theorem friction_channels_oppose {β_L V T β_C K_eff Tstar β_I G T_min : ℝ}
(hβL : 0 < β_L) (hV : 0 < V) (hT : 0 < T)
(hβC : 0 < β_C) (hK : 0 < K_eff) (hTlt : T < Tstar)
(hβI : 0 < β_I) (hG : 0 < G) (hTmin : T_min < T) :
learningFrictionRate β_L V T < 0
∧ 0 < cascadeFrictionRate β_C K_eff T Tstar
∧ institutionalFrictionRate β_I G T T_min < 0 :=
⟨learning_reduces_friction hβL hV hT,
cascade_increases_friction hβC hK hTlt,
institutional_reform_lowers_friction hβI hG hTmin⟩Results T-80 through T-89: Endogenous Information Friction Dynamics