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Models as epistemic artefacts: Toward a non-representationalist account of scientific representation

January 2005

Thesis for: PhD

Authors:

Tarja Knuuttila

University of Vienna

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Tarja Knuuttila

Models as Epistemic Artefacts:

Toward a Non-Representationalist

Account of

Scientific Representation

Philosophical Studies from the University of Helsinki 8

Tarja Knuuttila

Models as Epistemic Artefacts

What are the origins of the epistemological difficulties

concerning representation? How have philosophers of

science studying models and representation reacted to these

difficulties? How else might scientific models be approached

if not representationally? In addressing such questions,

Models as Epistemic Artefacts: Toward a Non-Representationalist

Account of Scientific Representation seeks to reinvigorate the

philosophical discussion of models and scientific repre-

sentation by proposing a new, artefactual approach to

models that loosens their epistemic value from representation

and ascribes it instead to their materially embodied con-

straints and interactive enablings. It also proposes that the

very problem of representation should be released from its

representationalist underpinnings. After a contextualising

introductory essay, the first two original research articles

deal with more general issues concerning representation,

while the remaining four articles examine representation

in the context of modelling. The articles also take part in

the current discussion of representation in science and

technology studies, semiotics and cognitive science.

Filosofisia tutkimuksia Helsingin yliopistostailosofisia tutkimuksia Helsingin yliopistosta

ilosofisia tutkimuksia Helsingin yliopistostailosofisia tutkimuksia Helsingin yliopistosta

ilosofisia tutkimuksia Helsingin yliopistosta

Filosofiska studier från Helsingfors universitetFilosofiska studier från Helsingfors universitet

Filosofiska studier från Helsingfors universitet

Philosophical Studies from the University of HelsinkiPhilosophical Studies from the University of Helsinki

Philosophical Studies from the University of Helsinki

Publishers:ublishers:

ublishers:ublishers:

ublishers:

Department of Philosophy

Department of Social and Moral Philosophy

P.O. Box 9 (Siltavuorenpenger 20 A)

00014 University of Helsinki

Finland

Editors:Editors:

Editors:

Marjaana Kopperi

Sami Pihlström

Panu Raatikainen

Petri Ylikoski

Bernt Österman

ISSN 1458-8331

ISBN 952-10-2797-5 (paperback)

ISBN 952-10-2798-3 (PDF)

Edita Prima Oy

Vantaa 2005

Models as Epistemic Artefacts:

Toward a Non-Representationalist Account of

Scientific Representation

Tarja Knuuttila

Abstract

This study seeks to situate the philosophical discussion on models

and scientific representation within the larger context of questioning

representation that is taking place in other fields, especially in science

and technology studies. It addresses four related questions: (i) What

kinds of different reactions there have been to the puzzle of

representation? (ii) From where do the seeming epistemological

difficulties concerning representation stem? (iii) How can

representation be approached in a non-representationalist way? (iv)

What kinds of things are models, and how do they give us

knowledge?

A new artefactual approach to models is advanced that loosens the

epistemic value of models from representation and ascribes it instead

to their materially embodied constraints and interactive enablings.

The thesis draws four additional major conclusions: (1) Our

understanding of modelling should not be reduced to models

representing some external target systems. Apart from being

representative things models are typically also productive things

whose workability and experimentability is crucial for their epistemic

value. (2) Representation should be approached both from the use and

production points of view. (3) From the use point of view

representation appears as a two-fold phenomenon that is based both

on the medium-specific affordances of the material sign-vehicle and

on the intentional process of relating the sign-vehicle to the

represented. (4) From the production point of view a major portion of

the work of representation that is taking place in sciences

concentrates on what is already represented and modelled somehow.

Looking at representation from this angle stresses the methods,

ingredients and various representative devices that are needed in

producing models.

The study consists of a contextualising introductory essay and six

original research papers. The first two articles deal with more general

issues concerning representation. The next four articles study

representation in the context of modelling. Common to all of them is

the idea that models can be seen as epistemic artefacts. The articles

refer to this idea in discussing the interrelated questions of

representation, modelling, and cognition.

Contents

Preface ...................................................................................................... 7

List of original publications ....................................................... 10

Part 1. Summary

1. Introduction ........................................................................................ 12

1.1 Background ................................................................................... 12

1.2 Aims and plan .............................................................................. 16

1.3 A note on the method ................................................................... 18

2. Representation and its discontents .................................................. 21

2.1 The concept of representation ..................................................... 21

2.2 Representationalism .................................................................... 2 3

2.3 Against representation?............................................................... 27

Renouncing representation.............................................................. 27

Deconstructing representation ........................................................ 29

Reconstructing representation ......................................................... 31

3. Scientific models in the philosophy of science ............................ 37

3.1 Syntactic and semantic views on models .................................. 37

3.2 A practice-oriented approach to models ................................... 40

3.3 Models as representations........................................................... 42

3.4 Models as epistemic artefacts ..................................................... 48

4. An overview of the original articles ................................................. 50

5. Conclusions .......................................................................................... 68

Bibliography ............................................................................................ 71

Part 2. Original articles

Preface

My fascination with the question of representation has been the red

thread running through my travels in different disciplines, and it has

finally led me to the completion of this doctoral dissertation in

philosophy. While taking my first Master’s degree in economics, I

started to wonder how seemingly very austere and unrealistic

economic theories and models are able give us knowledge about our

complex economic life, what kind of knowledge that is, and,

ultimately, what science is all about. In the philosophy courses given

in the Helsinki School of Economics I came to understand that these

problems were philosophical in nature. I wish to express my gratitude

to Professor Uskali Mäki for this insight, for his teaching and for the

scholarly example he has set over the years.

I probably would never have started to work on this doctoral thesis

had I not studied semiotics at the end of 1990’s. The circle of

semioticians that surrounded Professor Eero Tarasti at the University

of Helsinki was international, liberal and yet academically ambitious,

and this spirit can, I think, be attributed directly to Eero Tarasti

himself. Over the years I have participated in various projects and

events under his leadership, and I am grateful for his considerate

guidance and assistance.

In the Center for Activity Theory and Developmental Work

Research I found the same kind of multidisciplinary and active milieu

that I had experienced in semiotics. I was fortunate to be a doctoral

student in the Center during the years when it was among those units

at the University of Helsinki that had been nominated by the Academy

of Finland as Centers of Excellence. Many foreign guest lecturers and

research fellows visited the centre and Professor Yrjö Engeström led

all of this activity in a very convincing and expansive manner. I wish

to thank all the personnel of the Center for Activity Theory and

Developmental Work Research, especially Ritva Engeström, Jaakko

Virkkunen, Leena Harjula-Jalonen and Heli Kaatrakoski.

I have been blessed with three supervisors, who all have

contributed to this dissertation in different ways. The long and

8Tarja Knuuttila

enthusiastic discussions I have had with Professor Reijo Miettinen

about the importance of artefacts have obviously had a great effect

on how I conceive of models. Moreover, my participation in the

remarkable research group led by Professor Miettinen has taught me

that science is above all a collaborative and collective effort.

Professor Ilkka Niiniluoto supervised my thesis before becoming

Rector of the University of Helsinki. I am grateful for his help and

encouragement, above all for his open-minded attitude to

philosophy. Professor Matti Sintonen has guided me through the

difficult (and admittedly nervewracking) phase of finishing this

thesis. He has been supportive and always on hand to answer my

questions. Moreover, I owe him a lot for his insights into the history

of philosophy.

Professor Fred Karlsson, Professor Timo Honkela and Docent Atro

Voutilainen have helped me substantially with the case studies on

language technology and neural network modelling. In addition, both

Honkela and Voutilainen co-authored one of the articles I am

submitting as a part of this thesis. Erika Mattila has been my helpful

partner in our common endeavour to understand modelling better,

loyal both in good and bad days—and always ready to work even

harder.

My special thanks go to the following colleagues and friends with

whom I have collaborated in recent years and from whose advice

and generosity I have benefited: Kristian Bankov, Marcel Boumans,

Sampsa Hyysalo, Hanna Johansson, Timo Kaitaro, Marja-Liisa

Kakkuri-Knuuttila, Jonna Kangasoja, Sakari Katajamäki, Hannele

Kerosuo, Janne Lehenkari, Aki Petteri Lehtinen, Juha Leminen,

Johannes Lenhard, Andrea Loettgers, Endla Lõhkivi, Martina Merz,

Sami Pihlström, Veikko Rantala, Kristina Rolin, Max Ryynänen, Jussi

Silvonen, Juha Tuunainen, Marja Väätäinen and Petri Ylikoski. I also

want to thank Henry Fullenwider and Marjatta Zenkowicz warmly for

English-language revision of some of the manuscripts, and Tinde

Päivärinta for the layout of this book.

I am grateful to Professor Mary S. Morgan and Professor Mauricio

Suárez, whose work I greatly appreciate, for agreeing to pre-examine

my thesis and comment on it.

Scholarships from the Finnish Cultural Foundation and the

Research Funds of the University of Helsinki made it possible for me to

finish this thesis. I have received travel grants from the Chancellor of

the University of Helsinki, the Finnish Konkordia Fund and the

Philosophy of Science Association (NSF Travel Grant).

Finally, it is ultimately people who make academic life a

worthwhile endeavour. More often than not, colleagues become

friends and sometimes they become more than friends. I am so happy

that I have been able to share so many things with Susanna Välimäki

and Harri Veivo. What funny, witty and caring companions you have

been.

As for family and friends, I wish to thank one and all (some of

whom have already been mentioned above). And I am ever grateful

to my parents Raili and Petteri Knuuttila, my husband Panu

Savolainen, my nephew Jan, my daughter Laura and son Sauli for all

their love and care!

I dedicate this book to my beloved sister Petra Anneli (1962-1999),

who would have loved to see me making it.

Helsinki, October 2005

Tarja Knuuttila

Preface

10 Tarja Knuuttila

List of original publications

1) Knuuttila, Tarja (2003), “Is Representation Really in Crisis?”,

Semiotica 143: 95-111.

2) Knuuttila, Tarja (2002), “Signing for Reflexivity:

Constructionist Rhetorics and Its Reflexive Critique in Science

and Technology Studies”, Forum Qualitative Sozialforschung /

Forum: Qualitative Social Research, [On-line Journal], 3(3).

Available at: http://www.qualitative-research.net/fqs-texte/

3-02/3-02knuuttila-e.htm (52 paragraphs).

3) Knuuttila, Tarja and Atro Voutilainen (2003), “A Parser as an

Epistemic Artifact: A Material View on Models”, Philosophy of

Science 70 (Proceedings): 1484–1495.

4) Knuuttila, Tarja (in press), “Models, Representation, and

Mediation”, Philosophy of Science 72 (Proceedings), 2005.

5) Knuuttila, Tarja (in press), “From Representation to Production:

Parsers and Parsing in Language Technology”, in Johannes

Lenhard, Günther Küppers and Terry Shinn (eds.), Simulation:

Pragmatic Constructions of Reality. Sociology of the Sciences

Yearbook. New York: Springer, 2006.

6) Knuuttila, Tarja and Timo Honkela (in press), “Questioning

External and Internal Representation: The Case of Scientific

Models”, in Lorenzo Magnani (ed.), Computing, Philosophy,

and Cognition. London: King’s College Publishing, 2005.

Part 1. Summary

12 Tarja Knuuttila

1. Introduction

1.1 Background

If there is any theme that unites the heterogeneous postmodern

discussions in the fields of philosophy, humanities and cultural

theory, then representation is certainly a good candidate. Different

“postist“ movements such as poststructuralism, postcolonial theory

and certain currents of feminism have questioned representation in

several ways. The main thrust of these critiques has been that our

cultural representations are not to be trusted since there is no way for

us to ascertain whether they (re)present their objects—or reality—

truthfully. Moreover, this scepticism has concerned even scientific

representations which especially in the field of science and

technology studies have been “unmasked“ as more or less contingent,

and thus questionable, products of their times. The outcome of the

recent discussion has been that there is something wrong with our

received notion of representation, which conceives of knowledge as

accurate representation of the independently existing world. In this

sense the crisis of representation is not a new phenomenon, but can be

dated back at least to the beginning of the 20th century, where it can

be found for instance in abstract art in general, dadaism and cubism.

