two concepts of mechanism is ps

7/25/2019 Two Concepts of Mechanism is Ps

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Two Concepts of Mechanism:

Componential Causal System and Abstract Form of Interaction

Jaakko Kuorikoski*

Penultimate draft, please do not cite this version

Forthcoming inInternational Studies in the Philosophy of Science

Although there has been much recent discussion on mechanisms in the philosophy of

science and social theory, no shared understanding of the crucial concept itself has

emerged. In this paper, a distinction between two core concepts of mechanism is made on

the basis that the concepts correspond to two different research strategies: the concept of

mechanism as a componential causal system is associated with the heuristic of functional

decomposition and spatial localization and the concept of mechanism as an abstract form

of interaction is associated with the strategy of abstraction and simple models. The

causal facts assumed and the theoretical consequences entailed by an explanation with a

given mechanism differ according to which concept of mechanism is in use. Research

strategies associated with mechanism concepts also involve characteristic biases that

should be taken into account when using them, especially in new areas of application.

1. Introduction

The concept of mechanism has recently played a central role in philosophy of science and

social theory. Within philosophy of science, the concept of mechanism has been used and

explored in the theory of causation, the theory of explanation and in the slightly less-

*Jaakko Kuorikoski works in the Trends and Tensions in Intellectual Integration project at the

Department of Social and Moral Philosophy, University of Helsinki. E-mail: jaakko.kuorikoski@helsinki.fi


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known literature on research heuristics. Among other things, it has been suggested that

mechanisms could provide a plausible metaphysics for causation and that they would thus

answer Humes challenge of providing the secret connexion between cause and effect

(e.g. Glennan 1996). Theories of mechanistic explanation and research strategies aim to

rectify law-centred views which are not applicable to the special sciences dealing with

multi-levelled causal complexity (e.g. Bechtel 2006; Bechtel and Richardson 1993;

Craver 2007). Examples of mechanisms in this literature are mostly taken from the life

sciences and engineering and often resemble something truly akin to machines.

The mechanisms that mechanistically orientated social theorists are talking about bear

little resemblance to the mechanisms discussed in current philosophy of science literature

(see essays in Hedstrm and Swedberg 1998). In the social sciences, mechanisms are

something that are thought to be suitably middle range for providing building blocks

for social theorizing, since they sound more plausible than strict covering laws and more

down to earth than grand social theory. They are supposed to be useful because they are

seen to straddle, on the one hand, the unconditional necessity of laws and context-bound

local contingencies and, on the other hand, inapplicable high theory and variable-centred

banal empiricism. The economic way of theorizing is often seen as a paradigmatically

mechanism-orientated enterprise. Some theorists even define the very concept of social

mechanism in terms of individual rational choice and equilibrium (e.g. Cowen, 1998),

although it is debatable whether much of such talk has drifted beyond the idea of causal

mechanisms altogether. At the very least, according to most theorists, social mechanisms

ought to be constructed on the basis of individual behaviour.


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In this article, I claim that there is indeed a fundamental difference in the concepts of

mechanism commonly used in these discussions, and that the crucial difference has to do

with the way in which theorizing with mechanism concepts proceeds. More specifically,

there are two concepts of mechanism corresponding to two particular sets of research

strategies or heuristics. First there is the concept of mechanism as a componential causal

system, which is accompanied with the heuristics of decomposition and localization.

Second, there is the concept of mechanism as an abstract form of interaction,

accompanied by the strategy of abstraction and simple models. The difference between

these two concepts has to do with the amount of abstraction in the identity conditions of a

mechanism kind and with the kind of causal complexity in the systems to which these

concepts are applied, especially whether the causal properties that define the mechanism

kind are monadic or relational. The first concept is associated with an analytic research

strategy of finding out more about the properties of the parts, and the latter concept with a

synthetic strategy of moving from the known properties of the parts to the property of the

whole. The two concepts occupy only a limited region of the whole possibility space

spanned by these considerations, but it is no accident that the rest of the space is

relatively devoid of life.

Although mechanistic theorizing is virtuous in many of the ways pointed out above, the

use of these mechanism concepts is also prone to specific kinds of characteristic fallacies

and biases. Making the distinction between these concepts is therefore important not only

in clarifying their explanatory roles and the differences in the causal facts presupposed to


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obtain in their use, but also in helping us to anticipate what can go wrong when applying

and reasoning with these concepts. However, the distinction does not map directly to any

distinction between the human and the natural sciences. As will be argued below, both

kinds of mechanism concepts can be and are used in both the human and natural sciences.

