, ε uniform on [0, 2): no mismatch.
  • Both witnesses numerically.

What it answers

QUESTION-253 asked for “a showing either that the condition reduces to CLAIM-330’s with κ′ replaced by a function of r (the layer is κ′ renamed) or that it allows an instability, or a slow mode, that no choice of the two-variable parameters gives”. The threshold reduces, with the regime’s steady-state gain absorbed into β (the ν arrow) or δ (the μ arrow, a direct effect of the regime on scoring). The question’s own reading, r setting κ′, is not the μ arrow: since γ = 4ηs(κ′ − κ̄) (CLAIM-340), a regime that only varies κ′ adds a term in r·m to the authority update, second order at symmetry, so it moves no linear threshold at all. In that reading the layer is not even κ′ renamed at linear order; it matters only away from symmetry. The slow mode does not reduce. So whether legibility is “renamed” depends on what is asked of the model: for whether symmetry breaks, it is; for how long a lean lasts and how the system returns, it is not.

What it does not say

  • That legibility must be modelled as a state. If the regime is an instantaneous function of m and a, it folds into the couplings and the two-variable model suffices. Whether an organization’s legibility regime has dynamics of its own is empirical, and the record holds no case of it (QUESTION-253’s “What it does not ask”).
  • Anything outside the linearization at symmetry: not lock-in, not bistability, not the size an advantage reaches.
  • That a slower regime is worse. It adds more at the threshold, and holds a lean longer, whether the lean tracks a real difference or not.
  • That the third arrow is the only way to get a third mode. Any third state coupled into the loop would do; the construction’s content is that a legibility regime is one natural reading of such a state.

Note of 2026-10-25: when the slow regime can be reduced

From A29–A30 of the exchange of 2026-10-24, continued. Treating the legibility lean r as slow, dπ/dt = F(π, r) and dr/dt = εG(π, r), suggests the reduced flow dr/dt ≈ εG(π*(r), r). THEORY-771 licenses that when the fast authority dynamics contract to an equilibrium. A30: “the fast authority dynamics may cycle rather than converge to a unique equilibrium. In such cases we cannot automatically replace π by a function π*(ρ).” A valid slow reduction may then need averaging over an invariant distribution, or several attracting regimes. The harmonic part of the scores (CLAIM-444, THEORY-894) and Sato and Crutchfield’s cycling learners (THEORY-936) are where that happens. This claim’s result is a linearization at a stable symmetric state and stands as it is. Borkar’s two-timescale stochastic approximation was named with no work cited, and is not registered.