When it comes to science, already both John Dewey and Martin

Heidegger criticised the idea of knowledge as that of spectating the

world as a picture,1 a theme that was picked up by Richard Rorty in

his seminal and controversial Philosophy and the Mirror of Nature

(1980). This book can be regarded as a successful manoeuvre in

bringing the notion of representation to the centre of the debate in

analytical philosophy as well.

Neither was representation of central interest in the philosophy of

science before the 1980’s. 2 The term representation was not often used,

and when it was, it was neither thematised nor questioned. In the

1980’s the situation started to change largely due to the semantic

approach to models. As the semantic approach loosened itself from

the linguistic paradigm of the received view and began to conceive of

theories as extra-linguistic entities, as families of (theoretical) models,

1 Cf. Dewey’s critique of the “spectator theory of knowledge” in Dewey

(1929), and Heidegger’s famous essay “The Age of the World Picture” in

Heidegger (1977).

the question then became how these entities were linked to the world.

Unlike with propositions and sentences, such terms as “true” and

“false” did not seem to be apt in dealing with the relationship

between models and their target systems. “Representation” was more

appropriate.

This turn away from truth to representation also implied for many

a definite change in how science was perceived. As Woodward has

noted: “The notion of [adequate] representation is a more general idea

than the notion of a statement’s being ‘true’, with representation

having to do with a qualitative notion of ‘fit’ between a model and

world—a notion that admits of degrees” (2002, 380).3 For some, the

notion of representation has even served as a way to circumvent the

question of realism altogether (see e.g. Frigg 2003, 12).

Now, twenty years later, a lively discussion concerning scientific

representation is in full sway but it is largely still conducted in

relation to scientific models and more recently, simulations (e.g.

Winsberg 1999). This is actually quite remarkable. It suggests, among

other things, how internalistic4 this discussion has been. Indeed,

Callender and Cohen have recently claimed that the specific problem

2 Of course there were notable exceptions among the analytical

philosophers, such as Sellars (1968) and Rosenberg (1974). However, it was

typical for the so-called linguistic turn of the analytical philosophy to use

such terms as meaning, sentence and proposition, rather than

representation (see Rorty [ed.] 1992). Nevertheless, it can be claimed, as

Rorty (1980) in fact does, that in the background of this linguistically

oriented philosophy there still loomed the old problem of representation,

which motivated both the empiricists and idealists in their battle against

scepticism. See Popkin (1980) on the constitutive role of the problem of

scepticism in Western philosophical thought.

3 Pace Woodward, the notion of truth can also be made to admit of degrees:

sentences or statements can be classified according to their closeness to

truth, that is according to their degree of truthlikeness or verisimilitude (see

e.g. Niiniluoto 1999).

4 By “internalistic” I do not refer to the internalism/externalism debate in

epistemology (or in the philosophy of mind) but to the discussion in the

sociology of scientific knowledge on whether or not science should be

approached as a conceptual and rational activity only. To the extent that

philosophers have tended to take this view on science, it has led them to be

internalistic also in the sense of rather staying inside their own discipline.

The relatively recent “return” to naturalism has changed this attitude quite

a bit (see the section 1.3).

Introduction

14 Tarja Knuuttila

of scientific representation is a non-problem and that the discussion

of scientific representation has neglected “the philosophical work on

representation in general” (2005, 2). I think that there is a grain of truth

in their accusation even though it misconstrues much of the work

done in the burgeoning field of scientific representation. For one thing,

the philosophical writers on scientific representation have (pace

Callender and Cohen) considered the question of scientific

representation in a larger framework: for instance several authors

have related their discussion of representation in science to

representation in art (e.g. Suárez 1999, French 2003, Frigg 2003).

Ronald Giere’s work on scientific representation has drawn resources

from cognitive science throughout the years.

Having admitted this, it nevertheless seems to me that the present

discourse on scientific representation has remained a rather solitary

enterprise. It has been first and foremost interested in how (and by

virtue of what) models represent reality. That science is a hugely

complex and historically layered artefactual and representative

enterprise has been largely ignored in this discussion, which has

mainly been focused on ready-made models isolated from the

practices of their production.

Another peculiar character of the philosophical discussion of

scientific representation, also due to its internalistic character, is the

way it has succeeded in remaining nearly totally untouched by the

critical discussions concerning the notion of representation in the

other fields of inquiry. The discussants have agreed that models are

representative entities—otherwise, it has been supposed, they cannot

give us knowledge—even though no common understanding of what

representation involves has emerged. To be sure, already in 1983 Ian

Hacking in his Representing and Intervening proposed shifting the

focus of the philosophy of science from representing to intervening.

This was an interesting move indeed—and far ahead of its time—

taking into account that philosophers of science did not generally

understand scientific endeavour in terms of representation in those

days.

By the time Hacking was writing the turn to intervening was

something that had already taken place in science and technology

studies (STS), where the so-called laboratory studies aiming at

accounting for how scientific facts were produced in scientific work

were accumulating (Latour and Woolgar [1979]1986, Knorr Cetina

1981, Lynch 1985a). But the question of representation kept on coming

back. It refused to be repressed—if only because the constructivists

presented their laboratory stories as descriptions of what “actually”

took place in scientific “practice”. This led not only to discussions of

the problem of reflexivity (Woolgar [ed.] 1988) but also to some

insightful studies on how representations are constructed with the

help of diverse means and procedures (Lynch and Woolgar 1990),

how they function as “working places” (Amann and Knorr Cetina

1990) and as “immutable mobiles” that “draw together” things and

diverse activities (Latour 1990).

Another source from which the philosophical work on scientific

representation could have taken nourishment, but in fact has not done

so (with such notable exceptions as Ronald Giere and Paul Thagard)

is cognitive science and the philosophy of mind. Especially in

cognitive science some fundamental representationalist assumptions

concerning the interrelationship between cognition and

representation have been called into question by researchers studying

the importance of environment and artefacts for what can be called

“embodied, situated and distributed cognition” (Clark 1999; see also

Varela et al. 1991, Hutchins 1995, Clark 1997). These studies have in

part contributed to the recent discussion of the notion of mental

representation, where different standpoints vis-à-vis representation

have been taken, ranging from adopting less metaphysically

impregnated words and expressions such as “tools for thinking”

instead of “representation “ (Dennett 2000) to arguing for a need to

“rehabilitate representation” (Smith in Clapin [ed.] 2002).

An interesting feature of the above-mentioned discussions in the

field of STS and cognitive science is that, irrespective of their

scepticism concerning our representationalist heritage, they have

actually resulted in fresh approaches to representation—leading also

to radical reconstructions of what should count as knowledge and

cognition. Nothing like that, I claim, has yet happened in the

philosophy of science. Even so, I think that at least two features of the

discussion of scientific representation should make this discussion

rewarding also from a more general point of view. Firstly, the recent

work on scientific representation has focused on specifying and

evaluating the relative merits of different dyadic and triadic accounts

of representation (e.g. Giere 2004, Suárez 2003 and 2004, Frigg 2002

and 2003, Bailer-Jones 2003). The relevance of this kind of theoretical

work is not limited to scientific representation only. Secondly,

philosophers are now seriously interested in studying the functioning

Introduction

16 Tarja Knuuttila

of specific models in scientific practice. The volume Models as

Mediators, edited by Mary S. Morgan and Margaret Morrison (1999),

can be seen as an epitome of this kind of work. In the introductory

articles of that book they lay the basis for a research programme for

studying models from the point of view of scientific practice

(Morrison and Morgan 1999a, 1999b). Morrison and Morgan’s

approach to models as mediating instruments provides a potential

bridge between philosophical theorising and the more practice-

oriented approach of STS.

The almost non-existent dialogue between the aforementioned

different discussions of representation in general and scientific

representation in particular set the double agenda of this thesis: On

the one hand I situate the philosophical discussion of scientific

representation in the larger context of questioning representation that

has taken place in other fields, especially in STS. On the other hand I

take part in the discussion of models and representation in the

philosophy of science. The red thread that ties these interests together

is the material and artefactual approach to representation that I am

both developing and arguing for in this dissertation. What is special

about this approach is that it gives a non-representationalist account

of scientific representation.

1.2 Aims and plan

As already hinted by the double agenda adopted, the aims of this

study range from the more general to the more specific. At the most

general level, the goal of this study is to investigate the philosophical

or, more exactly, the epistemological problem of representation that

seems to underlie the recent critiques of representation. Thus, I first

study the various different reactions to the puzzle of representation.

Secondly, on this basis I attempt to diagnose the causes of the seeming

epistemological difficulties concerning representation. The hypothesis

guiding this study is that the so-called problem of representation: i.e.

“how is it possible for one thing to represent something else?” (Crane

1995, 9), is due to our representationalist heritage and that

representation need not be understood in a representationalist way.

This leads me, thirdly, to set as my next goal the developing of a non-

representationalist approach to scientific representation. Since the

discussion of scientific representation has so far taken place in the

context of modelling, my aim of developing an alternative approach to

scientific representation entails, fourthly, answering the question of

what kinds of things scientific models are and how they give us

knowledge.

The underlying assumption of this study is that scientific

representation is a very good place to study the puzzles of

representation and representationalism. This is due to science being

perhaps the one human activity that is most critically dependent on

the representationalist notion of representation. We are accustomed to

thinking that our scientific theories and models refer to an

independently existing reality outside of them and that they can at

best be considered as truthful, or accurate, descriptions of it. On the

other hand, however, sciences typically study unobservable entities

with the most sophisticated investigative machinery created by

humans so far, which makes the question of scientific representation

especially challenging. Last but not least, to inquire into

representation is to inquire into the nature of knowledge as well. The

epistemic value of models has traditionally been attributed to their

representative dimension. Thus studying how scientific models give

us knowledge—and what this knowledge is like—helps us to

understand more generally in which ways representation, knowledge

and, ultimately, cognition are intertwined.

That this dissertation consists of individual articles has some

consequences for how its aims are tackled. Since articles typically

focus on relatively narrow questions, part of the background of these

more specific topics is provided by the present summary (Part 1).

Hence to contextualise the individual articles and to give them a

common raison d’être, I discuss first what is meant by the notions of

representation and representationalism and how these concepts are

related to one another. Then I take up the phenomenon of the crisis of

representation from the point of view of scientific representation.5 I

study the diverse ways in which certain recent authors have sought to

settle the problem of representation and ask whether or not we should

renounce the concept of representation altogether or rather strive to

interpret it in a different way. As I do not think that it is possible—or

5 Despite the institutional differences and different goals of art and science,

the question of representation provides a common point of view from

which the specific features of art and science can be fruitfully compared

and examined (see e.g. Baigrie, ed. 1996 and Jones and Galison, eds. 1998).

Introduction

18 Tarja Knuuttila

even desirable—to renounce or deconstruct the notion of

representation entirely, my discussion of models is an attempt to

show how the problem of representation could be dealt with in a

positive way—yet taking into account the recent critique of

representationalism.

I suggest that in trying to approach representation in a fresh way

one should resist the traditional temptation to ground the

representative power of actual representative artefacts in primary

immaterial and ideal representations (e.g. abstract structures, “mental

models” or concepts). Instead, the actual processes of scientific

representing should be analysed from the epistemic point of view. This

means focusing on the production and use of materially embodied

representations. Along these lines I approach models, which have

generally been regarded as representations, and advance an

alternative conception of models as epistemic artefacts.

The main points of this thesis can be summarised as follows: i)

models are human-made artefacts which are used to interact with the

world rather than merely to represent it; ii) thus instead of being

abstract theoretical constructions they are better conceived of as

entities that are materialised in some media; iii) the epistemic value of

models accrues importantly from their material dimension, which

explains why models have many other epistemic functions besides

that of representing the world; iv) the representational function of

models should not be approached in “representationalist” terms; v)

representation is best understood as activity that relies both on the

medium-specific affordances of the material sign-vehicle and the

intentional process of relating the sign-vehicle to its object.6

1.3 A note on the method

Being careful examiners of other scientists’ methods and

presuppositions, philosophers of science were remarkably silent on

their own method until recently when the discussions of naturalism

(see e.g. Giere 1988 and 1999; Kitcher 1992, Downes 1993) and the

disunity of science (Dupré 1993, Galison and Stump 1996) swept over

the field. As to the discussion of naturalism Philip Kitcher (1992)

argues that philosophy of science is slowly (re)turning to the

6 I am grateful to Mauricio Suárez in helping me to explicate the main

points of my thesis.

naturalist epistemology. It is based on rejecting either one or both

“Post-Fregean” assumptions of how to pursue epistemology.