2. What is a mechanism?

It should be acknowledged from the very beginning that it is probably futile to try to

come up with a definition or analysis of the concept of mechanism that would at the same

time satisfy all theoretical needs, save all intuitions and fit actual research practice. Since

the use of the word mechanism is varied and often somewhat loose, both in philosophy

and in the special sciences themselves, there probably is no single correct way of

developing a taxonomy of the different concepts of mechanism either. The value of any

classification of concepts lies in the clarity it brings to the practices in which the concepts

are in active use. I believe the distinction made here passes this test of adequacy. The

following definition or characterisation of mechanisms in general by William Bechtel and

Adele Abrahamsen is a good trade-off between informational content and scope of

applicability and will thus serve as a starting point:

(M) A mechanism is a structure performing a function in virtue of its component

parts, component operations, and their organization. The orchestrated functioning


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of the mechanism is responsible for one or more phenomena. (Bechtel and

Abrahamsen 2005, 423)

M is designed to capture a number of characteristic properties of mechanisms:

mechanisms are identified through their causal role or function in some larger system or

context; mechanisms are complex entities consisting of parts enjoying at least some

amount of ontological and causal independence; mechanisms do what they do by virtue

of what their parts do and how the parts interact and, finally, the interaction of the parts is

in some sense regular and orderly. Along with Bechtel and Abrahamsen, mechanisms are

here taken to be concrete particulars, that is, real things in the world, but explaining with

and reasoning about mechanisms to be cognitive activities and thus requiring

representations of mechanisms (ibid., 424-425). This essay is about concepts of

mechanisms, but when these concepts are applied correctly, they pick out things in the

world with the appropriate causal properties. What M says about mechanisms as mind-

independent causal entities can easily be translated into requirements concerning models

or theories of mechanisms. Correspondingly, although practising social scientists and

theorists usually speak of mechanisms as parts of a theory or a model (see essays in

Hedstrm and Swedberg 1998) and philosophers as mind-independent parts of the ontic

furniture of the world, in practice this difference in parlance does not amount to much.

With M at hand, it is relatively easy to account for the usual perceived virtues of

mechanistic theories and explanations. Mechanisms need not produce universal covering

laws, because the manifestations of their operation can be frustrated or blocked by


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contingent causes internal or external to the mechanism. Thus the observable

consequences of mechanisms at work can have exceptions, yet their behaviour usually

exhibits some amount of regularity due to the specific organization of the components.

Mechanisms are not totally bound to specific contexts either, since they are made of

components with causal properties having at least some amount of external validity. Thus

knowledge of mechanisms can facilitate prediction and generalization. Referring to

underlying mechanisms can be explanatory even though they do not need to be described

in terms of an over-arching high theory, and theories of mechanisms provide deeper

understanding, more answers to why- and how-questions, than mere enumeration of

empirical facts and establishment of correlations. Theories or models of mechanisms

accomplish this by opening black boxes, that is, by explaining some macro behaviour in

terms of the behaviour and organization of its micro constituents. Mechanisms can thus

explain constitutivelyhigher level properties and dispositions of the embedding system

by the lower level causal powers of its parts. Mechanisms can also explain causallyor

etiologicallyby mediating between temporally ordered local changes in the system (see

e.g. Craver 2007, chpt. 4).

Hedstrm and Swedberg point out that the essence of mechanism (as an ism) is not to

be found in any definition of the key theoretical term, but in a particular style of

theorizing (Hedstrm and Swedberg 1998, 25). In fact, M has not been developed

through the usual philosophical process of testing subsequent conceptual analyses against

pre-theoretical intuitions of what are and what are not really mechanisms. Neither is it

designed with a view of mechanisms as a fundamental ontological category needed for a


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plausible metaphysics of causation. Instead, it is the byproduct of a philosophical

reconstruction of a particular family of research strategies orheuristics. The important

work done in scientific practice with the concept of mechanism defined in M is in

directing theorizing, modelling and empirical research. Differences in the concept of

mechanism used, differences in the identity conditions for what it is to be a mechanism of

a certain kind, entail differences in what kinds of further questions are asked and what

avenues of further research are pursued when a certain kind of mechanism is perceived to

be operating within some domain of phenomena. It is in terms of this crucial heuristic

role of the concept that the important distinction discussed below emerges.

3. Mechanisms as componential causal systems

M is a result of philosophical interest in research strategies used in the study of complex

systems in the life sciences, such as molecular biology and neuroscience. According to

Bechtel and Robert Richardson (1993), the study of these kinds of complex causal

systems often proceeds according to the heuristics ofdecomposition and localization

(DL). The word heuristic here does not refer to a more or less automatic psychological

mechanism, but to an informal method or rule of thumb for how to carry out research in

some loosely defined context. The ultimate goal of the use of DL heuristics is to provide

mechanistic (constitutive) explanations of system- or macro-level properties. The DL

procedure goes roughly as follows. First, the different phenomena that the system of

interest exhibits are identified. Then the phenomenon of interest isfunctionally


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decomposedin the sense of being analyzed into a set of possible component operations

that would be sufficient to produce the phenomenon. One can think of this step as

thinking of a preliminary set of simple functions that taken together would constitute a

more complex input-output relation (the system-level phenomenon). The system is also

structurally decomposedor analyzed into a set of component parts. The final step is to try

to localizethe component operations by mapping the operations onto appropriate

structural component parts. The primary meaning of localization here is the pairing of

operations and parts, not (necessarily) that of locating something in physical space. The

idea is thus first to ask what kinds of more basic properties or behaviours could, taken

together, possibly result in the explanandumbehaviour and then try to find out whether

the system is in fact made of such entities that can do the jobs required. If this cannot be

done, the fault may lie in the manner of functional or structural decomposition and these

may then have to be rethought. In the end, even the identification of the target

phenomenon or system may have to be revised. The identification and decomposition

procedures will in the beginning be guided by earlier theories and common sense, but

empirical evidence can always suggest that a thorough reworking of the basic ontology

and the form of the possible explananda may be in order. (Bechtel and Richardson 1993)

Although M is derived from research on the use of decomposition and localization

heuristics, it does not by itself entail it. The claim made here is that M is compatible with

(at least) two, more substantial, concepts of what mechanisms are and that these concepts

entail different research heuristics, namely, DL and what I call the strategy of abstraction

and simple models.


