Preemption and fizzling cases together might be taken to show that probability-raising (however interpreted and refined) is systematically unable to provide necessary or sufficient conditions for causation.
Disconnection and misconnection cases together might be taken to show that process-linkage (however interpreted and refined) is systematically unable to provide necessary or sufficient conditions for causation.
We need an account of how identifying an inus condition for causation provides a possible explanation for some observed effect.
Explanations of SES disparities in mental health tend to support one of two broad hypotheses: that SES factors cause the onset of a mental health condition (social causation), or that poor mental health causes a downward shift in social class or status (health selection).
For example, this last observation is perfectly reflected in a claim he makes about the necessary conditions of formal causation: "The first requisite [for formal causation] is the actual existence of a form itself" (prima est actualis existentia ipsius formae: DM XV 6.3).
More generally, the strategy of searching for necessary and sufficient conditions of actual causation, characteristic of most theories of actual causation (including Halpern & Pearl, 2005; Woodward, 2003), is open to criticism.
The interpolated, albeit vague, conditions that require causation in 'the right way' are meant to cover well-known counterexamples that depend upon deviant causal chains occurring either in the course of the agent's practical reasoning or in the execution of his intentions.
As our results suggest, one missing snapshot of an event (implied causation condition) does not automatically trigger an event update because enough predictions of the event are fulfilled.
The number of yes answers (i.e., the number of reports indicating that the contact moment had been seen) in the condition with implied causation (causal) differed significantly (z = 22.21 and p <.001) from the number of yes answers in the condition without implied condition (non-causal), with an estimated (log) mean difference of 4.03, CI [3.60, 4.46].
New recommendation Many cases of dementia have more than one condition contributing to causation.