According to them, epistemology should be both an apsychological and

an a priori investigation—“knowledge is to be given a ‘logical

analysis’” (57). These assumptions were constitutive for analytical

philosophy for decades. Accordingly, “for at least a period,

philosophers could be confident of their professional standing,

priding themselves of a method—the method of conceptual analysis—

which they, and they alone, were trained to use“ (54).

On the level of doing philosophical research, the naturalist

epistemology means that we should take seriously the results of

scientific research. According to Giere “any conclusions one reaches

about the nature of science are subject to criticism based on theoretical,

historical, psychological, or social investigations into particular

scientific practices” (1999, 5; see also Giere 1988, 8-10). Thus as a

result of adopting the naturalist epistemology my work is also

multidisciplinary. In tackling the problem of representation I have

drawn resources from semiotics, STS, activity theory (see Engeström

and Escalante 1995, Engeström et al. 1999, Miettinen 2001) and

distributed cognition. What is common to these approaches is that

they, in one way or another, concentrate on mediation provided by

signs or tools in explaining human activity and cognition.

Furthermore, several of the articles of this study participate also in the

philosophically inclined discussions in the aforementioned fields.

Last but not least, my approach to the problem of representation is

uncompromisingly naturalist in the sense that I do not want to posit

any fundamental representations behind those things that we actually

use in scientific practices in order to represent.

Provided that we accept the results of empirical science as part of

philosophical reasoning, should we then stop at that? Is there a place

for empirical study in philosophical argumentation? I think that there

is, if only because a lot of research done in the philosophy of science

proceeds by presenting cases from specific disciplines, taking

historical data into account as well. Since I approach representation

and modelling from the point of view of scientific practice, I have felt

a need to get some grasp of the practices themselves. Thus in one of

the studies concerning modelling (“From Representation to

Production: Parsers and Parsing in Language Technology”) I present

a case of modelling in language technology in which I use interviews

of the researchers working in the field. This is partly because research

Introduction

20 Tarja Knuuttila

on the procedures and phases of modelling is largely non-existent,

and knowledge of it remains largely at the tacit participant-level.

My empirical data consists of 24 transcribed semi-structured

interviews that I conducted in two phases between the years 2000 and

2002 and in spring 2004 with researchers and developers of language

technology who have either been doing language technological

research in the Research Unit for Multilingual Language Technology

in the Department of General Linguistics in University of Helsinki, or

have been otherwise affiliated to the group. The key researchers and

developers were interviewed more than once for a relatively long

period (from 1 ½ hours to 3 hours). The written material on which the

case study is based consists of publications of the researchers

interviewed, other literature on computational linguistics and

language technology, and some reports and documents concerning

the Research Unit for Multilingual Language Technology and

language technology in Finland in general. I have also benefited from

casual discussions with the language technologists, attended some

courses on language technology and taken part in language

technological events and activities. Moreover, I have been observing a

language-technological project funded by National Technological

Agency of Finland (TEKES), in which researchers from the Department

of General Linguistics have participated. Some of the researchers

interviewed also commented on the earlier drafts of my papers on

language technology, and Study 3 “A Parser as an Epistemic Artefact:

A Material View on Models” was co-authored by Atro Voutilainen, a

member of that team.7

As for the claims of the disunity of science, it is already widely

acknowledged that physics may not provide an appropriate model for

approaching other sciences. Yet, in discussions of modelling the

theoretical models of physics are typically taken as representatives of

models in general. In this study I have instead used models from the

fields of computational linguistics and artificial intelligence as

examples. One of the purposes for choosing them has been to show the

limitations of the traditional notion of models as representations of

their target systems. As the traditional notion fits inadequately these

models, I wish to articulate an approach to models that would suit

them better. I do not claim that the computational models I have

chosen can serve as representatives of models in general—if only

because no model can. Nevertheless, the importance of computational

models and simulations in science is constantly increasing and in fact

creating new fields of inquiry. On the other hand, I would like to

suggest that the notion of models as epistemic artefacts is useful as a

general approach to models, as a way of viewing them from another

angle than has been customary.

2. Representation and its discontents

2.1 The concept of representation

The word representation comes from Latin raepresentare “to make

present or manifest or to present again” (Pitkin 1967, 241). It was

almost exclusively applied to inanimate objects, the political idea of

human beings representing each other appeared only after the

fourteenth century (ibid.). In her etymological study of the concept of

representation Pitkin describes the meaning of raepresentare in the

following way:

It can mean to make them [inanimate objects] literally present, bring

them into someone’s presence, accordingly it also comes to mean

appearing in court in answer to summons, literally making oneself

present. It can also mean the making present of an abstraction through

or in an object, as when a virtue seems embodied in the image of a

certain face. And it can mean the substitution of one object for another,

instead of the other (Pitkin 1967, 240).

The modern usage of representation developed from the latter

meaning of the aforementioned quotation (Volli 2003).8 Thus, for

instance, Prendergast (2000) discriminates between two basic

meanings of the term: between the older “re-presentation” and the

7 It appears to me that since scientific inquiry is nowadays so specialised

and heterogeneous, the philosophers and other researchers who are

studying science should work collaboratively, or at least in constant

dialogue, with the scientists whose work and discipline they are examining

(unless they themselves have some experience of the field of inquiry in

question). The ethnographical approach to scientific work, once so popular

among STS researchers, was successful in making scientific work and its

material dimension visible. However, I do not think that “anthropological

observation” per se could help us get any more than a superficial

understanding of the content and methods of different disciplines.

Introduction—Representation and its Discontents

22 Tarja Knuuttila

more recent “standing for”. Instead of striving to produce the illusion

of presence, to re-present, the representative relation of standing for is

that of substitution, of substituting something absent with something

present. The substitution can take the form of simulacrum, but it is a

form of representation as making present (in the older sense of

representation) only if it produces an illusion of presence by virtue of

being an accurate replica of the real thing.

As distinguished from “re-presentation”, representation as

“standing for” is not to be confused with the thing itself. Pitkin notes

how representation as “standing for” seems to require a certain

distance or difference as well as resemblance and correspondence

(1967, 68). Representation as “standing for” is typically approached

through the metaphors of portrait, map or mirror: what they have in

common is that they are all renderings of an “original” in a medium

different from it. Thus the function of representation as “standing for”

is to bring knowledge: it “consists of the presence of something from

which we can draw accurate conclusions about the represented,

gather information about the represented because it is in relevant

ways like the represented” (Pitkin 1967, 81). When applied to political

sphere this idea of representation provided a justification for

representative democracy. The substituting representatives for the

whole people were like a copy, a second-best approximation of direct

democracy, which would have been the ideal system according to the

Anglo-American democratic ideology (ibid., 84).

As for my focus on the epistemic value of models, I find Pitkin’s

evaluation of representation as “standing for” in the political realm

insightful: “…[this] view of representation … does not allow for an

activity of representing. … It has no room for any kind of representing

as acting for, or on behalf of, others; which means that in the political

realm it has no room for the creative activities of the representative

legislature, the forging of consensus, the formulating a policy” (90). In

fact, I am going to claim in this thesis that treating models as

8 There have been, of course, many other conceptions of representation,

but representation as “standing for” seems to be the most common and

prevailing one (see e.g. Peirce CP 2.273; Palmer 1978, 262; Crimmins 1991,

791). Even though typical for the modern period, it originates from the

scholastic aliquid stat pro aliquo. However, Nöth (1995) claims that medieval

philosophers used more often another formulation, namely supponit aliquid

pro aliquo, which means “something serves in place of something else” (84).

predominantly representative entities—as surrogates that stand for—

ignores their material and interactive side, from which their heuristic,

mediating and many other epistemic capabilities arise.

2.2 Representationalism

Representation as “standing for“ seems to be embedded in

representationalism. According to representationalism, the sensing and

knowing mind cannot have direct acquaintance with its objects. It can

approach them only through ideas, which are assumed to represent

them. Thus knowledge is conceived of as an assemblage of

representations that reproduce accurately, i.e. stand truthfully for,

what is outside the mind (or, after the “linguistic turn”, outside

linguistic description—or other external representations) (see e.g.

Rorty 1980, 3-6; Gutting 2001, 336). The crucial difficulty of

representationalist theory is that the mind “supposes” that its ideas

represent something else but it has no access to this something else

except via another idea.

The conception of a mind as container of ideas is most commonly

associated with Locke. He was criticised already by other empiricists,

but he nonetheless succeeded in articulating the way the early modern

age thought about perception and knowledge. In his Les mots et les

choses (1966) Michel Foucault claims that this age, the “Classical Age”

as he calls it, was that of representation par excellence. It strove for a

universal method of analysis that would perfectly order

representations and signs to mirror the real orderings. Language

coincided with thought, it was the transparent system of signs that

represented the representation, that is, the ideas. Moreover, it was

assumed that language by its very nature made successful

representation possible, which led Foucault to characterise “classical

language” as “the common discourse of representation and things”

(1970, 311). Thus the Classical age relied on the ability of language to

represent the world as it is, but as a consequence man as representer

was left out of the “picture”. This is what Foucault aims to show with

his lengthy analysis of Velásquez’s painting Las Meninas, to which the

first chapter of Les mots et les choses (1966) is dedicated. Foucault takes

Las Meninas to be a perfect image of Classical representation, which

makes the different aspects of representation visible, yet leaving them

dispersed because there is no “unifying” subject. The mirror behind

the painter shows what he sees and what he is in the process of

Representation and its Discontents

24 Tarja Knuuttila

depicting on his canvas, the ruling couple Philip IV of Spain and his

wife Mariana. Yet neither the painting itself nor the act of painting are

shown in Las Meninas: the painter is standing back from his work; if he

had been in the process of painting, he would have disappeared

behind the canvas. Moreover, as spectators, we realize that the royal

couple is in fact standing in our place—everything else is depicted

except the subject of representation and the act of representing.

As the Modern age no longer treated discourse as a perfectible and

transparent medium, the representational capacity of man became

available as a distinct object of knowledge. Foucault remarks how

Kant and the age that followed him did not complain about man’s

limited capacity to know how things are. They rather turned it into an

advantage, a condition of all factual, empirical knowledge.

Epistemology, as an attempt to explain and justify how things in

general can be given to representation, was born. Foucault writes:

The Kantian critique…questions representation, not in accordance with

the endless movement that proceeds from the simple element to its

possible combinations, but on the basis of its rightful limits. Thus it

sanctions for the first time that event in the European culture which

coincides with the end of eighteenth century: the withdrawal of

knowledge and thought outside the sphere of representation. That

space is brought into question in its foundation, its origin, and its

limits: and by this very fact, the unlimited field of representation,

which Classical thought had established…now appears as a

metaphysics (Foucault 1970, 242).

Interestingly, whereas for Foucault Kant broke away from the

representationalist paradigm, in the alternative philosophical story of

representationalism provided by Richard Rorty, Kant more or less

perfected it and thus laid down the lines for the representationalist

tradition of (analytical) philosophy to come.9 In his Philosophy and the

Mirror of Nature (1980) Rorty claims that two assumptions have

dominated the representationalist tradition of Western philosophy.

One is the Kantian, according to which human knowledge should be

understood as a special relation between the objective knowledge

substrate offered by the world and the active cognitive abilities of the

subject. The other assumption is the platonic belief that there is a way

to portray things that can reach them as they are. However, also for

Rorty the representationalist tradition has roots in the beginning of the

modern age. Rorty sees representationalism as a reaction to the

emergence of the new natural sciences, which led to the relocation of

the intentional and phenomenological in the realm of the mental. Thus

philosophy turned to inspect the ideas in the mind. The rationalists

and the empiricists alike tried to establish a secure foundation for

knowledge, and that foundation was to be found from inside of the

mind. The earlier distinction between appearance and reality was

replaced by that between inner and outer and the question became

“How can I escape the veil of ideas?” (1980, 160). Kant provided this

an elegant answer, according to Rorty, by changing the empiricist

question of psychophysiological mechanisms into a discussion of the

legitimacy of science itself (1982, 145). He took up an unresolved

scientific problem—the relation of sensations to their objects—and

turned it into a question about the possibility of knowledge, which

question was to be resolved in the sphere of representation. Thus

Rorty holds Kant responsible for the foundational pretensions of

philosophy: “the Kantian picture of concepts and intuitions getting

together to produce knowledge is needed to give sense to the idea of

‘theory of knowledge’ as a special philosophical discipline” (1980,

168).