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In order to get from M to DL, we need to add a few extra ingredients to the mechanism

recipe. Function localization makes sense only if the component parts of the system have

different causal properties that are to a large extent constituted and thus explainable by

their intrinsiccausal make-up. Function localization thus requires that the system is

nearly decomposablewith respect to the (kinds of) causal properties figuring in the

functional decomposition in the following sense (cf. Simon 1962)1: the intrinsically

explainable causal powers of the component parts are more important for the explanation

of the macro behaviour of the system than the relational causal powers of the components

constituted by their environment and interaction. The parts of the whole should therefore

exhibit sufficient causal variety to be able to account for the different causal roles

required to produce the explanandumphenomenon. This variety should in principle be

apparent even before the functional decomposition of the macro behaviour into

component functions. The concept of mechanism appropriate for the use of DL is

therefore that of a set of component parts fulfilling different causal roles within a nearly

decomposable system. These different causal roles together produce or realize some

causal property of the system. Let us call such mechanisms componential causal systems

(CCS). Whatever regularity and external validity the behaviour of the system may have is

due to the intrinsic causal powers of the component parts and to the stability of their

organization. Most of the recent philosophy of science literature on mechanisms seems to

concern primarily mechanisms in this particular sense (e.g. Bechtel 2006; Craver 2007;

Glennan 1996; 2005 and especially Machamer et al. 2000).


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When macro behaviour has been decomposed into localizable component behaviours, the

inner mechanisms of the components responsible for their behaviour can in turn be

mechanistically explained by opening the component black box by repeating the

decomposition and localization routine. The inner workings of the cell were worked out

by structurally decomposing the cell into cell organelles and pairing them with cellular

operations. For example, cellular energetics was localized in the mitochondria (the initial

localization hypothesis was partly argued for on the basis that the organelles showed

evidence of the relevant component operations even when isolated from an intact

embedding cell). The organelles were then structurally decomposed and the

subcomponents paired with subsequent component operations: the mitochondrion was

itself structurally decomposed and the major biochemical metabolic operations

subsequently localized within this structure, thus forming a link between cytology and

biochemistry. (Bechtel 2006, 190-222) Mechanistic research programmes thus tend to

move progressively from a higher level of mechanism(Craver 2007; Glennan 2005) to a

lower one and are in this sense reductionist. Levels of mechanisms are a type of

ontological level (cf. Mayntz 2004) or level in nature in that they should be thought of as

features of the world, not of our conceptualisation of it.2The relation between a higher

and a lower level of mechanism is compositional: the lower level components of a

mechanism are its proper parts (and thus usually strictly smaller than the mechanism).

Parts are components only in relation to a specific behaviour that the embedding

mechanism exhibits and levels of mechanisms are thus local and system specific, not

global. Thus levels of mechanism do not order plain objects, but objects together with

their causal properties in relation to another (higher level) causal property. (Craver 2007,


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188-195) Consequently, the identity conditions of a given mechanism kind are often

thought to include the material basis realizing the causal functions of the component

parts. In Mario Bunge words (2004, 195), CCS-mechanisms are seen as stuff-dependent

and system-specific. Notice that this claim about the identity conditions of these

mechanism kinds is a hypothesis about a systematic connection between the types of

causal systems being studied and the amount of causal content put into concepts used in

reasoning about those systems, not a claim about any kind of necessary conceptual truth

or metaphysical thesis.

Decomposition and localization are most easily understood when the causal macro

properties of the system depend on the intrinsic and varied causal properties of spatially

bounded parts and their respective spatial organization and the causal flows between

them. In such a case, the components can meaningfully be individually investigated as

individual input-output systems even when isolated from the larger system in which they

are embedded. Paradigmatic examples of such decomposable mechanisms are pieces of

machinery and complex organisms with their functionally differentiated organs, cases in

which the spatial organisation of component parts is stable. When referring to

componential causal systems, the word mechanism is not a totally dead metaphor in that

individual parts serving different functions imply a design as in a mechanical contrivance

built for a specific purpose (cf. Harr 1972, 118; Ruse 2005).

