 Some think that more than a family of true counterfactuals is required in order for a token causal model to be correct—or, at least, in order for a causal model to provide us with a guide to token causation (see  §3.3).  Many, persuaded by the considerations from  §1.2.3  above, include information about which variable values are more or less normal than which others. And Handfield et al. (2008) suggest that the models must only represent relations of influence which correspond to “connecting processes”, in the sense of Fair (1979), Salmon (1984, 1994), or Dowe (2000). The idea is this: if a variable, X, shows up on the right-hand-side of Y’s structural equation, then there must be some possible state of the system (some possible assignment of values to the variables in the model) such that, in that state, there is a connecting process leading from X’s value to Y’s value.