It is important to bear in mind that Rorty’s anti-

representationalism is not only an attack against the notion of

representation as “mirroring”, corresponding or resembling but even

more importantly against what he calls “privileged representations”

9 Rorty seems not to pay enough attention to the fact that for Kant the

activity of thinking is not mimetic but constructive (Rusterholz 2003, 53).

Kant can be considered one of the founding fathers of constructivism. As

Matti Sintonen (1995, 1996) has argued, the gist of Kant’s transcendental

method and of the entire “Copernican Revolution” was in acknowledging

the active contribution of the mind. The transcendental method in

epistemology requires not just that one examines the objects of putative

knowledge but also that one focuses on the conceptual tools used in

knowledge acquisition as well as on what one must do to obtain

knowledge. Nor does this constructivism confine to the representation of

the external world. Jaakko Hintikka (1973, 1974) has maintained that there

is a close relationship between Kant’s transcendentalism and his theories of

space, time, and mathematics. On these themes, see Sintonen (2005,

forthcoming). Also Sismondo (1996) and Hacking (1999) consider Kant to

be the forefather of constructivism, Sismondo even dubs the whole STS

constructivism the “Neo-Kantian science”.

Representation and its Discontents

26 Tarja Knuuttila

and their privileging of philosophy.10 This clearly emerges from the

following short resume of his antirepresentationalist story:

To describe this development as a linear sequence is of course

simplistic, but perhaps it helps to think of the original dominating

metaphor as being that of having our beliefs determined by being

brought face to face with the object of belief (the geometrical figure

which proves the theorem, for example). The next stage is to think that

to understand how to know better is to understand how to improve the

quasi-visual faculty, the Mirror of Nature, and thus to think of

knowledge as an assemblage of accurate representations. Then comes

the idea that the way to have accurate representations is to find, within

the Mirror, a special privileged class of representations so compelling

that their accuracy cannot be doubted. The privileged representations

will be the foundations of knowledge… Philosophy as epistemology

will be the search for the immutable structures within which

knowledge, life and culture must be contained—structures set by the

privileged representations, which it studies. (Rorty 1980, 163).

Rorty’s reconstruction of the history of Western philosophy is not only

provocative but also revealing. It is indeed not difficult to find

privileged representations in which philosophers have sought to

ground their endeavour: ideas, concepts, logical forms, Husserlian

“essences”… and structures, which have featured importantly in the

discussions of models and representation.11

10 According to Rorty, the turn to language did not entail any notable

change for the representationalist tradition of philosophy, since analytical

philosophy attempted to formulate many traditional epistemological

problems by linguistic means. In Why Does Language Matter to Philosophy?

(1975) Hacking expressed a similar view. He calls the early modern age the

“heyday of ideas”, whereas he considers himself to be writing in the

“heyday of sentences”. Hacking notes how language was not an interesting

problem during the heyday of ideas, which was instead interested in

“mental discourse”. Hacking nevertheless claims that “the structure of the

recent philosophical problem situation... is formally identical to the

seventeenth century one, but the content of that structure is different”

(1975, 167). The problem of the “interface between the knower and the

known” has remained much the same, but public discourse has replaced

mental discourse and sentences have replaced ideas.

2.3 Against representation?

The remarkable thing about the “postmodern” discussions of

representation and representationalism is that they have been

conducted nearly exclusively in negative terms. The concept of

representation has been found lacking both in theory and practice.

Theoretically, it seems that our Kantian heritage has left us captives of

the sphere of representation. Either representation cannot reach the

things in themselves, providing only a deficient substitute for them, or

then it creates an effect of reality that it strives to capture, but in vain

(because there is nothing to capture—according to the most adamant

poststructuralists). Hence it is hardly astonishing that the question of

representation has been a subject of constant epistemological concern

and even horror (an expression by Steve Woolgar). Moreover, at a

practical level, given the diversity of the representations we use and

the complexity of our practices of representation, it seems clear that the

general concept of representation as “standing for“ does not help us

much in explaining what kinds of things representations are and how

they are supposed to represent.

In this situation many have felt that something needs to be done—

but what? At least three different positions vis-à-vis the problematics

of representation have been taken. Some wish to renounce

representation and simply evade the problem as unproductive and

unfruitful. Then, instead of putting the question of representation

aside, one can attempt to deconstruct the notion—to show that in

talking about representation we are actually talking about different

ways of rendering, referring to, denoting, indicating, etc. that do not

share any common core that entitles us to call them representations.

Finally, one can seek to reconstruct our notion of representation in

such a way that it pays due attention to the criticism.

Renouncing representation

In Philosophy and the Mirror of Nature Rorty (1980) concludes that it is

time to break with the received epistemological framework and to stop

11 On the other hand this predilection for privileged representations has

been typical of the cognitive sciences as well, where such hypothetical

entities such as concepts, symbolic structures, mental models, prototypes,

schemes, etc. have been ascribed to our minds to explain our cognitive

capabilities.

Representation and its Discontents

28 Tarja Knuuttila

thinking of knowledge in terms of representing accurately that what is

outside the mind and, subsequently, language. Actually, we should

stop thinking about language in terms of representation entirely:

We must get the visual, and in particular the mirroring, metaphors out

of our speech altogether. To do that we have to understand speech not

only as not the externalizing of inner representations, but as not a

representation at all. We have to drop the notion of correspondence for

sentences as well as for thoughts and see sentences as connected with

other sentences rather than with the world. We have to see the term

“corresponds to how the things are“ as an automatic compliment paid

to successful normal discourse rather than as a relation to be studied

and aspired throughout the rest of the discourse. (371-72, italics mine)

As noted above, Rorty is predominantly interested in targeting

philosophy as a discipline that takes upon itself the task of

legitimising the knowledge claims of the other areas of culture.

Without the notion of knowledge as accuracy of representation and

the consequent privileged representations, the claims that

“philosophy should consist of ‘conceptual analysis’ or ‘phenom-

enological analysis’ or ‘explication of meanings’ or examination of

‘the logic of our language’…would not have made sense” (1980, 12).

Rorty has actually been rather uninterested in science.12 However,

claims similar to his have been presented also in the context of

science. Ian Hacking and Andrew Pickering, among others, have

contested the centrality of representation for our notion of what

science is about. Hacking (1983) aims to turn from truth and

representation to experimentation and manipulation:

Realism and anti-realism scurry about, trying to latch on to something

in the nature of representation that will vanquish the other. There is

nothing there. That is why I turn from representing to intervening.

(145)

Pickering (1995), for his part, contrasts “representational and

performative idioms of thinking about science”:

12 Hacking notes, rightly I think, that “Rorty’s version of pragmatism is yet

another language-based philosophy, which regards all our life as a matter

of conversation” (1983, 63).

The representational idiom casts science as, above all, an activity that

seeks to represent nature, to produce knowledge that maps, mirrors,

or corresponds to how the world really is. In so doing, it precipitates a

characteristic set of fears about the adequacy of scientific representation

that constitute the familiar philosophical problematics of realism and

objectivity… (5)

…My suggestion is that we should see science (and of course,

technology) as a continuation and extension of this business of coping

with material agency. And, further, we should see machines as central to

how scientists do this. (7)

In the face of these claims I wonder whether it is desirable, or even

possible, to do without the notion of representation? Is renouncing

representation just a question of talking differently, and consequently

even thinking differently—using perhaps the proposed notions of

conversation (Rorty), intervention (Hacking) or machines (Pickering)

instead? But are not scientific intervening, testing and producing

effects, or “coping with the material agency“ activities involving

complex representative artefacts and skills? If so, then what could be

meant by the need to get rid of representation or to contrast it with an

intervening or a performative idiom? I think that this former question

is especially justified in the context of models, which occupy an

interesting middle ground between representation and experimen-

tation. What seems to motivate the aforementioned attempts to get rid

of the notion of representation for good is that continuing to use the

concept would eventually evoke the representationalist conception of

science. I do not see that this needs to be the case, as the various

attempts to reconstruct or rehabilitate representation show.

Deconstructing representation

Instead of evading the question of representation, scholars in the field

of science and technology studies have attempted to tackle it head-on.

Inspired by ethnomethodology they have gone into “the field” to

observe how scientists “actually” go about representing. Their studies

deconstruct scientific representation into complex processes making

use of various “documents“ or “inscriptions“. Representations

become things that are worked upon, being ultimately “rich

depositories of ‘social’ actions“ (Lynch and Woolgar 1990, 5). In

examining these “representative documents”, the studies in question

begin by inquiring: “What do the participants, in this case, treat as

Representation and its Discontents

30 Tarja Knuuttila

representation?” (ibid., 11), rather than asking what is meant by

representation.

What follow from this approach are studies that meticulously

follow the “assembly line”, the processes of constructing scientific

representations. From this point of view scientific representation

appears as a subtle “dialectic of gain and loss“ (Latour 1995). It is not

just a question of reduction or simplifying. Some methods of

representation further fragment, upgrade and define the specimen in

order to reveal its details, whereas others add visual features for the

purposes of clarifying, extending, identifying, etc. Often the aim of

scientific representation is to mould the scientific object so that it can

assume a mathematically analysable form or to be more easily

described and displayed using different textual devices (see e.g.

Latour 1990, Lynch 1985b and 1990). Scientific representation widens

in these studies into an expanded process of circulating and

arranging diverse extracts, “tissue cultures”, photographic traces,

diagrams, chart recordings, verbal accounts and so on into a serial

order. The epistemological problem concerning the relation of

scientific representations to the reality surrounding us is due,

according to this view, to our forgetfulness of these expanded material

and social processes behind the finished representations. “Through

successive stages [sciences] link us to an aligned, transformed,

constructed world” (Latour 1999; 79, see also Latour and Woolgar

[1979]1986, 69).

I find this approach insightful and corrective of the received view

on representation in its stress on the complicated process of

producing scientific representations. Yet something seems to be

missing from these studies. This has been expressed nicely by Ronald

Giere, who entitles his review of them tellingly: “No representation

without representation” (Giere 1994). Despite all the careful studies

on how scientists go about representing, nothing is actually said

about what possibly makes the inscriptions examined representative—

except of course for the overall claim that the representation and

represented both emerge and merge in the same material process of

scientific work.

It seems that these studies are playing a double game. On the one

hand they proceed as if they had excluded any consideration of the

epistemological question of representation and were instead interested

in the representative practices as social phenomena only. As Michael

Lynch puts it: “For the sociological purposes, the ‘real object’ is the

representation in hand, e.g. the visual display, and not the invisible

phenomenon or abstract relationship out there” (1990, 154). On the

other hand these studies nevertheless have a distinct epistemological

aim to “explode“ the supposed homogeneous conception of

representation in order to make room for the “deeds performed, when

those [representational] items are embedded in action“ (Lynch 1994,

146). This is in line with ethnomethodology, which has inspired much

research in STS particularly with its disdain of theoretical discourse

(In Study 2 I examine this double agenda of STS in some detail).

Now there is something contradictory about this way of

proceeding. Firstly, in an effort to deconstruct the notion of

representation the protagonists rely on what is commonly taken as

representation already in their choice of case studies. Rather than

exploding the notion of representation these cases reveal what a

complicated phenomenon scientific representation is. Secondly, in

order to challenge what they take to be the philosophical view on

representation, these studies claim that they show us what really goes

on in scientific representation. But then the question is whether

ethnomethodologists and other STS scholars themselves are relying on

a rather traditional notion of representation—the very same notion

they set out to demolish.

Reconstructing representation

Why is representation such a bad word for so many? It appears that

this reaction results from our inherited representationalist conception

of knowledge, which ties knowledge firmly to representation and for

which representation is a static relation between that which

represents (statements of language, ideas in the mind, abstract

structures, etc.) and that which is represented (“reality“, the “world“,

some physical system, and so on). Whether the representation is true

of its intended object is a question of observing a correspondence

(analysed most often as isomorphism or similarity) between the

representation and that which is represented. Moreover, according to

this view, that which is represented, i.e. reality, consists of a fixed

totality of mind- and representation-independent objects. I do agree

with the critics of representation that this view of representation

deserves to be set aside. However, I do not think that this conclusion

should lead us to banish the notion of representation (or the

representative idiom) altogether—if only because the question of

Representation and its Discontents

32 Tarja Knuuttila

representation seems to stay with us however uncomfortable we are

with it. The aforementioned struggles of STS scholars with

representation provide good examples of this.