However, there are also theories and explanations in the social sciences that rely on a

concept of mechanism as a componential causal system, but in the social sciences the


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relevant form of localization of component functions is usually that of mapping

component operations onto specific social institutions. As examples of componential

social mechanisms, consider the different mechanisms through which central banks

influence the money supply: open-market operations, different interest rate instruments

(such as the discount rate for discount window borrowing) and the direct control of

reserve requirements. The central bank can buy or sell government securities to and from

commercial banks in open financial markets and thus influence banks reserves, which in

turn affect the amount of money in the economy. The central bank can also set the rate at

which banks can obtain additional reserves by directly borrowing from the central bank,

usually at a slightly higher rate than the short-term market rates. The central bank can

also directly change the ratio of reserves to granted loans that the commercial banks are

obliged to live by. Each one of these mechanisms can be localized to ostensibly different

parts of the financial system (open money markets, auctions and regulative legislation)

and a common part of the banking sector, namely the reserves. These institutional parts

are real components in the sense that they each possess stable clusters of properties, they

can be epistemically accessed by multiple independent means and they can be causally

intervened on in a relatively independent manner (cf. Craver 2007, 131). Together these

parts constitute the system-level property of the central banks influence on the money

supply. The important thing here is the mapping between the component operations and

parts, not where the parts are spatially located. Fittingly enough, the standard text-book

account of the bank-mediated money-multiplying mechanism between new money

issued by the government and the effective increase in liquidity in the economy, is also

one of Nancy Cartwrights examples of socioeconomic machines(1995).


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Many instances of the old structural functionalist sociology can also be seen as

employing a CCS view of society as a complex system and the associated functional

localization heuristic. In this case, causal functions contributing to or necessary for the

well-being of the society are localized to different social institutions and practices. The

focus is on the properties of a part (an institution) from the viewpoint of a hypothesized

need of the system (society). The organismic analogies of physiologists such as Walter

Cannon and Lawrence Henderson, according to whom governmental institutions could be

seen as organs keeping society in a societal homeostasis, were influential on later

functionalist thinking, such as the work of Talcott Parsons (Cross and Albury 1987).

This anatomical-physiological view was also expressed by people with markedly

different social views, such as Carl Menger and Friedrich Hayek, who both claimed in a

similar vein that social institutions should be seen as organs of an encompassing social

organism (Vromen 1995: 174-176). Analogies drawn with machines and organisms

immediately suggest the idea of an interconnected system of causally and ontologically

separable components with differing causal roles or functions.

What it means to explain something with a mechanism of a certain kind depends on the

identity conditions of the mechanism kind in question. As was suggested above, since the

CCS conception is associated with a progress of inquiry geared towards descending

levels of mechanisms, the identity conditions of CCS mechanisms are tied to the causal

nature of the components. The most straightforward and extreme case of a CCS

mechanism being the same as some other mechanism is when the constituent parts of


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the mechanisms in the different contexts are themselves identically constituted. With

such strict identity conditions, the identity of a mechanism is truly stuff-dependent. Most

cases of ontological unity in physics are extreme cases of such identity in that there really

is only one relevant level of mechanism in which the unity resides (e.g. light and radio-

waves are simply different kinds of behaviour of a qualitatively identical electromagnetic

field). Everything that is known about the isolatedorshielded functioning of the

mechanism in the old context can now be transported to the new context. These include

things such as what happens if one removes, alters or re-configures the components,

introduces previously known interfering factors within the mechanism or alters the causal

inputs within their previously observed ranges. Whether what happens to the mechanism

under previously unobserved boundary conditions can be predicted depends on how well

the properties of the components are known.

However, in most cases, theoretically interesting applications of CCS concepts do not

literally concern such strict identity. The identity conditions for a CCS mechanism can be

loosened to include only the localizability of the component operations and the specific

organization of the parts realizing them. This, usually necessary, loosening of the identity

conditions opens the door to possible fallacies in reasoning with the concept in question.

4. Mechanisms as abstract forms of interaction

What about the mechanism of evolution by natural selection? Evolution by natural


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selection is usually functionally decomposed into variation, inheritance and selection.

None of these component operations can be straightforwardly localized into

subpopulations or parts of the ecosystem there are no natural bureaus of mutation or

quality control. When the functional decomposition is taken further, properties such as

fitness and the predation coefficient appear which seem to be candidates for localization

into the obvious component parts, namely, individual organisms. However, fitness is a

paradigm case for a relational concept that is often mistaken for an intrinsic property of a

single organism (Wimsatt 1980). In the case of the mechanism of selection, the causal

properties relevant for any sensible functional decomposition of the original mechanism

are essentially relational and cannot be neatly paired with what would seem to be its

constituent parts.

In many cases, the causal powers of the constituent parts of a complex system (defined

according to some pre-theoretical ontology) are already known and do not exhibit such

variety that could account for the causal roles required for the constitution of some

macro-property of interest (according to some preliminary functional decomposition). In

some branches of the social sciences, especially in mainstream economics, there seems to

be an overwhelming consensus on what the causal constituents of the macro behaviours

of interest are and even apparent certainty about their causal properties and behaviour;

the relevant or legitimate causal constituents are individuals, households or firms and

their only causally relevant behaviour is utility maximization. In contrast, the macro

behaviour of interest is dependent on the cumulative interactions and interdependencies

of the parts. For example, in a less than fully competitive market situation, the behaviour


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of every single agent is in principle dependent on the actions of every other agent in the

system. However, for DL to be informative and tractable, the relevant properties of the

component parts should be analyzable in isolation of the embedding system. Although

component operations such as buying and selling seem to be straightforwardly

attributable to agents doing the buying and selling, the relevantproperties (preferences,

strategies, aggregate demand and supply) of the agents are in reality essentially relational.

