Title: Mechanistic Causality: Dispositions vs. Structures
1Mechanistic Causality Dispositions vs. Structures
- Lorenzo Casini
- L.Casini_at_kent.ac.uk
2Outline
- Mechanisms complex systems
- Glennans account latest views
- Dispositionalist interpretation
- The case of asset pricing
- Between dispositions and structures
3Complex systems
- Systems whose behaviour result from
(rule-based) interactions of many (different)
components and exchange (of e.g. energy, mass,
information) with environment - Can display one or more among
- Nonlinearities
- Sensitivity to initial conditions
- Self-organisation
- Adaptivity
4Mechanistic causality
- The given
- Complex systems sciences study mechanisms (cf.
Bechtel Richardson, BA, Kuhlmann, etc.) - In C S S, talk of causal relations and of
mechanisms often go together - Working hypothesis
- causal relations in complex systems have to do
with mechanisms - Desiderata for account
- informative about truth conditions
- provide explanation of phenomena
5Glennans account
- (C) Event A causes event B iff there is a
mechanism (M) which connects them (1996 49, 56,
64) - All sorts of mechanisms between any two events.
How to select the right one? - (M) A mechanism for a behavior is a complex
system that produces that behavior by the
interaction of a number of parts, where the
interactions between parts can be characterized
by direct, invariant, change-relating
generalizations (2002 S344) - Interactions are only so characterised what are
they? - Events are related by mechanism (complex
system) complex system object whence, events
mediated by an object not a process ?
Relation between object and process?
6Latest views
- Causal claim relates events (property instances)
and has the form - Event c causes event e (in background conditions
B) in virtue of properties P (of c, e, or B)
(...) For instance, Bob's coughing (c) caused
Carol to wake up (e) in virtue of cough's
loudness (P). (2010a 364)
production relevance
relates events relates properties
singular general
non-counterfactual counterfactual
truth conditions explanation
- production provides truth conditions
- to say that one event produced another is to say
that in fact the causative event is connected to
the effect via a continuous chain of causal
processes (2010a365-6)
7(i) relation processobject
- Mechanism is both a system and a process which
are so related - Mechanism" is used to describe two distinct but
related sorts of structures. First, mechanisms
are systems consisting of a collection of parts
that interact with each other in order to produce
some behavior. () Second, mechanisms are
temporally extended processes in which sequences
of activities produce some outcome of the
mechanisms operation. () There is a natural
relationships between processes and systems, for
the operations of systems give rise to processes.
(2008 376) - (Couldnt it be other way round ? )
8(ii) nature of interactions
- Interactions are only characterised as ..
what are they? - an interaction is an occasion on which a change
in a property of one part brings about a change
in a property of another part. For instance, a
change in the position of one gear within a clock
mechanism may bring about the change in the
position of an interlocking gear. Interaction
is a causal notion that must be understood in
terms of the truth of certain counterfactuals.
(2002 S344) - What makes counterfactual assertion true?
- singular determination, i.e. exercise of power
- When a change in a produces a change in b, it
follows (with the usual caveats about
overdetermination, etc.) that if a had not
changed, b would not have changed. But the
counterfactual locution should be understood not
as a claim about non-actual worlds, but a claim
about the determining power of a in this world.
(2010b, sec.5)
9Ambiguity remains
- What is the truth maker of a causes b ?
- determining power of a
- or
- continuous chain of causal processes between a
and b - Other sources of ambiguity
- Glennan also talks of causal rel between events
as if it is relevance rel - the set of events causally sufficient to bring
about an effect are typically large, so that when
we speak of the cause of an event, we are using
pragmatic criteria to single out a certain event
as especially salient. (2010a 364-5) - Powers are usually ascribed to objects not
events can be OK but we need a
(dispositionalist?) story here..
10A dispositionalist interpretation
- Chakravartty (2007)
- A causal property is a property conferring to
particulars that have it dispositions to behave
in certain ways when in the presence or absence
of other particulars with causal properties of
their own (p.108) - causation is a relation of de re necessity
between properties, or property instances - account of de re necessity follows from account
of causal properties identity (pp. 113-114)
(DIT) - what makes a causal property the property that
it is are the dispositions it confers to the
objects that have it (p 129) - causal phenomena are the result of continuous
processes of interaction among particulars with
causal properties
11- talk of events as relata is convenient but
elliptical for description of aspects of such
processes - identity of particulars (objects, events,
processes) is derivative from identity of causal
properties. - Position entails holism, or ontological
circularity - All laws (general relations between properties)
and all causal properties are fixed at once given
a set of properties and their distribution - What is the truth maker of a causal claim?
- (...) it is a consequence of DIT that networks
of causal properties have a holistic nature. This
furnishes a more radical solution to the problem
of truthmaking than it is generally appreciated.
The existence of any one causal property is a
sufficient truthmaker for counterfactuals about
all possible relations applicable to the world in
which that property is found (p. 146)
12- All this seems in line with complex systems
scientists views - Causal relations are not something extra added
to predefined noncausal objects. They appear
simultaneously with objects in a world that
becomes, as a result of systematic individuation,
a complex causal network of things and events.