On the other hand the notion of experimental manipulability,

which Hacking (and to a certain extent Pickering) professes, does not

really succeed in its task of replacing representational realism. In the

first place, it fits well only those sciences that allow for experimen-

tation, and thus it is not particularly suitable for the social sciences. To

illustrate, let us take the case of economics. Mäki (1996) argues that

whereas the existence of the entities to which the theoretical terms

refer is problematical for the natural sciences, the problems of

economics are different. The argument from experimental

manipulability cannot easily be applied to economics. Apart from the

difficulty of conducting experiments in economics, experimental

manipulability is not needed for ontological realism in economics

because we are not uncertain to which entities many theoretical terms

of economics (such as “consumer” or “firm”) refer. Furthermore, as I

have already noted, efforts to avoid or renounce representation do not

work even in the experimental sciences except on the level of general

declarations. This is because as soon as we start to inquire how

scientist intervene, we find ourselves engaged in complex represen-

tative processes involving specialised artefacts that record, chart,

trace, etc.

Since representation cannot so easily be dismissed, one possibility

of tackling the problem of representation is to loosen it from its

representationalist grip by reconstructing it. This effort is actually

being made on several fronts, both in philosophy and in other fields of

study. In regard to my line of argumentation I find three approaches

especially relevant: the work on embodied and distributed cognition

in cognitive science, the recent pragmatic approaches on models and

scientific representation in the philosophy of science, and the

theorizing and historical studies of scientific objects in STS. One way

to see how these very different approaches contribute to a non-

representationalist conception of representation is to see how each of

them attacks one of the following three basic assumptions of

representationalism:

1) Knowledge consists of a collection of (internal) representations

2) These representations correspond accurately to the bits and

pieces of reality

3) Reality is already made up: it consists of a fixed totality of

representation-independent objects

Recent work in the field of embodied and distributed cognition has

questioned the first assumption by concentrating on what has been

called “cognition in the wild” (Hutchins 1995). This economical and

embodied cognition uses external scaffolding, environmental clues

and cheap tricks in its cognitive tasks instead of creating complete,

internal representations of the world. The argument is that the human

brain evolved originally to coordinate the body, which made cognition

action-oriented rather than reflective. Instead of one single central

processor controlling all the cognitive activities, evolution preferred a

solution with many, more specialized processors (see e.g. Varela et al.

1991, Clark 1997 and 2003). On this basis it is possible to claim that

our cognition is distributed between individuals and artefacts

(Hutchins 1995) and that it is also largely skill-based and tool-using.

Thus for instance Dennett stresses the importance of “florid

representing”, which depends on the “objectification” of certain skill-

based contents into tools suitable for exercising other skills (Dennett

2000). Latour takes up this theme of the cognitive value of creating

objects about objects when he argues that the possibility of

superimposing, reshuffling and recombining signs and inscriptions

can engender totally new phenomena (Latour 1990). Giere (2002a) has

approached scientific cognition as distributed, claiming that “most

models in science, even in classical mechanics, are too complex to be

fully realised as mental models” (10).13 The recent, active discussion of

expertise and the tacit dimension of knowledge (see e.g. Dreyfus and

Dreyfus 1986, Collins and Evans 2002, and Study 5 of this

dissertation) is partly related to these developments.

Representation and its Discontents

13 An important precursor of this line of thinking was Lev Vygotsky, who

already in the 1920’s suggested that the development of a child’s higher

psychological functions is a result of the internalisation of social forms of

action mediated by signs and tools (Vygotsky 1978). Cognition is thus not

only embodied but also cultural. Interestingly, we do seem to use

internalised public tools, such as language, when thinking and trying to

solve cognitive problems “in our heads”.

34 Tarja Knuuttila

Whereas the first approach concentrates predominantly on the

nature of knowledge and cognition, the second line of attacking

representationalism focuses directly on the relation of representation

to what is represented. These studies criticise the assumption that

representation is a dyadic relation of correspondence between the

representative vehicle and its target. In the field of the philosophy of

science a host of pragmatic approaches to representation have recently

been proposed (Suárez 2004, Giere 2004, Bailer-Jones 2003, Frigg

2003). They all stress the importance of the use and users for

representation. Consequently, what is common to these approaches is

that they focus on the intentional activity of representation users and

deny that the relation of representation to what is represented can be

based only on the respective properties of the representative vehicle

and its target object (see Suárez 2004). Instead of asking “how do

models represent the world?” one should rather ask “how models are

used to represent the world” (Giere 2004). In arguing for three- or even

four-place relation between representation and the represented, these

pragmatic approaches in fact follow the tradition set up by C. S. Peirce,

for whom the sign relation was irreducibly a triadic relationship

including the sign (or “representamen”), the object and the

interpretant. Furthermore, Peirce understood sign activity, semiosis, in

terms of inferentiality and mediation, both of which have been

discussed in recent literature on models and representation.14

Finally, representationalism can be challenged by denying that it

makes sense to think about the world as consisting of representation-

independent objects. This is because “objects” are not available to us

except through representation. From a thoroughly constructivist point

of view, talking about representation should not pose any problem,

since representations are freed from representing the world as it is.

Quite the contrary, we construct scientific, artistic and other objects by

way of representing them. This theme has been insightfully explored

by the work on ”epistemic things” or, alternatively, “epistemic

objects” by Hans-Jörg Rheinberger (1997) and Karin Knorr Cetina

(1999, 2001). In their work, conventional scientific entities appear as

open-ended epistemic things that are actually effects of manifold and

interwoven representative practices. For neither Rheinberger nor Knorr

Cetina does this open-endness mean relativism, since scientists are

not free to construct objects as they wish—representative practices

constitute part of “experimental systems” (Rheinberger) and are

constantly “in the process of being materially defined” (Knorr Cetina

2001, 181). The implication is that the material world somehow resists

scientists’ attempts to mould it, the “the things strike back”, as Latour

(2000) has put it. 15 In scientific practice, this constraint is actively

sought, which is most evident in the case of experimentation.16

However, I will argue later in the individual studies of this

dissertation that this is also done in modelling, even though there also

the constraint itself is constructed and not just the setting in which it

is aspired after, as in experimentation. If scientific objects are treated

as constructions, then their historical trajectories become possible

topics of their own. Thus Lorraine Daston claims in her introduction

to the collection of essays Biographies of Scientific Objects that scientific

objects can be both real and historical; that is, their existence is

relative: “new scientific objects pour forth, and old ones fade away”

(2000, 5). That this way of thinking seems strange to most

philosophers is due exactly to the fact that they tend to think that the

scientific objects were always there waiting to be found.17 But then the

history of science does not offer much support for this thought.

14 On Peirce’s later stress on mediation, see Bergman (2004, ch. 4). Eco

(1984, ch. 1) and Merrell (1995, ch. 1) have in turn stressed the inferential

character of Peirce’s conception of the sign.

15 The “objectualists” appear to claim that reality is both a construction and

a constraint, which is of course confusing. It appears to me that behind their

way of seeing things there is actually a distinction between reality and the

real. This distinction, which can be traced to the work of French

psychoanalyst Jacques Lacan, somehow captures the flavour of the

poststructuralist theorising of the ineffable. (French poststructuralist theory

has had an important influence on both Knorr Cetina’s and Rheinberger’s

views on epistemic things). Reality is an effect of the coherence of our

representative practices: it is, as Hacking has aptly put it, a second-order

concept that follows from our practice of representation. “The world has an

excellent place, even if not the first one… It was found by conceptualising

the real as an attribute of representations“ (1983, 136). Thus reality is, from

the very outset, a fictive construction which is continuously questioned by

the real. The real is the unrepresentable ground of the subject’s own being

and that of the world beyond it (see Boothby 2001, 12). Thus the real

constrains the way reality can be constructed and maintained (see also

Ragland-Sullivan 1996, 192).

16 For instance Ludwik Fleck claims that the “general aim of the

intellectual work” is to create a “maximum thought constraint”: “The

work of the research scientist means that in the complex confusion and

chaos he faces, he must distinguish that which obeys his will from that

which arises spontaneously and resists it” (1979, 95).

Representation and its Discontents

36 Tarja Knuuttila

I find all these different strategies of shattering the assumptions

underpinning representationalism important and have tried to

accommodate them in my work on scientific models. Through the

notion of models as epistemic artefacts I have tried, firstly, to detach the

epistemic (and cognitive) value of models from their representational

status. Secondly, as artefacts, models are used in scientific practice

many ways, one of which is representation. I am not contesting

representation itself but rather the way it is conventionally

understood—thus I side with forces of the pragmatists of

representation. Thirdly, my view on models as first and foremost

artefacts rather than representations implies that I do not think that

there is any pre-packaged collection of objects available for us to

represent. Rather, it seems to me that models help us to imagine what

there could be, as Morgan (2004) and Frigg (2003, ch. 5) have pointed

out. With the notion of the epistemic artefact I have nevertheless

wanted to show how importantly tied our imagination is to materiality

and to the established ways of using various representative media.

Moreover, the artefactual account of models easily lends itself to the

consideration of the processes by which models and their subsequent

productive properties are built—an aspect that has been stressed by

the STS studies on representation (see above).

Next I will turn into a discussion of scientific models. To ground

the idea of models as epistemic artefacts I will provide a short

overview on how models have been treated in the philosophy of

science and how the question of representation has arisen in that

discussion.

17 The idea that our objects of knowledge are not independent of our

knowing dates back at least to Kant, see the footnote 10. Several

philosophers have also attacked the notion of the “ready-made world” (see

e.g. Putnam 1982, Tuomela 1985). What distinguishes these views from the

recent interest in scientific objects is that, unlike the philosophical

discussion, the study of scientific objects does not understand construction

predominantly in conceptual and linguistic terms but rather as social and

material activity.

3. Scientific models in the philosophy of science

The discussion of models in the philosophy of science has

heterogeneous beginnings, testifying to a variety of theoretical, formal,

and practical aspirations that appear to have different and even

conflicting goals (Bailer-Jones 1999, 32). Thus in addition to

approaches that have predominantly been interested in the pragmatic

and cognitive role of models in scientific enterprise, attempts have

been made to establish, within a formal framework, what scientific

models are. The syntactic view of models, once the “received view“,

and the semantic approach to models, the prevailing model-theoretic

approach, are both attempts of this kind.

3.1 Syntactic and semantic views on models

According to the syntactic view, a model is designed to give an

interpretation of an uninterpreted formalism or calculus. Thus,

according to Ernest Nagel, for example, a model is an interpretation of

“the abstract calculus which supplies some flesh for the skeletal

structure in terms of more or less familiar conceptual or visualizable

materials“ (1961, 90). For the proponents of the syntactic view a

scientific theory was such an uninterpreted or partially interpreted

formalism, a purely syntactic structure consisting of a set of axioms.

To interpret a theory was to specify a model for it, which makes all the

axioms of the theory true (or false). Consequently, a model for a theory

T could be defined as a set of true propositions with the same formal

structure or calculus as T (96).

The semantic conception of models contested this “linguistic“ view

of models by replacing the syntactic formulation of the theory with the

theory’s models, which are non-linguistic entities. In this view,

theories are not assemblages of propositions or statements, but

“extralinguistic entities, which may be described or characterized by a

number of different linguistic formulations“ (Suppe 1977, 221). These

extralinguistic entities—models—are taken to be structures that are

defined either by the use of set-theoretical predicates (e.g. Suppes 1961,

da Costa and French 1990) or by the use of suitable mathematical

language (e.g. van Fraassen 1980). The emergence of the semantic

conception dates back to the 1960’s with impulses both from

mathematics and computer science (see Suppe 1989, Prologue).

Scientific Models in the Philosophy of Science

38 Tarja Knuuttila

Of the semantic approaches to models (and theories) perhaps the

best-known are those of van Fraassen (1980) and Giere (1988). Their

approaches differ from each other in the degree of their abstractness

and in the ways they utilise aspects of the semantic approach to

accommodate their divergent standpoints to the empiricism-realism

debate (French and Ladyman 1999, 104).

Van Fraassen, the (constructive) empiricist, advances a “new

picture of theories“:

To present a theory is to specify a family of structures, its models; and

secondly, to specify a certain part of those models (the empirical

substructures) as candidates for the direct representation of observable

phenomena. The structures which can be described in experimental and

measurement reports we call appearances: the theory is empirically

adequate if it has some model such that all appearances are isomorphic

to empirical substructures of that model (1980, 64).

