In the CbD approach, developed by Ehtibar Dzhafarov, Janne Kujala, and colleagues, (non)contextuality is treated as a property of any system of random variables, defined as a set R = { R q c : q ∈ ∈ Q , q ≺ ≺ c , c ∈ ∈ C } in which each random variable R q c is labeled by its content q , the property it measures, and its context c , the set of recorded circumstances under which it is recorded (including but not limited to which other random variables it is recorded together with); q ≺ ≺ c stands for " q is measured in c ". The variables within a context are jointly distributed, but variables from different contexts are stochastically unrelated, defined on different sample spaces. A (probabilistic) coupling of the system R is defined as a system S in which all variables are jointly distributed and, in any context c , R c = { R q c : q ∈ ∈ Q , q ≺ ≺ c } and S c = { S q c : q ∈ ∈ Q , q ≺ ≺ c } are identically distributed. The system is considered noncontextual if it has a coupling S such that the probabilities Pr [ S q c = S q c ′ ] are maximal possible for all contexts c , c ′ and contents q such that q ≺ ≺ c , c ′ . If such a coupling does not exist, the system is contextual. For the important class of cyclic systems of dichotomous ( ± ± 1 ) random variables, C n = { ( R 1 1 , R 2 1 ) , ( R 2 2 , R 3 2 ) , … … , ( R n n , R 1 n ) } ( n ≥ ≥ 2 ), it has been shown that such a system is noncontextual if and only if