Therefore, in cases of non-decomposable systems (with respect to the causal properties

relevant for the functional decomposition), opening the black box responsible for some

observed behaviour cannot be a matter of pairing component operations with different

component parts (such as different groups of people) with varied intrinsic causal powers.

Decomposing the individual behavioural dispositions of constituent parts (such as

individual agents) into some set of lower level component operations (such as

psychological mechanisms) is also unhelpful for understanding the original macro

phenomenon, since the intrinsic causal properties of the parts are not of primary interest.

Many social systems have, from the social scientists point of view, aflat hierarchy

(Simon 1962) in that they are not made of a large variety of separate components with

intrinsically different causal properties. This means that going further down the levels of

mechanisms by examining the way the component parts are themselves causally

constituted may not be very informative about the behaviour of the system as a whole.

If pairing component operations with component parts appears to be a non-starter, some

other way of making sense of the realization of the component operations has to be

utilized.Abstractionis the procedure of intentionally omitting from the description of a


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system some of its details and causal factors known to be relevant (Jones 2005).3In

contrast to reduction achieved by going down the levels of mechanisms, conceptual

abstraction takes place on a single level of mechanism: the level of abstraction is not

(necessarily) increased or decreased when the focus is shifted from a mechanism to its

constituent parts or vice versa. Generalization and understanding can be achieved by

mentally or virtually stripping from a particular causal system some of its causal

properties. Similarly, more abstract, and thus more general and tractable, mechanism

concepts can be generated from a more concrete description of a mechanism type by

omitting one or more of its characteristic causal properties. Renate Mayntz (2004) uses

the following sequence of mechanism concepts as an example of such a conceptual

hierarchy: positively path dependent technological innovation, increasing returns and

positive feedback. Each concept in the series has a wider scope of application and is

consequently less informative (implies less about the system to which the concept is

applied to) than the previous one. These mechanism kinds cannot be related as levels of

mechanisms: increasing returns is not a concrete component part of positive feedback or

vice versa. Each mechanism kind can also be realized by any number of different causal

bases. The identity of a mechanism is therefore not dependent on the nature of the causal

material, but on theformof the interaction between the constituent parts and the degree

of abstraction of the description of that interaction. Let us call such a mechanism concept

an abstract form of interaction(AFI). Some examples of such interaction forms are

different market forms, selection, crowding out, diffusion, non-intended segregation (as

in Thomas Schellings checkerboard-model), vacancy chains and self-fulfilling

prophecies.


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Notice that although the condition of near decomposability of the embedding system has

been dropped, AFI mechanisms are still compatible with M: they are structures

performing functions by virtue of their component parts, component operations, and their

organization, and the orchestrated functioning of these mechanisms is responsible for one

or more macro phenomena. The important difference with CCS mechanisms is that the

component operations cannot be straightforwardly mapped onto the intrinsic causal

properties of the component parts and that the full causal make-up of the parts is not

therefore included in the identity conditions of the mechanism concept. Notice also that

although abstraction itself takes place on a single level of mechanism, mechanistic

explanation with an AFI mechanism still explains macro-level properties in terms of the

behaviour of its micro-parts. Explanation through the use of an AFI-mechanism involves

going down levels of mechanisms and is in this sense reductionistic in the same way as

explanation with a CCS mechanism.4It is also important to keep in mind that AFI is a

label for a conceptof mechanism; mechanisms themselves are always concrete things

existing in space and time and therefore cannot be abstract in any meaningful sense.

Since the identity of an AFI mechanism is dependent on its place in the hierarchy of

abstraction, and since especially in the rational choice orientated social sciences this

abstract definition usually has something to do with expectations and preferences,

regardless of whether they are actually causally realized by intentional action, it is

commonplace to speak of the mechanism as the logic of action or the logic of the

situation (cf. Popper 1957, 149). One does not often hear about the logic of the cell or


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that of the combustion engine. Since the form of interaction is not in itself dependent on

the way the causally relevant properties of the component parts are constituted (i.e. on the

explanation of the relevant behavioural dispositions of the components), the same sample

models and hence the same mechanism schemata can be utilized in many different

kinds of contexts or domains. AFI mechanisms are usually thought of as not being stuff

dependent or system specific. Consider Harold Hotellings Main street duopoly

argument (Hotelling 1929). This simple model depicts two vendors on a street and seeks

to ascertain the optimal place for a vendor given that customers are distributed uniformly

along the street and that they always choose to deal with the nearest vendor. The answer

is that both vendors will be located in the middle (which incidentally happens to be the

socially worst outcome in terms of the average distance the customers need to travel).

The model has in different hands mutated from ice cream dealers on a beach to political

parties fighting for voters on a political left-right axis. Here the common abstract

interaction form, the common mechanism, is just a one-dimensional metric space that is

inhabited by two quasi-intentional agents strategically optimizing their share of the space.

Exactly what formal features of interaction are entailed by a given mechanism attribution

is by no means a settled matter. A good example of a mechanism concept that is used in

slightly different senses in different contexts is the market. Just think of what different

kinds of things describing some social constellation as a market can be expected to

entail. In different contexts, significant differences can be found in the explicitness and

efficiency of a common currency, property rights and the enforcement of contracts. Then

there are the various different market forms distinguished by specific trading procedures


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or imbalances in market power. Using the same word to refer to mechanism concepts of

differing levels of abstraction in different contexts is a common source of confusion.

