Direct and indirect causes (original) (raw)
Related papers
A Probabilistic Analysis of Causation
"ABSTRACT (Follow link above for pre-print, or below for published version) The starting point in the development of probabilistic analyses of token causation has usually been the naive intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that an examination of the structure of these problem cases suggests a different treatment, one which avoids the costs of extant probabilistic analyses. 1. Introduction 2. A Naive Probabilistic Analysis, Two Objections and a Refinement 3. Non-Probability-Raising Causation 4. Graphical Representation of Cases of Non-Probability-Raising Causation 5. Probability-Raising Non-Causation 6. Graphical Representation of Cases of Probability-Raising Non-Causation 7. Completing the Probabilistic Analysis of Causation 8. Problem Cases for Extant Probabilistic Analyses 8.1 Causation by Omission 8.2 Direct Non-Probability-Raising Causation 8.3 Failures of Transitivity 9. Conclusion"
Direct causation: A new approach to an old question
U. Penn Working Papers in Linguistics, Volume 26.1, 2019
Causative constructions come in lexical and periphrastic variants, exemplified in English by Sam killed Lee and Sam caused Lee to die. While use of the former, the lexical causative, entails the truth of the latter, an entailment in the other direction does not hold. The source of this asymmetry is commonly ascribed to the lexical causative having an additional prerequisite of “direct causation", such that the causative relation holds between a contiguous cause and effect (Fodor 1970, Katz 1970). However, this explanation encounters both empirical and theoretical problems (Nelleman & van der Koot 2012). To explain the source of the directness inferences (as well as other longstanding puzzles), we propose a formal analysis based on the framework of Structural Equation Models (SEMs) (Pearl 2000) which provides the necessary background for licensing causal inferences. Specifically, we provide a formalization of a 'sufficient set of conditions' within a model and demonstrate its role in the selectional parameters of causative descriptions. We argue that “causal sufficiency” is not a property of singular conditions, but rather sets of conditions, which are individually necessary but only sufficient when taken together (a view originally motivated in the philosophical literature by Mackie 1965). We further introduce the notion of a “completion event” of a sufficient set, which is critical to explain the particular inferential profile of lexical causatives.
The British Journal for the Philosophy of Science, 2006
The paper builds on the basically Humean idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epistemic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this 'status raising' is best explicated not in regularity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals with cases of overdetermination and pre-emption. It finally indicates how the account's profound epistemic relativization induced by ranking theory can be undone. 1 Introduction 2 Variables, propositions, time 3 Induction first 4 Causation 5 Redundant causation 6 Objectivization 1 The major cycles have been produced by David Lewis himself. See Lewis ([1973b], [1986], [2000]). Hints to further cycles may be found there. 2 It is first presented in (Spohn [unpublished]). 3 See, e.g. the April issue of the Journal of Philosophy 97 (2000), or the collection by Collins et al. ([2004]). See also the many references therein, mostly referring to papers since 1995.
Erkenntnis, 2012
David Lewis’s latest theory of causation defines the causal link in terms of the relation of influence between events. It turns out, however, that one event’s influencing another is neither a necessary nor sufficient condition for its being a cause of that event. In the article one particular case of causality without influence is presented and developed. This case not only serves as a counterexample to Lewis’s influence theory, but also threatens earlier counterfactual analyses of causation by admitting a particularly troublesome type of preemption. The conclusion of the article is that Lewis’s influence method of solving the preemption problem fails, and that we need a new and fresh approach to the cases of redundant causation if we want to hold on to the counterfactual analysis of causation.
2006), Causation: An Alternative
2016
Abstract: The paper builds on the basically Humean general idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epis-temic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this ‘status raising ’ is best explicated not in regu-larity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals with cases of overdetermination and preemption. It finally indicates how the account’s
Probability-Lowering Causes and the Connotations of Causation
Ideas y Valores 151: 43-55, 2013
A common objection to probabilistic theories of causation is that there are prima facie causes that lower the probability of their effects. Among the many replies to this objection, little attention has been given to Mellor’s (1995) indirect strategy to deny that probability-lowering factors are bona fide causes. According to Mellor, such factors do not satisfy the evidential, explanatory, and instrumental connotations of causation. The paper argues that the evidential connotation only entails an epistemically relativized form of causal attribution, not causation itself, and that there are clear cases of explanation and instrumental reasoning that must appeal to negatively relevant factors. In the end, it suggests a more liberal interpretation of causation that restores its connotations.
Causation, 2020
Causation is defined as a relation between facts: C causes E if and only if C and E are nomologically independent facts and C is a necessary part of a nomologically sufficient condition for E. The analysis is applied to problems of overdetermination, preemption, trumping, intransitivity, switching, and double prevention. Preventing and allowing are defined and distinguished from causing. The analysis explains the direction of causation in terms of the logical form of dynamic laws. Even in a universe that is deterministic in both temporal directions, not every fact must have a cause and present facts may have no future causes.
Causation: Objective or Subjective?
Probabilistic and Causal Inference, 2022
We, and scientific practice, tend to conceive of causation as an objective relation characterizing the external world. Philosophy has been more ambiguous. This chapter intends to renew the doubts. If causation is only a model-relative notion and if causation is tightly entangled with notions that are best understood in a subject-relative way, then the objectivity of causation is at least undermined. The paper discusses these doubts and concludes that the objectivity of causation must not be presupposed, but must be constructively earned.