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Causation: Many Words, One Thing?. Lorenzo Casini L.Casini@kent.ac.uk. Outline. Many pluralisms Against determinate pluralism Against the thick-concept view From thick concepts to inferences A key to (weak) monism?. Many pluralisms. Shared idea:
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Causation: Many Words, One Thing? Lorenzo Casini L.Casini@kent.ac.uk
Outline Many pluralisms Against determinate pluralism Against the thick-concept view From thick concepts to inferences A key to (weak) monism?
Many pluralisms Shared idea: • there are distinct kinds of causal relations • no single feature that makes all of them causal Under the influence of Hume and Kant we think of causation as a single monolithic concept. But that is a mistake. The problem is not that there are no such things as causal laws; the world is rife with them. The problem is rather that there is no single thing of much detail that they all have in common, something they share that makes them all causal laws (Cartwright 2007: 19).
There is pluralism and pluralism, however: • determinate vs indeterminate (Williamson 2006) • evidential vs metaphysical vs semantic (Reiss 2011) Above distinctions are orthogonal – one can be:
..and there are many monisms as well.. • Godfrey-Smith (?) • myself?
The monist (Williamson 2006) objects to the pluralist: • Why, depending on circumstances, do we appeal to • one or the other criterion (contra indeterminate p) ? • several / all criteria (contra determinate p) ? More in general: • How to reconcile • causation is diverse, and • “causal” is used to denote all these relations ? • Isn’t there something all notions (‘typically’) share ?
Against determinate pluralism Hall’s two concepts (2004): C causes E iff Longworth’s (2006) counterexample: Two brothers want to kill father by preventing him from taking his life-saving drugs. One should have given the drugs but didn't. If he had, the other would have taken them away. Father dies. What’s the cause? • no mechanism: omission kills father • no dependence: hadn’t first brother acted, second would have Intuition: first brother killed father, not second Moral: there can be causation but neither production nor dependence (C produces E) OR (E depends on C)
Longworth’s “three” concepts (2010): There exists one disjunction such that for any causal relation: • obtaining of one or other disjunct is sufficient • whole disjunction is necessary (disjunction is exhaustive) Causalcontent of a causal concept is measured by number of disjuncts it implies: e.g.: thick causal verb locality-cum-transference, whereas thin ‘causes’ whole disjunction, only. C causes E iff (E can be manipulated via C AND C raises prob of E) OR (C and E are local AND there’s transference of physical quantity between C and E) OR(E counterfactually depends on C)
Put forward as alternative to Cartwright’s thick-concept view: All thick causal concepts imply ‘cause’. They also imply a number of non-causal facts. But this does not mean that ‘cause’ + the non-causal claims + (perhaps) something else implies the thick concept. For instance, we can admit that compressing implies causing + x, but that does not ensure that causing + x + y implies compressing for some non-circular y (Cartwright 2007: 22) For Longworth (2010): • C offers no argument for: ‘cause’ + x thick concept • Extra-content ( y ) of thick concept may be non-causal nuance Taken together: • Causal content of thick concept some (non-causal) x*or other* N.B.: need to distinguish single-case vs general-case..
C’s (2010) 1st reply: Thick concept specific (non-causal) x This may be true in general-case but false in single-case. E.g.: IF (p53 correctly regulates synthesis of Mdm2) AND (p53 is phosphorylated OR Mdm2 is) AND (gene p53 is not mutated) AND ...AND Prob(pro-apop proteins are synth | Mdm2 is synth) > Prob(pro-apop proteins are not synth | Mdm2 is synth) AND other non-causal facts, THEN ‘p53 promotes apoptosis’ IF ‘p53 promotes apoptosis’ THEN Prob(pro-apop proteins are synth | Mdm2 is synth) > Prob(pro-apop proteins are not synth | Mdm2 is synth) Latter may or may not be true, depending on context – hence, extra-content e.g.p53 has also role in extrinsic pathway, where it increases cell's responsiveness to extra-cellular death ligands by promoting expression of Fas-encoding genes. BUT this doesn’t address L's point! i.e.: (causal content of) thick concept one or more disjuncts • This allows for thick causal description being realised in multiple ways, e.g. ‘promotes’ (prob raising) OR (…) OR …
C’s (2010) 2nd reply: Arguably, there is no exhaustive disjunction • nor is exhaustive disjunction needed to explain shared label “causal” (more on this soon) Also, further objection: • Why do the different notions all count as causal notions? • What makes the relations referred to by notions, in spite of their diversity, all causal relations? Indeterminate pluralism does not answer these questions…
Against the thick-concept view ...but neither does the thick-concept view! Amongst various notions is only family resemblance – each causing has “its own peculiar truth makers” (C 2007: 22). “If there is no universal account of causality to be given, what licences the word ‘cause’ in a law? The answer (...) is: thick causal concepts” (C 2007: 12). In turn, what grants family resemblance among thick concepts? Answer: the cluster of thick descriptions (often) implying a cluster of similar conditions under which causal laws work (see C 2010: 327). • in short: thick concepts all imply causation (= are all causal) because their correct application depends on satisfaction of conditions (usually) invoked when, as a matter of fact, thin concept ‘causes’ is also used. • Not much of an explanation!
