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A more general way of putting the problem revealed by these examples is that those features of a process P in virtue of which it qualifies as a causal process (ability to transmit mark M) may not be the features of P that are causally or explanatorily relevant to the outcome E that we want to explain (M may be irrelevant to E with some other property R of P being the property which is causally relevant to E). So while mark mathlab transmission may well be a criterion that correctly distinguishes between causal processes and pseudo-processes, it does not, as it stands, provide the resources for distinguishing those features or properties of a causal process that are causally or explanatorily relevant to an outcome and those features that are irrelevant.
A second set of worries has to do with the application of the CM model to systems which depart in various respects from simple physical paradigms such as the collision described above. There are a number of examples of such systems. First, there are theories like Newtonian gravitational theory which involve “action at a distance” LaTeX editor in a physically interesting sense. Second, there are a number of examples from the literature on causation that do not involve physically interesting forms of action at a distance but which arguably involve causal interactions without intervening spatio-temporally continuous processes or transfer of energy and momentum from cause to effect. These include cases of causation by omission and causation by “double prevention” or “disconnection.”[ 13 ] In all these cases, a literal application of the CM model seems to yield the judgment that no explanation has been provided — that Newtonian gravitational theory is unexplanatory and so on. Many philosophers have been reluctant to accept this assessment.
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