Causal relations obtain among states of things in
static conditions and among events in dynamic
conditions. An example of a static causal
relation is the suspension of the Golden Gate
Bridge by steel cables. Two states or events are
causally relatable if they are connectible by a
process, which can be stationary, related if they
are so connected. If the connecting process is
the change of a thing, then the thing is the
agent of interaction. () (Auyang 1998, p. 260) -
- Weed (2005) Auyangs conception of a state
space, prior to analysis is that of a reality
composed of actually indefinite strings of
activity.
13- For Chakravartty, if the account of de re
necessity is viable, then - it gives criterion to distinguish causal /
accidental regularities and - this criterion is explanatory (p. 130)
-
- How does Glennans revised account fare wrt (1)
and (2) in complex systems? - Are dispositions and de re necessity helpful
tools? - First, whilst guaranteeing existence of
sufficient truth maker, holism (obviously)
doesnt help determine minimally sufficient
(local) truth conditions. But these may
nonetheless exist, whenever system is
sufficiently isolated / carefully described. - Let us consider an example then..
14(Apoptosis)
Weinberg (2007), p. 354
15Asset pricing. Stylised facts
- Prob that tomorrows price goes up equals goes
down given available evidence (conditional
distribution is approx Gaussian). Yet - big (/little) price changes follow big (/little)
price changes changes not uniformly distributed
(volatility clustering) - asset returns at different t show a dependency
(volatility persistence) autocorrelation
(correlation between values at different t, as
function of t difference) of squared returns
decays slowly - distributions of unconditional returns at
frequencies of less than one month are
fat-tailed too many observations near the mean,
too few in mid range and too many in the tails to
be normally distributed. - Mechanistic account needs to answer, e.g.
- What causes crash/bubble?
- What explains time series?
Gaussian and other distributions
16Asset pricing. Time series
Lux Marchesi (1999), p. 397
17Asset pricing. Model
- Lux Marchesi (1999) analogy with phase
transition phenomena in physics
Summary from Kuhlmann (2009)
18Structural vs. mechanistic account
- What are the truth conditions for, e.g., Switch
of fundamentalists into chartists caused the
bubble? - What explains, e.g., specific event (crash) or
general pattern (fat tails, volatility
clustering/persistence)? - Smith (1998) no ontological commitment is needed
- fit between geometrical structure of model and
model of data is sufficient for approximate
truth - explanation of behaviour just is a geometrical
feature of dynamical model property of
representation of a concrete structure (cf.
Goldstein, 1996 Huneman, forthcoming) - no appeal to causal notions
19- For Glennan, instead, more is needed
-
- It is possible to formulate a mechanical model
using a state space representation but not all
state space models are mechanical models. The
requirements for a model being a description of a
mechanism place substantive constraints on the
choice of state variables (such as the fact that
state variables should refer to properties of
parts), parameters, and laws of succession and
coexistence. The satisfaction of these additional
constraints is what accounts for the explanatory
power of mechanical models. (2005 447-448) - The point is whether these additional constraints
can be met in complex systems..
20- Kuhlmann (2011) is halfway between Smith and
Glennan - although doesnt reify structure/geometry,
- contrasts compositionally complex mechanisms
(MDC, BA) and dynamically complex mechanisms
(e.g. nonlinear systems, chaotic systems, CA) - Similarity essential to explanation of both
- reference to interactions of systems parts (e.g.
agents, comparison of profits) - behaviour of the whole system must show some
degree of robustness (high volatility for wide
rage of parameter values, thresholds for
transitions) - Difference these features must be filled in
differently - behaviour of c.c.m.
- ontological details are important
- parts maintain identity and function throughout
process - behaviour of d.c.m. (e.g. apoptosis, asset
pricing) - ontological details are less important
/irrelevant (e.g. whether and what specific
agent buys or sells) - parts can change identity and function
(fundamentalists become chartists, optimistic
become pessimistic)
21- Result entities dispositions in complex
systems explain less than we hoped explanation
depends largely on structural features of the
arrangement. Depending on this - A has the capacity to produce B if not interfered
- A has the capacity to prevent B if not interfered
- And vice versa (B has the capacity to
produce/prevent A if not interfered) - Analogously, for apoptosis
- Depending on geometry, XIAP, by binding to Casp3,
which would normally prevent apoptosis, can
also promote it, due to XIAPs inability to
inhibit Casp9, which is then left free to trigger
Casp3 - Caspases are synthetised as inactive and become
active by proteolitic cleavage one can say they
are disposed to become active, but mechanists
(seem to) view procaspases and caspases as
different things with different functions
22Summary
- Glennans account and his latest views have
ambiguities as regards the nature of truth makers
and explanation - His account can be made coherent by employing a
dispositionalist metaphysics (Chakravartty) - In complex systems, talk of mechanisms and
causality as involving properties and (dynamical)
relations is legitimate - However, reference to specific parts with stable
identities and functions to explain behaviour and
provide truth makers is less appropriate
vis-à-vis structural features of the arrangement
23References
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