If the complex system cannot be decomposed into chunks in such a way that the relevant

causal properties of the parts could be investigated in comfortable isolation, something

other than DL is evidently needed. Process tracing (as in Steel 2004) may not be a viable

empirical strategy either, since detailed investigation of individual interactions and causal

flows between constituent parts may obscure the bigger picture of the pattern of

interactions. AFI mechanisms often (but not always) concern the aggregation of simple

behaviours of some micro-units into a novel macro- or population-level phenomenon.5

However, the number of different kinds of units is usually limited and the localization of

component operations to unit-kinds is not possible.6Functional localization to units or

groups of units is problematic precisely because the interaction is more important for the

macro behaviour of the population than the intrinsically explainable causal properties of

the units. Consider the well-known difficulties in trying to study empirically market

supply and demand separately, pointed out in a clear manner already by Trygve

Haavelmo (1944), among others. Similarly, natural selection is not, and should not be

studied as, a componential mechanism embedded in a decomposable complex system

(Skipper & Millstein 2005). Conceptualizing fitness as an intrinsic property of an

organism or competitiveness as an intrinsic property of a firm are typical examples of

conceptual errors resulting from attempts to conceive the mechanisms of the market or

selection as componential causal systems.


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If the system cannot be literally decomposed into functionally distinct components, then

one has to live with the functional or operational decomposition. However, the resultant

macro behaviour of multiple overlapping interaction forms is usually not transparent and

it is of dubious epistemic value to substitute an ill-understood model of the world for the

ill-understood world itself. This is why it makes sense to study simple constituent

submodels of different kinds of interaction forms, different AFI mechanisms, separately

and only when the behaviour of these simple models is well understood, should these be

combined to form models of greater empirical congruence. The models should be of

sufficient degree of abstraction in order for the relation between the causal properties

together with interaction of the micro-constituents and the macro-behaviour to remain

tractable. (Boyd & Richerson 1987) Thus we arrive at the family of research heuristics

characteristic of investigating AFI mechanisms: abstraction and simple-models strategy,

the staple of most model-based social science and much of model-based biology (see

especially Levins 1966).

What can be concluded from the hypothesis that a certain AFI-mechanism is operating in

some domain of phenomena? First, familiar patterns of inference derivable from the

essence (i.e. from the interaction form) of the mechanism can now be used in the new

domain. If some social constellation can be meaningfully seen as a competitive market,

the usual microeconomic conclusions concerning the pattern of social exchange and

allocation of whatever it is that counts as commodities can be expected to apply. If

some relation structurally resembles a principal-agent relationship, one begins to look for

signs of adverse selection and moral hazard. However, it is often tempting to assume that


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if two systems exemplify a similar AFI-mechanism, the causal constituents of those

systems should also share other causal properties not directly related to the mechanism in

question. This opens the door for characteristic fallacies in reasoning with AFI

mechanisms.

5. Characteristic biases of mechanistic theorizing

Research heuristics or strategies are not logically bullet-proof inference schemas or

algorithms that guarantee a successful result. Instead, they are purpose relative

approaches or sets of tentative instructions that have proven to be useful in some limited

problem area, most of the time. Heuristics can lead to wrong results or dead ends, but

when they do, they usually do it in a way that can be anticipated beforehand. Heuristics

have characteristic biasesthat one should be aware of when using them. As both concepts

of mechanism correspond to a particular research heuristic and heuristics always bring

with them a set of characteristic biases, we may expect that modelling and reasoning with

CCS and AFI mechanism concepts are prone to different kinds of characteristic mistakes.

Biases inherent in the application of mechanism concepts and associated research

strategies are typical biases of reductionistic research strategies, which have been

explored in depth by William Wimsatt (1980; 2006; 2007). Here it should be noted that

reductionism is not an evaluative term. Even though reductionist research heuristics have

characteristic biases, they are often the best or only means of scientific progress one


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just needs to be careful when using them. Most importantly, we often learn the most

valuable lessons when we realise why some reductionistic heuristic fails in a given case.

Some reductionistic biases are associated with both mechanism concepts. For example,

any mechanism attribution requires that a boundary between a system and its

environment has to be drawn. However, the original system-level explanandummay in

the end turn out to be a relational property and looking exclusively within the system for

the explanatory mechanism may thus be futile. Use of either of the mechanism concepts

can also lead one to forget that the way the system/environment boundary is drawn is

itself only a tentative theoretical hypothesis and interactions not respecting this boundary

may be easily missed. However, there are also biases that are specific to the two distinct

mechanism concepts.