Ronald Giere, a (constructive) realist, denies that the relation between

a model and a real system should be isomorphic. Giere (1988)

develops his account of models on the basis of classical mechanics as

presented in advanced textbooks. He proposes that, to take an

example, the “linear oscillator“ referred to in mechanics texts is not a

single model with different specific versions but a cluster of models of

varying degrees of specificity (80). Thus Giere finds in the standard

textbooks “a population of models consisting of related families of

models“ (82). The models as such are not true or false with respect to

the world; the role of the theory is rather to claim a “good fit“ between

the models and some important types of real systems. Consequently,

Giere suggests that a theory is comprised of two elements: (1) a

population of models, and (2) various hypotheses linking those

models with systems in the real world (85).

Giere argues that the relationship between models and the world is

not primarily that of truth, correspondence or isomorphism, but

similarity. He is not very worried about the vagueness of the notion of

similarity, since in his opinion the cognitive sciences are

accumulating evidence that “human cognition and perception operate

on the basis of some sort of similarity metric“ (81). Moreover, Giere

claims that even the links between the models are rather relations of

similarity than logical connections. As a consequence a scientific

theory turns out not to be a well-defined entity. Nothing in the

structure of any model itself could determine whether it belongs to a

given family of models or not. It is up to the scientific community to

judge whether the resemblance is sufficient.18

The semantic conception replaced the “received view”, becoming

itself a received view.19 Frederic Suppe (1989) states confidently that

“the Semantic Conception of Theories today probably is the

philosophical analysis of the nature of theories most widely held

among the philosophers of science; it frequently is used to analyse and

treat other philosophical problems” (3). That a conception of theories

should provide us a prevailing approach to models seems already at

the outset somewhat paradoxical. It tends to downplay models in

respect to theories, as has been pointed out by Morrison and Morgan:

The semantic view claims that models, rather than theory, occupy a

centre stage, yet most, if not all of the models discussed within the

framework fall under the category ‘models of theory’ or ‘theoretical

models’… Viewing models strictly in terms of their relationships to

theory draws our attention away from the process of constructing

models and manipulating them, both of which are crucial in gaining

information about the world, theories and the model itself. (1999a, 7-

8).

Consequently, Morrison and Morgan propose that we should

investigate the models actually used in science to understand what

kind of entities scientific models are and how they function. In this

18 Giere’s views of models have remained generally similar over the

years, but they show signs of changing. In Giere (1999) he claims that

models are “humanly constructed abstract entities” (168). It seems to me

that this idea does not fit very well with the notion of distributed

cognition, a topic that he has shown a good deal of interest recently (2002a,

2002b). The idea that models are abstract entities is better suited to the

idea of “mental models” that was still popular in cognitive science some

years ago (see Giere [ed.] 1992). But in order for cognition to be

distributed, models must be materially existing things of some kind—if

they are to function as central tools of science and mediate between people

and other artefacts.

19 German structuralism (see e.g. Balzer, Moulines and Sneed 1987) also

has a model-based approach to scientific theories. They are however more

concerned with the architectonic of sciences than with individual models.

Recently, several researchers have developed the so-called “partial

structures” view, which limits the isomorphic relations between the model

and its target system (see e.g. Bueno 1997, and French and Ladyman 1999).

Scientific Models in the Philosophy of Science

40 Tarja Knuuttila

they are following a long tradition of approaching the epistemic value

of models from the point of view of scientific practice.

3.2 A practice-oriented approach to models

It can in fact be claimed that the very discussion of models was

originally motivated by practice-oriented considerations—even the

proponents of the semantic view understood themselves as providing

a more realistic picture of theories (see van Fraassen 1980, 64). Yet the

practice-oriented approach has usually involved taking into account

different aspects of the actual making of science. In the 1960’s issues of

theory reconstruction and theory change as well as of scientific

discovery prompted many philosophers to start to study models

(Bailer-Jones 1999, 31). Various writers including Achinstein (1968),

Black (1962), Hesse (1966) and Hutten (1954) likened models to

analogies and metaphors in their attempt to understand how models

function in scientific reasoning. Moreover, both Max Black and Peter

Achinstein created typologies of models in an effort to give a more

complete account of the variety of models used in science.

It is of interest that both Black and Achinstein started their

discussion of models by considering three-dimensional physical

objects, which Black thought were the “standard cases“ of models in

a literal sense of the word. He called them scale models, covering “all

the likenesses of material objects, or systems, or processes, whether

real or imaginary, that preserve relative proportions“ (1962, 220).

When we make scale models, Black points out, our purpose is to

reproduce in a relatively manipulable or accessible embodiment,

selected features of the “original“. “We try to bring the remote and the

unknown to our own level of middle-sized existence. There is,

however something self-defeating in this aim, since … we are forced to

replace a living tissue by some inadequate substitute, and a sheer

change of size may upset the balance of factors in the original“ (221).

Thus, “inferences from a scale model to an original are intrinsically

precarious and in need of supplementary validation and correction“

(ibid.). Achinstein, too, paid attention to the manipulability or

“workability“ of physical models (which he called representational

models). According to him “representational models, although used

in all the sciences, are particularly central in engineering. Instead of

investigating an object directly, the engineer may construct a

representation of it, which can be studied more readily” (1968, 209).

Morrison and Morgan’s conception of models as mediators that

function as investigative instruments amounts to a return to this

tradition, in that they also stress the epistemic importance of building

and manipulating models.

The notion of models as mediators builds importantly on the work

of Nancy Cartwright (1983). In arguing that the fundamental laws of

physics do not describe the regularities that exist in nature,

Cartwright reverts to models. There is a gap between the general

theoretical principles of physics and the messiness and complexity of

data which phenomenological laws in turn strive to capture. It is the

task of models to bridge that gap: “The route from the theory to reality

is from theory to model, and then from model to the phenomenological

law. The phenomenological laws are indeed true of the objects of

reality—or might be; but the fundamental laws are true only of objects

in the model” (4). For a model to function as a bridge between theory

and data, a model has to include some genuine properties of the

objects modelled. But in addition to that, models contain properties of

convenience and fiction (15). These features are needed to bring the

objects modelled into the confines of the theory. Building models is

pragmatic activity, “adjustments are made where literal correctness

does not matter very much in order to get correct effects where we

want to get them; and very often…one distortion is put right by

another” (140).

The similarities between Cartwright’s account of models as

bridges and that of Morrison and Morgan’s as mediators are clear. In

both accounts models occupy the middle space between the theory

and the world (or data), thus linking them. What is more, both

accounts stress how “additional elements” are brought into models.

This is exactly what makes models able to connect the different realms

but it is also what makes them “at least” partly autonomous, a point

that Morrison and Morgan especially stress. What I find particularly

fresh and rewarding in Morrison and Morgan’s approach is precisely

their emphasis on the epistemic importance of the independence of

models and their mediating capabilities. I think that their approach

can actually be used as a starting point for developing a non-

representationalist account of models (granting that anything like this

need not have been their original intention). However, before turning

to that, I wish to examine the idea that models are, first and foremost,

representations.

Scientific Models in the Philosophy of Science

42 Tarja Knuuttila

3.3 Models as representations

As already noted, a certain understanding of representation is part

and parcel of the semantic approach, since the structures specified by

models are posited as possible representations of either the observable

phenomena or, even more ambitiously, the underlying structures of the

real target systems. This relation of representation between a model

and its target is understood in terms of isomorphism or partial

isomorphism. Thus, according to the semantic view, the structure

specified by a model represents its target system if they are structurally

isomorphic. By isomorphism I refer to a kind of mapping that can be

established between the two that preserves the relations among their

elements. Isomorphism can be defined formally, which is one of the

charms and motivating forces behind the semantic theory. Not all

protagonists of the semantic theory agree with the formulation

presented above. For instance Giere (1999) thinks that it represents a

“carryover from an older picture of science”:

The clearest expression of the old picture is to be found in the

philosophy of mathematics and logic, and in formal semantics. The

idea is that the structure of reality mirrors the structure of set-theory.

Reality is conceived of as consisting of discrete objects, sets of discrete

objects, sets of sets of objects, sets of ordered pairs of objects, and so

on. True statements are those that describe objects as belonging to the

sets to which they in fact belong. A complete science would be the

conjunction of all and only the true statements of this set-theoretically

structured reality. (78)

In terms of the argument of this thesis it is evident that the above-

mentioned picture of science painted by Giere is thoroughly

representationalist: it depicts representation in terms of a

correspondence created by isomorphism, supposes that reality

consists of a fixed set of discrete objects and posits that there is a

privileged set of representations, structures that are, to use an

expression of Rorty “automatically and intrinsically accurate” (1980,

170).

Overall, the critics of the semantic approach have not worried very

much about its representationalist view of science. Instead they have

limited their critique to the tendency of the semantic approach to

reduce representation to isomorphism (or similarity). The critics have

argued, among other things, that denoting a symmetrical, reflexive

and transitive relation, isomorphism does not satisfy the formal and

other criteria we might want to affirm concerning representation (see

e.g. Suárez 2003, Frigg 2003). I find these critiques both thorough and

conclusive, which is the reason this issue does not concern me here. I

rather turn to the alternative accounts of models that have been

presented by the critics of the semantic approach.

Interestingly, the critics of the semantic approach nevertheless

share with them the same presupposition that the main task of models

is to represent the world. In arguing against the semantic view of

models, some of them have explicitly made representation the crucial

property of models (see e.g. Frigg 2003, 33; Hughes 1997, and Suárez

1999), which is presumably something that most philosophers

generally agree in. A characteristic statement of this linkage is that

given recently by Paul Teller (2001):

I take the stand that, in principle, anything can be a model, and that

what makes a thing into a model is the fact that it is regarded or used

as a representation of something by the model users. Thus in saying

what a model is the weight is shifted to the problem of understanding

the nature of representation. I do not begin to have a workable

account of representation, so what is accomplished by this move? The

point is that when people demand a general account of models, an

account, which will tell us when something is a model, their demand

can be heard as a demand for those intrinsic features of an object which

make it a model. But there are no such features. We make something

into a model by determining to use it to represent.

While I do agree with Teller that it is our achievement that models

represent, I would rather not propose that we make a thing into a

model by deciding to use it as a representation of some aspect of the

world. In my opinion there are several reasons why we should resist

binding models too firmly together with representation:

1) Needless stumbling over the “puzzle of representation”. It is perhaps no

wonder that the proponents of the semantic view have not presented

any explicit analyses dealing with scientific representation, since the

semantic approach takes the question of “in virtue of what do models

represent” to be solved by reverting to isomorphism.20 The problem of

representation arises when, on the one hand, models are regarded as

being primarily representational entities and, on the other hand, it is

granted that constructing models involves idealisations,

Scientific Models in the Philosophy of Science

44 Tarja Knuuttila

approximations, conventions, fictions, and the like. Thus the question

becomes, as Callender and Cohen have aptly put it: “How can

[models] represent, if they, well, misrepresent?” (2005, 5). The urgency

of this question is, of course, directly linked to the representationalist

conception of knowledge. It dissipates once we stop linking the

epistemic value of models to their being more or less accurate

representations of the independently existing, real target systems.

What is more, then we are not in such a pressing need of giving an all-

around explanation for the possibility of representation. Rather,

whether or not a model represents something will be judged case by

case in view of its specific goals and with the help of other

information at hand—and general philosophical intuitions

concerning what makes a model a representation are largely

redundant in this task. Perhaps the best a purely philosophical

analysis can do is to offer a deflationary account of representation, as

Suárez (2004) has suggested.

