SSIS Postgraduate Conference, Exeter, 1 May 2015
Cause, Causatives,
and Theories of
Causation
Julian Reiss, Durham
Background
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Main concern: Provide a satisfactory account of
causation in the sciences
My own work focuses on the biomedical and social
sciences
Previously: detailed examination of the methods of
causal inference in these sciences
Here: taking a closer look at the causal language that is
employed in science, taking cancer causation as a main
case study
Background
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Two things:
❖ Take scientific language at face value
❖ (Instead of starting with metaphysical intuitions and
developing a theory that satisfies the given constraints)
❖ Main target: Any attempt to explicate causation by means of
‘C causes E iff “…”’
❖ ‘Straightjacket Theories of Causation’
❖ No matter what is on the RHS of the definition
❖ In particular (for instance) whether or not ‘cause’ appears
Feature 1: Indispensability of
Causatives
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Feature 1: Scientific language is full of causatives such as push,
bond, attract,
crunch,
deflate
‘To buy’
= Toprolong,
cause dampen,
to acquire?
To cause to establish
Familiar from Anscombe
and Cartwright
ownership?
To cause to have ownership?
A problem: it’s not clear that you can always translate these into
To
cause
to
have
ownership
by
‘cause + x’ (buy)
transferring money?
cause to
ownershiptheory:
by
This does constituteTo
a problem
forhave
the straightjacket
they
cannot account for the
large majority
of causal
claims in science
causing
someone
to have
.
money?
(‘Cause’ itself is used quite rarely!)
C andMetaphysical
E must be distinct events––and
Feature 2:
distinct not only in the sense of
nonidentity but also in the sense of
Anarchy
nonoverlap and nonimplication. It won’t
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❖
do to say that my speaking this
Straightjacket Theories often necessitate
the assumption
of further
metaphysical
sentence
causes my
speaking
this
principles (e.g., counterfactual theory); e.g.:
sentence, or that my speaking the
❖ Independent events
whole of it causes my speaking the first
half of it, or vice versa; or that my
❖ No absence causation
speaking it causes my speaking it
❖ Causal order is identical to temporal order
loudly, or vice versa.
Feature 2: Scientific language is extremely flexible with respect to the C’s and E’s that
are being causally related or indeed with respect to what is represented by a causal
claim
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Hypothesis: there is no general metaphysical principle to which one cannot find a
counterexample
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So ‘C φs E’, where φ is a causative, doesn’t work either
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A theory of causation must be a theory of causal claims
Feature 3: Polysemy
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The third feature is that causatives are polysemous
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Some
can be
causally
nonWith causatives
these considerations
in used
mind, both
it is essential
to and
determine
causally
whether the use of PREPS [potential-reduced exposure products]
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actually
lowers
carcinogen
dose.
What
they
depends
on context
(Hecht
2002,mean
‘Biomarkers
For Investigating
Tobacco and Cancer’)
Therefore: a theory of causation must be a theory of
causal claims in a context
🍸 Interval 🍸
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The ‘Straightjacket Theory of Causation’:
context iff “…”’
‘C causes E in
iff a“…”’
❖ Indispensable causatives
❖ Metaphysical anarchy
❖ Polysemy
A pluralist truth-conditional
theory?
What are the chances of providing truth
conditions for a complex statement such as
‘[Claim using φ-causative] in context K’ iff…?
❖ I have no knock-down argument against it but
doubt whether it can be done
❖ Q&A if you want to know more
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An Alternative: Inferentialism
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Main idea:
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Causation and inference are clearly related
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(Justified/accepted) Causal claims, in conjunction with other knowledge
such as observations, license inferences to future and past states of
affairs
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Observations, in conjunction with background knowledge, license
inferences to causal claims
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Proposal: The content of causal claims consists in the inferential network of
which they are a part
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Essentially: the content of a causal claim is given by the set of propositions
from which it follows and those which follow from it
Inferential systems
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More precisely: The content of a causal claim is given by its
inferential system; that is, by the propositions from which an
epistemic community is entitled to infer the causal claim, and
those the community is entitled to infer from it
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Divides into ‘inferential base’, ‘inferential target’ and causal
claim CC itself
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Inferential base: essentially, the evidence – RCTs, controlled
experiments, statements describing experimental design,
observational studies, statements describing how confounders
and biases are ruled out, background knowledge etc.
Evidence
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I can only sketch the story here
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Roughly, ask: under what conditions are we justified in inferring a
causal claim from the evidence?
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Answer, roughly: when there is a study that uses a reliable method
and shows the claim to hold
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Experimental methods often achieve reliability by design; but even
they have to be checked for confounders, biases
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Observational methods achieve reliability to the extent that
alternative accounts can be ruled out
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All this is highly context dependent
Inferential Targets
‘Inferential
EC EC
EC claims
❖ Causal
their own sake
EC EC are rarely established for
system-CC’
EC EC
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Rather, for the cash value:
EC EC
EC EC EC
❖ explanations
EC EC
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CC
attributions
of
blame
and
praise
EC
EC EC EC
EC
❖ predictions
EC EC
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TC TC
TC TC TC
TC TC
propositions
about effective strategies
EC
Context
EC EC EC
EC
EC EC the content of a causal claim, ask: What is its
❖ To determine
inferential
system?
Inferential
base
Inferential
target
Causal Redundancy
Here is an example of how the account works
Cause
❖ What is the content of a sentence such as ‘Billy’s throw
caused the iPad to shatter?’
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Ask: what is the inferential system of the sentence?
Outcome
❖ Answer
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Inferential
base:
critical
observation
Backup
Cause
❖ That is:
observation plus critical background
assumptions that are contextually justified
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Causal Redundancy
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Inferential target (e.g.):
Smoking
❖ Billy is responsible;
Billy’s throw explains the shattering;
CompenLung
❖ BUT NOT: Had Billy not thrown, the iPad wouldn’t have
sation
Cancer
shattered
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Why? We’re entitled to infer the counterfactual only in
Asbestos
contexts where
there are no backup causes (among other
things)!
Conclusions
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By way of concluding, let me point out how the account deals with the
three features about causal language in science
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Feature 1: Indispensability of causatives
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It makes no difference between sentences in which ‘cause’ appears
and those in which it doesn’t
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For any sentence in a scientific publication we can ask, ‘What is the
inferential system for this sentence?’
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Neither does ‘cause’ vs causative make a principled difference, nor
whether the sentence is a causal claim at all (though: the inferential
networks of predictive sentences, for instance, may be a lot harder to
understand)
Conclusions
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Feature 2: Metaphysical anarchy
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As causation has to do with our reasoning practices and not with what the world is
like, anything goes metaphysically speaking
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The account, as presented here, can be underwritten by a realist metaphysics
(which would mean that a representationalist account would eventually have to be
found) or by anti-realism (the option I favour but don’t presuppose)
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No general metaphysical principles are assumed
Feature 3: Polysemy
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There is no difference-in-principle between causal and non-causal claims; to what
extent a claim is causal depends on family resemblance of inferential systems
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And family resemblance is much more than hand-waving in this case: we know the
typical kinds of proposition in inferential base and target