5.1. Biases characteristic to the CCS concept

Since the characteristic property of CCS mechanisms is the near decomposability of the

embedding system and the associated possibility of the localisation of component

functions, characteristic biases of CCS mechanism concepts usually result in what

Wimsatt calls functional localisation fallacies. Sticking too closely to the pre-theoretical

ontology of the whole and its component parts may hinder the formulation and study of

properties and interaction at some other level of organization. For example, too eager an

application of DL can lead to treating relational properties as if they were monadic or


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intrinsic - a necessary condition for the localization of component operations into

component parts. An important example of such a localization fallacy in the social

sciences is the assumption (often taken as the default) that the suboptimal performance of

an organisation is due to the intrinsic properties of a particular member or class of

members. For example, corruption leads to suboptimal behaviour at the system level (e.g.

bad governance) and is often fought against by trying to change the properties of the

malfunctioning parts (corrupt officials). This can be done, for example, by increasing

their pay checks, by increasing the potential cost of getting caught or by replacing

officials with new ones. However, in many cases, corruption is structurally embedded in

the system in ways that force the holders of the positions to succumb to corruption no

matter what their intrinsic properties are. (Epstein 2008)

The reverse form of the function localization fallacy is the reification of a component

operation that is dependent on the causal contribution of some component part as an

intrinsic functional property of that component part. The fact that some aspect of

systems macro behaviour may be present or absent whenever some component part is in

operation or not, does not yet mean that that aspect or component operation can be

localized as a property of that component part. Prominent examples of this fallacy are the

attribution of cognitive functions to brain areas solely on the basis of observed effects of

brain lesions and the attribution of functions for DNA sequences on the basis of a

correlation between mutations and phenotypic abnormalities. The tendency of treating

apparent component parts as nearly decomposable and ignoring their interaction leads

easily to mistaken attributions of truly systemic properties to component parts.


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25

Similar mistakes can also be made from the bottom up by assuming that the properties

of isolated structural parts are context-insensitive or lack significant interaction effects

and can thus be straightforwardly combined to explain or predict a system-level

phenomenon (so called atomistic fallacy). Frequency dependence of causal effects is

probably the simplest case: increasing the wealth of an individual is a reasonably

effective strategy of increasing his or her subjective well-being or happiness, but

simultaneously increasing the wealth of a group of people may not have a similar

aggregate effect, since the feeling of happiness is usually dependent on ones relative

position to ones peers. Satisfaction with the pre-theoretical ontology and a simple

mapping between the functions and the structural parts might also mean that once a

function has successfully been attributed to a part, the search for other possible functions

for that particular part or possible back-up mechanisms for that particular function are

ignored. (Wimsatt 2007, Appendix B)

5.2. Biases characteristic of the AFI concept

The first characteristic problem with AFI concepts is that it is often the case that the

mechanism concept cannot be legitimately used in the domain in question with the same

level of abstraction as in some other, more familiar, setting and that its use may not

therefore allow similar inferences in the different contexts. The uses of the concept of

market mechanism in different strands of economics-inspired social science, such as the


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26

political market for votes and favours (e.g. Downs 1957), the markets for religious

services (e.g. Young 1997) and the different markets in science (e.g. Mirowski and Sent

2002), offer a plethora of examples of this danger. Although there might be some

common core of the concept of market discernible in these diverse fields, free exchange

of commodities between vendors and customers mediated by some form of currency,

one usually cannot derive and explain any macro explananda from this common core

alone. In very few of these markets can anything like a pareto-efficient market

equilibrium be expected to obtain and therefore the quick inference from the same

mechanism, in this case only the most abstract and austere meaning of the market, to

the same effects would be erroneous. Instead, the important explanatory factors most

often are institutional or psychological factors that differ from case to case (Lehtinen and

Kuorikoski 2007).

In contrast to CCS mechanisms, the identity conditions of which usually include causal

details of their constituent parts, the use of an AFI mechanism concept only facilitates

inferences from the interaction form of the constituents, not from any other causal

properties of the constituents. It is a common fallacy to infer from the use of a certain

AFI concept that the constituents of the system so described have other causal features

common with some other similar, often exemplary or paradigmatic, AFI mechanism. This

fallacy simply stretches an analogy or metaphor too far. For example, although ideas,

customs or fads can perhaps be seen as subject to a form of cultural selection analogous

to natural selection, it cannot be inferred from this alone that these memes have any

relevant causal properties in common with genes (evolutionary economists certainly are


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not immune to this fallacy, see Vromen 1995). Similarly, if the assumption of optimizing

behaviour is in some context argued for on the basis of some selection mechanism (only

profit maximizing firms stay in the market), then one should not expect any such

responses from the system that would require that the constituent parts actually optimized

intentionally.

The third danger or bias inherent in the use of AFI-mechanism concepts is that since the

mechanism schema necessarily abstracts from the causal details of the investigated

system, the attribution of a particular concept to the system may obscure the fact that the

system may have other important causal properties besides the behaviour resulting from

the particular mechanism. Describing some system as a particular AFI-mechanism

always, but often implicitly, shifts the explanatory focus and may thus cause myopic

research practice. This worry is particularly pertinent in the case of attempted unification

via a set of similar mechanism schemas, since such unification also means that the

questions asked in the unified or conquered field change. One instance of such an attempt

at unification is the use of economic models of rational choice in the social sciences,

which is often explicitly argued for on the basis of some intrinsic virtues of unification

and mechanistic explanation (e.g. Lazear 2000, Mki 2001). Not surprisingly, rational

choice based political science has been accused of shifting the focus of research from

historical and process-specific issues to less important and highly generic and abstract

systemic properties of voting systems (Green and Shapiro 1994).