2) Many scientific models cannot be considered as clear-cut representations of

any specific external systems. In the case of many scientific models we do

not know what exactly they are supposed to represent. This is

especially striking for instance in artificial intelligence, where new

kind of reality is being created. For instance, in his study of early

synthetic brain models Asaro (2005) claims that “it is hard to conceive

of just what entities these models were supposed to be modelling”

(55), granting that these models were models of mental functions,

whose ontological status is questionable as opposed for instance to

those of behaviour or neurons. It seems to be more true of scientific

practice that rather than functioning as straightforward

representations of some “real” systems, models often present us some

tentative mechanisms, processes or solutions that can then function as

a basis for various inferences. On many occasions models are used

primarily as demonstrations, exemplifications, proofs of existence,

test-beds, etc. Interestingly, even bad models and errors give us

knowledge, which runs counter to the idea that knowledge is based on

20 This is of course a somewhat simplified claim. Both van Fraassen and

Giere have been stressing the pragmatic nature of representation in their

recent writings (Giere 2004, van Fraassen 2004). But then I do not know

whether Giere can still be classified among the adherents of the semantic

conception.

representing things rightly (in relevant respects and aspects). That

this should be so is occasionally reflected in the way authors

interested in scientific practice write about representation. For

instance, when discussing representation, Morrison and Morgan

(1999b) use such expressions as “rendering” and “translation”. Their

choice of these words seems to result from their uneasiness with the

traditional notion of representation as that of “standing for” (though

they refer to “mirroring”). “Rendering” and “translation” are

commonly-used words in STS.21 Both terms refer to the

accomplishments that are brought about by the participants’ actions.

From this perspective, representation becomes a complicated

productive and interpretative process, which is one of the points I

make in Study 5.

3) Conceiving of models as representations accepts the cognitive challenge of

modelling in the wrong way. It is as if we already knew enough of the

world to be able to represent the real objects waiting there to be

represented. The representational approach also seems to assume that

we already know how to represent the objects to be represented and

have the appropriate means at hand. But if this were the case we

would not need to represent the object in the first place for other than

perhaps didactic and practical purposes (for those who do not know

what we know and for the purposes of communicating and

remembering). Thus representationalism approaches science from the

point of view of finished science. I suggest that we model the

phenomena because we usually do not know enough about those

“systems”. Thus one has to conjecture what the different features of

the phenomena are like, how they are organised and how they

function. This conjecturing has to happen through and with the help

of certain already familiar representative means (formal languages,

diagrams, three-dimensional objects, modelling methods, etc.), the use

21 “Rendering” is used by ethnomethodologists, who thereby dissociate

themselves from the representationalist paradigm (see Garfinkel 2002, ch.

3). “Translation”, in turn, has been made popular by the actor-network

theory. Latour (1999) defines it in the following way: “Instead of opposing

words and the world, science studies, by its insistence on practice has

multiplied the intermediary terms that focus on the transformations so

typical of the sciences… In its linguistic and material connotations,

[translation] refers to all the displacements through other actors whose

mediation is indispensable for any action to occur” (311).

Scientific Models in the Philosophy of Science

46 Tarja Knuuttila

of which is by no means a minor part of the problem. As I argue in

Study 5, the problem of representation does not concern only what is

being represented, but also the ways to do it. Moreover, the means of

representation are themselves conducive to certain kinds of solutions

and problems—which is due to the affordances of the medium used.22

4) Models have many other distinctive uses apart from representation.

Because of this, it is misleading to reduce modelling to representation.

Firstly, models typically occupy an intermediate space between

representing and experimenting. They share with representation the

property that their medium of expression is different from that of their

object of reference. On the other hand they share with experimentation

the fact that one can try out different possibilities with them. For

instance, it is possible to study how the “structures [of the model]

behave when the parts of the model are put together and when we

vary certain things in the model” (Morgan 2002, 220). Another typical

feature of modelling is the way we “model” entities and processes of

new domains with the help of already existing theoretical tools,

computational templates and methods borrowed from another more

established domains. One might call this procedure “representing

as”, but typically in this context the expression used is to “model on”;

e.g. “many sciences are modelled on mechanics”. This is related to the

cognitive value of modelling: since the phenomena we are interested

in seem often quite impenetrable to us, we can probe them by applying

to them modelling methods and templates that have proven to be

successful elsewhere. This is linked to the third point I want to make.

Regarding models as representations have led many to argue that

models are intended for specific phenomena (see Frigg 2003, 33;

Suárez 1999). This seems to follow from the idea that models are,

inherently, “models of” something. But models are as importantly

“models for” something, as Fox Keller (2000) has pointed out. They

are not just representative entities, but often also productive ones. I do

agree that when a model represents, the model is intended for a

22 A nice example of this is provided by Morgan (2004), where she

discusses the mathematisation of economics, how in the beginning of the

mathematisation of economics both “the process of making

representations” and “the representing relation” remained partly opaque

for the early developers. Moreover, Morgan notes how the

mathematisation of economics changed the way economists understand

and depict the economy.

certain phenomenon. But it seems to me to be more true of scientific

practice that models are characteristically entities that can be used to

represent many different kinds of things. The defenders of the

“models of” view can certainly try to account for this by converting

the material object representing different target phenomena into

different models. This seems to me a legitimate philosophical move,

yet it loses sight of one important characteristic of modelling: the

detachability and the consequent re-applicability of certain already

rather stabilised representative apparatuses to diverse kinds of

problems and data.

I think that the basic problem of the representational approach in

general is that it treats science as if it were already finished, or at least

quite ready.23 That this has not worried philosophers very much over

the years is for the most part due to their preoccupation with what can

be called as “the rational reconstruction of science”.24 However, if

philosophers are, as I think they should be, interested in the very

practices through which knowledge is being created, then the

representational approach to models proves to be limiting. This is

somewhat paradoxically acknowledged by the recent pragmatist

accounts of scientific representation by Giere (2004) and Suárez

(2002a, 2004) which both make it clear that nothing very substantive

can be said about the relationship of representation in general. In

these accounts representation is contextualised to the users’, or

agents’, activity of representing (Giere) or inferring (Suárez) in view of

their specific aims and goals.25 Thus, on my interpretation, these

accounts actually point out the need for an approach that, instead of

Scientific Models in the Philosophy of Science

23 Here I speak rather of “representational” instead of “representionalist”,

since those authors, like Teller, who consider models as representations do

not underwrite all the tenets of representationalism (as semantic conception

does, in my opinion).

24 This attitude started to change, of course, already in the early 1960’s due

to the so-called “historicist turn” with philosophers such as Stephen

Toulmin, Thomas Kuhn and Norwood Russell Hanson.

25 Giere’s four-place definition of scientific representation and Suárez’s

inferential conception of scientific representation are presented in Study 4

of this dissertation. This discussion is, however, based on the papers they

presented at the 2002 Biennial Meeting of the Philosophy of Science

Association (Giere 2002c, Suárez 2002b) and not on their final published

symposia papers (Giere 2004, Suárez 2004).

48 Tarja Knuuttila

focusing only on representation provided by ready-made models,

takes a wider perspective on the epistemic value of models—an

approach that takes seriously the epistemic importance of building

and interacting with models.

3.4 Models as epistemic artefacts

It seems to me that Morrison and Morgan’s framework of models as

mediators provides an alternative to considering models as

representations. They explicitly recognise the many tasks of models, of

which representation is just one. As I will treat their approach in the

individual articles of this dissertation, I will not go into its details

here, but rather rehearse what I take as the most important

characteristics of their programme, viz. the independence and

mediating characteristics that they ascribe to models. Nevertheless, it

appears to me that Morrison and Morgan do not quite cash out the

radical potential of their programme. In order to turn the models-as-

mediators approach into a true alternative to the prevailing models-as-

representations approach, one needs to free models from the theory-

data framework still present in Morrison and Morgan (1999b) and to

interpret models materially, thus granting them an individual status

as epistemic artefacts.

Provided that the word mediation can be understood in a very

wide sense covering complex semiotic processes, including the

activities of various actors, the mediation between theory and data (or

world) that Morrison and Morgan concentrate on is a rather limited

version of mediation. Morrison and Morgan point out that it is the

(relative) independence of models that makes them able to mediate. I

agree, but would like to add that it is in turn the material dimension,

and not just “additional elements”, that makes models able to

mediate. It is the material dimension of objects that gives them the

robustness necessary to maintain their identity across different sites.26

But making this move means also leaving the conceptual and ideal

world of philosophy and entering into the social and material world

of human actors, where material objects, usually human-made

artefacts, draw together numerous activities and different actors.

From the scientific practice point of view, it is easy to see that scientific

models are such things. This is especially evident in computer

modelling, where models more often than not act as boundary objects

(Star and Griesemer 1989) between different groups of scientists from

different disciplines.27

Now, apart from enabling the mediation between different actors,

materiality is also important for the epistemic functioning of models.

Morrison and Morgan attribute a large part of the epistemic

significance of models to the processes of their construction and

manipulation instead of focusing unilaterally on representation. As

they stress that we learn from models by building and manipulating

them, their approach in fact implies that there needs to be something

more concrete than just conceptual ideas to work on. For us to learn

from a model, it has to be a self-contained thing with which we can

interact and work. The epistemic enablings of models are due to the

way in which their materially embodied constraints intersect with

their intentional uses. Consequently, I suggest that models are

intentionally constructed and materially embodied things, epistemic

artefacts, the constraints of which are characteristically turned into

affordances for epistemic purposes. A fuller formulation of this idea is

presented in Study 3.

I suggest that conceiving of models as epistemic artefacts provides

a fresh outlook on models and their epistemic value. It attributes the

epistemic value of models to their epistemic productivity rather than

reducing it to the representation of some pre-existing natural or social

systems. It also provides a new angle from which to approach the

characteristics of models and representation. Namely, approaching

models as artefacts makes it natural to ask how and of what elements

they are made. This directs our attention to the processes of

representation that underlie “ready-made” models. From this point of

view representation appears as a complicated process that makes use

of various representative means to convey something that has already

been theoretically rendered or otherwise prepared into another

medium or form. With this in mind we can turn to the original articles,

on which the main burden of proof of this dissertation rests.

26 By “material” I mean something that is concrete and corporeal,

occupying space and time and able to interact with other things and

human beings. For a discussion of the ontology of material objects in the

social world, see Harré (2002).

27 See Mattila (2005) for an analysis of the interdisciplinary work of

modelling the transmission of infectious disease.

Scientific Models in the Philosophy of Science

50 Tarja Knuuttila

4. An overview of the original articles

The articles are ordered according to the time of their writing. This

seemed to be the most natural way to organise them in view of both

their content and the emergence of the ideas presented in them: from

them one can trace the development of the artefactual approach to

scientific representation that I am arguing for in this thesis. As already

mentioned in the Introduction, these articles participate in the specific

discussions of scientific representation in various fields: philosophy of

science, science and technology studies, semiotics and cognitive

science. Consequently, in the abstracts of the articles below I shall, in

addition to presenting their main arguments and results, also

contextualise them and show how they relate to each other. The first

two articles deal with more general issues concerning representation.

The first focuses on the so-called crisis of representation in the

humanities, and the second deals with the problem of reflexivity in

the field of science and technology studies. The next four articles

study representation in the context of modelling. Common to all of

them is the idea of models as epistemic artefacts. They use this concept

in discussing the interrelated questions of representation, modelling,

and cognition.

Study 1:

Knuuttila, Tarja

“Is Representation Really in Crisis?”

Semiotica 143 (2003), 95-111.

“Is Representation Really in Crisis?” is written mainly for

semioticians and literary critics. Accordingly it assumes some

background knowledge of semiotics. It claims that there is nothing

very “postmodern“ or recent about the crisis of representation. The

“crisis” has mainly dressed a traditional epistemological problem in

more up-to-date garb. The most important point of the article is to

show, however, how the work done on scientific representation in STS

is relevant for the discussions of the crisis of representation. I argue

that the excesses of postmodernist discourse depend on a too

idealistic and traditional understanding of representation, an

understanding for which the work being done in STS offers a good

antidote. The theme of representation as artefact-using activity, which

is central to this thesis, appears already in this article.

The article opens by distinguishing between two types of claims

concerning the crisis of representation: an ontological and an

epistemological version of it. The ontological version takes for granted

that the crisis has been brought about by the expansion of mass

communication, which has made our modern life world increasingly

packed with representations and virtual artefacts of all sorts. It is

supposed that rather than being in contact with reality, we are thus

increasingly dealing with representations of it. On this basis it has

then been claimed that reality proper is in fact receding—without us

even noticing.

The epistemological version, in turn, questions the relationship

between our representations and reality. The problem is how our

ideas, words or other signs are able to “correspond” to real objects

when they seem to be very different kinds of things. The linguistic turn

of the last century externalised the sphere of representation, yet the

problem of representation stayed much the same. A recent externalist

version of the problem of the empiricists can be found for instance in

Umberto Eco’s semiotics (e.g. 1984). According to his notion of

An Overview of the Original Articles

52 Tarja Knuuttila

encyclopedia, a sign cannot refer to an object but is simply interpreted

by another sign. Thus the sphere of representation starts to look like a

prison from which there is no access to reality proper.