C holds not just thick-concept view, but also inference view: Is there not something by virtue of which it is correct to call all these different kinds of relations ‘causal’? Here is a proposal. Rather than looking for one special relation in the world that legitimates representing them as causal, look instead for some unified feature ofthe representations themselves (C 2007: 46). Explanatory value of thin concept ‘causes’ derives not from its—allegedly unique—meaning… …but from figuring in formalisms whose assumptions specify conditions that (thick) causal laws must satisfy When assumptions are satisfied, they represent insofar as they licenseinferences (cf. Suarez 2004) There is no all-encompassing formalism that fits all real systems (cf. C 2007: 22-23, 46-52) N.B.: one can reject thick-concept view whilst endorsing inference view N.B.B.: both make claims on meaning of causal notions (contra Reiss 2011: 909) From thick concepts to inferences
Meaning of “x” has to do with “what can both serve as and stand in need of reasons” (Brandom 2007: 654), i.e., the inferences in which “x” figures as (part of) premisses or conclusions (cf. Sellars 1953, Wittgenstein 1956) controlled experiments, RCTs,observational studies, simulations,statistical analyses, etc. (plus theoretical and background assumptions) interventions, forecasting, explanations ‘causes’
A key to (weak) monism? evidential pluralism (Russo & Williamson 2007)… • (in the health sciences) different kinds of evidence (mechanism, difference-making) needed to establish causal claim • they don’t presuppose different concepts of causality – in line with epistemic account of causality (Williamson 2005, 2006b). …vs conceptual pluralism (Reiss 2011: 923-924) Suppose the term ‘cause’ is used on two different occasions and it is not known whether it has the same meaning on both occasions. Two such claims would have the form ‘X α-causes Y’ and ‘Z β-causes W’. We can then say that ‘α-causes’ has the same meaning as ‘β-causes’ (on these occasions) to the extent that ‘X α-causes Y’ is inferentially connected to the same kinds of propositions regarding the relation between X and Y as ‘Z β-causes W’ is inferentially connected to propositions regarding the relation between Z and W.
who is right? Two inferentialist readings... • Each causal claim has different inference base and inference target, hence different meaning (Reiss) • Causal claims differ only as to the relative strength of the various inferences which warrant them / they warrant (Williamson?) • Is ‘causes’ vague or unspecific? Vague: there can be one cluster, a not-so-amiable (or “cantankerous”) jumble of criteria (cf. Godfrey-Smith 2009) Unspecific: vagueness is epistemic not semantic, i.e. concerns not knowing which one among (many) distinct notions is employed in each case (Reiss) Argument for conceptual pluralism (Reiss): Arguably, no disjunctive analysis is possible; yet [t]here is a definite set of propositions with which any causal claim is inferentially related. True, we might not always have a very clear idea of what these sets are. But this is a question of epistemology, not of semantics” (Reiss 2011: 924) Contra Williamson: whether criteria ‘typically’ coincide is empirical not conceptual matter, “much like discovering that various symptoms of a disease typically co-occur” (Reiss 2009: 33)
Trouble for inferentialism is semantic holism (Quine 1951): If meaning is inference, and inferences are all related, then meaning of any expression depends on all inferences. • How is conceptual content relatively stable? • How is successful communication possible? Whether responses to holism (cf. Sellars 1948, Brandom 2000) are successful is an open question.. ..but to the extent that they are, they don’t justify Reiss’ strong conceptual pluralism: • respect in which different meanings differ cannot be made fullyexplicit for semantic reasons, too – i.e., respect changes along with changes in meaning of ancillary notions that should help make it explicit • for distinct concepts to exist there need to be different communities using sameword with different meanings andnever (successfully) communicating with one another – implausible • ‘causes’ may still have one, vague (‘high-level’) meaning • a ‘weakly-monistic’ inferentialist account is possible
Summary • Determinate pluralism is implausible and not explanatory • Thick-concept view is not explanatory either • Inferentialism needs not commit to strong conceptual pluralism • Possible to develop a weakly-monistic account
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