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6. Conclusions

From the core concept of mechanism, more or less captured in M, there is an interesting

further distinction to be made corresponding to two distinct ways of investigating and

theorizing about causal systems. If the system in which the putative mechanism is

embedded is nearly decomposable into distinct components with intrinsically constituted

and diverse causal properties, one can try to localize and map the sub-operations of some

macro behaviour of the system onto a set of these causal components. This set of causal

components is then the mechanism responsible for the behaviour in question.

Paradigmatic examples of such causal componential system can be found in machines

and organisms, but an analogous conception can also be discerned in some social science

contexts as well. In the latter case, the relevant localization is not straightforwardly

spatial but instead a localization of a component operation into a specific social

institution.

If the causal properties relevant for some macro behaviour cannot be localized neatly

onto the constituents of the system (defined according to some reasonable ontology), but

instead the most relevant causal properties are relational and emerge from the interaction

of the constituents, then the best bet is to ignore some causal detail by abstraction and

then try to model some of the component operations in a tractable manner. In this case

the deeper causal nature of the constituents is not as important as the abstract form of the

interaction between them. This is why it is the latter that is often thought of as


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29

constituting the identity of the mechanism responsible for the macro behaviour in

question.

The general conception of what a mechanism is dictates what it is to be a mechanism of a

certain kind. Since CCS mechanisms are associated with heuristics geared towards

opening localized component black-boxes, the identity conditions of CCS mechanisms

are dependent on the causal nature of the constituent parts. Correspondingly, since all

lower-level causal details are not that interesting with respect to behaviour realized by

AFI mechanisms, the identity conditions of AFI mechanisms usually only include the

form of the causal interaction, not the exact causal nature of the interactors. This is a

claim about a tendency to conceptualize certain kinds of systems in a certain way, not a

conceptual a priori necessity or a metaphysical thesis about the fundamental ontology of

mechanisms. As a consequence of this, the distinction presented here is not always clear-

cut and nothing prevents combining these concepts in a model, theory or research

programme. For example, the open market operation mechanism of interest rate control

includes an AFI mechanism, namely, the financial market.

What one takes to be the identity conditions of a mechanism of a certain kind dictates the

way one explains, investigates and reasons about the systems to which the mechanism

concept is applied. Thus the distinction made here will clarify and make sense of some of

the differences and peculiarities in mechanistic research programmes in different

scientific fields and domains of application. Most importantly, since the two concepts

correspond roughly to two different sets of research strategies or heuristics, the


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30

identification of a mechanism concept used in some setting as a CCS or an AFI type of

concept should point to the possibility of characteristic errors resulting from the biases of

the associated research heuristics.

Acknowledgements

An earlier version of this paper was presented at the workshopMechanisms in the

Sciences: Concepts, Discovery, Explanation, University of Helsinki, August 2007. I

would like to thank all the discussants and the members of the Philosophy of Science

Group for their comments. Special acknowledgements go to Peter Hedstrm, Daniel Steel

and Petri Ylikoski for their detailed and insightful comments. I also owe thanks to the

three anonymous referees of this journal for their valuable suggestions and to the Finnish

Cultural Foundation for generously supporting this research.

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1This is one sense of near decomposability in Simons classic article. I am not going deeper into exegetics

here in trying to question whether there is a singular concept of near decomposability behind the different

definitions and uses in the article (such as the near decomposability of a flow matrix or the independence of

long term aggregate dynamics with respect to short term component dynamics).2Craver uses the term levels of mechanism to distinguish it from other kinds of ontological levels, such as

mereological levels or levels of aggregation. Renate Mayntz uses the more ambiguous term of ontological

level in order to draw a contrast to levels of abstraction, which order representations, not things in the

world.3With abstraction, I refer to both vertical and horizontal isolation, as discussed by Uskali Mki (1992).

Horizontal isolation means completely omitting or excluding some causal factors or features from a model

and vertical isolation means simplifying but still retaining some causal feature by stripping awayparticularities (e.g. moving from a parametric to an unspecified functional form). Although Mki

characterizes the latter as vertical, both forms of theoretical isolation remain within the original level of

mechanism.4AFI concepts can, and often do, contain references to causal factors in multiple levels of mechanisms.

Many mechanism types in the social sciences refer simultaneously to groups, agents, preferences etc. The

constellations of causal properties picked out by AFI concepts are thus examples of entities that Wimsattdescribes as being in between levels (Wimsatt 2007, 217). The use of AFI-concept is also not necessarily

linked to methodological individualism; AFI-concepts could be applied to the interaction of social units of

meso- or macro-level. However, it should be stressed that these kinds of spatial metaphors can beextremely misleading: mechanisms themselves do not reside in any particular level of reality (see also

Craver 2007, chapter 5). Mechanisms are constellations of causally interacting objects and are thus alwayssimply located in (the one and only) space-time.5Although many seem to treat it as such, aggregation in itself can hardly be seen as a type of mechanism.


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6As an anonymous referee correctly pointed out, sometimes heterogeneity can itself be a causally relevant

property (selection is a good example). However, in most cases what is relevant is the heterogeneity itself

(a relational or system-level property), not which particular units have which particular properties.

two concepts of mechanism is ps

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