It appears to me, however, that the proponents of the crisis of

representation have not paid enough attention to the technological

efficiency of our mediated lifestyle, which critically depends on our

reliance on man-made representations of diverse sorts. I argue in “Is

Representation Really in Crisis?” that postmodern discussions of

representation have more often than not, forgotten that

representations are themselves concrete, material things that have real

effects. To make the point I present some exemplary work on

representation done in the field of STS. Bruno Latour and Steve

Woolgar’s Laboratory life (1986[1979]) has shown how any scientific

representation is a result of many laborious translations accomplished

using diverse and often complicated inscription devices. The paradox

of the process of representation is that once the final representation is

reached, the process of making it is excluded in the discussions about

what it means. Representations are treated as if they were direct

“signatures of the phenomena under study“, but as a by-product of

this procedure the problem of representation emerges. I also discuss

the work of Michael Lynch, who has attempted to show how in

scientific representation the artificial properties introduced by the

representational devices merge with the natural object and thus make

it understandable in the first place.

Now, the problem is how to interpret these constructivist insights.

I claim that they indicate a way out of the crisis of representation;

however totally different conclusions from constructivism have also

been drawn. For many, constructivism has meant relativism28

(witness for instance the unhappy phenomenon of the so-called

“science wars”). Reading Richard Rorty and Hilary Putnam I try to

diagnose why being both a constructivist and a realist has been such

an uneasy position for many philosophers. This seems to be at least

partly due to the common predisposition of philosophers to treat

construction as if it were a matter of conceptual and linguistic activity

only. The situation becomes different once it is realised that our

representative practices and their products take part in complicated

28 This is of course one important reason why the constructivist

standpoints presented in STS have created so much heated discussion (see

e.g. Hacking 1999; Gross and Levitt 1994).

social and material activities with their own specific ends. These

worldly activities, in which the representations themselves are

produced and used, establish the link between them and those things,

the processes and phenomena they are about. Moreover, this is

actually a process of co-construction: through the interrelated

activities of theoretical reflection, representation and experimentation

scientific objects come into being. This kind of constructivist outlook

leads to relativism only if we accept the tenets of representationalism,

according to which the world consists of some fixed totality of

representation-independent objects and expect that in order to give us

knowledge our representations have to depict these objects truthfully

or accurately.

An Overview of the Original Articles

54 Tarja Knuuttila

Study 2:

Knuuttila, Tarja

“Signing for Reflexivity: Constructionist

Rhetorics and Its Reflexive Critique in Science

and Technology Studies”

Forum Qualitative Sozialforschung / Forum: Qualitative Social

Research, (2002), [On-line Journal], 3(3). Available at: http://

www.qualitative-research.net/fqs-texte/3-02/3-02knuuttila-e.htm

(52 paragraphs).

As, paradoxically, many constructivists29 themselves also understood

realism in representationalist terms, the accusations of relativism that

have been levelled at constructivists are at least partly justified. The

second article inspects what happens when one takes into account the

constructedness of our representations, but is still attached to the

ideas of metaphysical realism and the accompanying correspondence

theory of truth. I claim that it was exactly this combination that led

“reflexivists” to claim that scientific discourse is fundamentally

flawed in its attempt to create an illusion of objectivity. Since the

1970’s these kinds of reflexive pronouncements were launched

especially in the fields of anthropology, sociology and social studies

of science. The declarations were followed by attemps to write

scientific articles so that they would more obviously display their own

undeniable artificiality.

The second article studies the discussion of reflexivity in STS. The

STS discussion offers an especially good place to study reflexivity

since reflexive critique was ambitiously practised there on at least in

three interrelated levels. Firstly, the STS reflexivists pointed out the

inherent reflexivity of STS itself: its aim of studying scientific study

scientifically.30 Secondly, though being in principle favourable to the

emerging constructivist programme, the reflexivists nevertheless

29 In this study I have used “constructionism” instead of “constructivism”

in line with Hacking (1999). In the rest of this thesis I have used the STS

participants’ term “constructivism” instead.

30 This critique applies especially to the “strong programme” of the so-

called Edinburgh school, which still opted for causal explanation.

criticised the constructivists for forgetting the constructedness of their

own accounts. From the reflexivists’ point of view the constructivists’

effort to describe what really goes on in science was dubious taking

into account their own constructivist doctrines. Thus, thirdly, the

reflexivists proposed that one should renew scientific writing by

adopting literary devices that would make explicit the

constructedness of any scientific account.

In regard to the aforementioned claims, “Signing for Reflexivity:

Constructionist Rhetorics and Its Reflexive Critique in Science and

Technology Studies” examines what kind of a problem reflexivity in

STS is, and whether the new ways of writing proposed by the

reflexivists constitute an appropriate reaction to the problems of

scientific representation. The article attempts to show that the

artificiality and conventionality of our representations lead to

epistemological problems only if we assume that in order to give us

knowledge of the world, our representations have to be more or less

accurate or truthful reflections of it. If this is not the case, the rationale

for writing reflexively vanishes. In fact, if we admit that any scientific

representation is also a purposeful construction, then the question

becomes in what ways representations satisfy their intended scientific

uses best. Literary devices borrowed from artistic discourses may

entirely miss the mark when it is a matter of conveying some features

or results as clearly and convincingly as possible. In fact, the

reflexivists’ own discourse testifies to this. Their critiques of

constructivism were written in the form of conventional critiques.

Only after the point was thus successfully brought home did they start

to experiment with reflexive writing.

Nothwithstanding their fruitless struggle with (literary)

representation, the reflexivists made a genuine contribution in

pointing out the self-refuting tendencies of constructivist rhetorics.

Namely, the assertion that all knowledge is local, situated and socially

accomplished contingent achievement seems to be either trivially true

or leads to reflexive paradoxes. The question is why these kinds of

claims were then repeated over and over again in STS—despite the

reflexivist critique presented. I suggest that STS authors were, more or

less consciously, practising deconstruction: they were attempting to

contest the hierarchies invested in traditional distinctions such as

global/local, theory/praxis, or general/specific. This work need not

challenge the epistemic value of science per se, but if it gives the

An Overview of the Original Articles

56 Tarja Knuuttila

appearance of doing so, it leads to a position that easily turns against

the STS scholars themselves. A good example of this has recently been

presented by Lynch and Cole (2002). They analyse the difficulties

encountered by one of the authors, who, being known for his STS

connections, had to account for his conception of science before being

accepted to give expert testimony in a legal case.31

31 “Signing for Reflexivity: Constructionist Rhetorics and Its Reflexive

Critique in Science and Technology Studies” was already in press when this

interesting paper was presented in the EASST 2002 Conference in York,

which is the reason I do not refer to it in the Study 2.

Study 3:

Knuuttila, Tarja and Atro Voutilainen

“A Parser as an Epistemic Artefact: A Material View

on Models”

Philosophy of Science 70 (Proceedings), (2003), 1484–1495.

In opposition to the widespread belief (also exemplified by the

reflexivist struggles) that the artificial features of scientific

representations somehow question their objectivity and epistemic

status, this article claims that artefact building does bring us

knowledge in various ways. The article takes part in the philosophical

discussion of scientific models by proposing a new approach to

models. I suggest that models can be conceived of as epistemic artefacts,

the epistemic value of which derives from their being intentionally

constructed and purposefully constrained material things. In addition

to stressing the cognitive importance of artefactuality, this approach

also departs from tradition by relating the epistemic value of models to

their material dimension. The reigning semantic approach to models

treats them as abstract theoretical entities for which only structural

“two- or three-dimensional” representation matters. This view on

models has as its goal to present a unifying, formal account of models,

which, despite its proponents claims to the contrary, actually has

problems in accommodating the very diversity of models in scientific

practice. One may suppose, however, that the very plurality of models

in scientific practice is not inconsequential, thus leading one to ask

how these diverse things function in science.

The article takes as its starting point Morrison and Morgan’s

(1999b) practice-oriented conception of models as investigative

instruments and develops it in the direction suggested by Marcel

Boumans (1999) in the very same collection of articles. Whereas for

Morrison and Morgan models are (partly) independent mediators

between theory and data, Boumans loosens models from their

subservience to the theory-data-framework by treating them as

constructed entities made up of various ingredients. Inspired by this

line of work I however take one step further and argue that models

used in science are actually epistemic artefacts, whose epistemicity

An Overview of the Original Articles

58 Tarja Knuuttila

importantly accrues from their intentionality32 and materiality. The

intentionality and materiality of epistemic artefacts are coupled

through the notion of affordance due to James J. Gibson’s ecological

theory of perception (1979). What is remarkable about this notion is

that it cuts across the dichotomy between the subjective and objective

stressing the complementarity between the environment and the

organism. Thus affordances are on the one hand based on the objective

material properties of the environment and on the other hand on its

consequences for the specific organism. 33 Applied to humans and

artefacts this means that the materiality of an artefact constrains the

uses to which it can be put. I argue that this element of constraint is in

fact conducive to scientific reasoning, if devised in a skilled and

purposeful way, which is where intentionality comes into the picture.

The notion of an epistemic artefact is applied to a language-

technological artefact, a parser. The description of the parser is written

by my co-author Atro Voutilainen, a language technologist. A parser

is interesting model, in that its very status as a model is questionable

from the traditional semantic point of view. As a working program, it

cannot easily be rendered as an abstract structure, given that it seems

to be more like a thing, or an instrument, that is primarily appreciated

for what it produces: a morpho-syntactic analysis of written text.

However, approaching a parser as an epistemic artefact discloses its

affinity to various other things that scientists call models. In the case

of a parser the constraints built into the language description are

made operative by implementing it as a computer program.

Consequently, the notion of models as epistemic artefacts makes room

also for considering computer programs as models.

Finally, I discuss the implications of the artefactual approach

developed for the question of representation. The article ends by

taking up many themes concerning models and representation that

will be more fully developed in the next two articles. Thus I argue that

models as epistemic artefacts give knowledge in many other ways

than just via direct representative links, being typically used as both

objects and tools of inquiry. Moreover, I point out how the different

roles of a model can be closely linked. Consequently, the instrumental

success of a parser, i.e. its producing reliably what we expect from it,

makes it also an interesting object to study in our effort to understand

language and cognition.

Study 4:

Knuuttila, Tarja

“Models, Representation, and Mediation”

(in press) Philosophy of Science 72 (Proceedings), (2005).

This article continues and expands the discussion of models and

representation started by the previous article. It relates the notion of

models as epistemic artefacts to the discussion on models and

representation in the philosophy of science. The article opens by

observing that even though philosophers of science typically ground

the knowledge-bringing aspects of models in representation, they have

widely different opinions of what constitutes representation. This of

course is bound to awaken suspicions of whether philosophers

actually do agree as to what the epistemic value of models depends on.

Consequently, I examine the recent discussion of models and

representation, where a definite change from more traditional dyadic

structuralist approaches to triadic pragmatist ones can be discerned.

From a brief discussion on the shortcomings of the structuralist

approach I move on to the pragmatic approaches advanced by

Daniela Bailer-Jones (2003), Ronald Giere (2002c) and Mauricio

Suárez (2002b).

Of the pragmatic accounts presented, I find Bailer-Jones’s idea of

approaching the question of representation through the propositions

entailed by models somewhat misguided. It loses sight of the diverse

media that models make use of, a consideration that seems to be

important for understanding the specific scientific value of models as

representations. Moreover, the talk about propositions in the context

of models and representation appears to be somewhat paradoxical,

given that the interest in models in the philosophy of science has been

motivated by a desire to break away from the language-orientedness of

32 Artefacts can be claimed to be intentional in the very general sense of

being directed towards some goal or thing, which intentionality is

bestowed upon them by human activity.

33 For an interpretation of affordances in terms of material dispositions, see

Harré (2002) and Scarantino (2003).

An Overview of the Original Articles

60 Tarja Knuuttila

the so-called “received view” (see e.g. van Fraassen 1980, 44;

Woodward 2002, 279-380; Frigg 2003, 10-11). In contrast, both the

similarity account of representation by Ronald Giere and the

inferential account by Mauricio Suárez seem to give interesting and

partly complementary approaches to representation. Thus, whereas

Giere stresses the properties of the representative vehicles (i.e. they

should be similar to their targets in specified ways), Suárez focuses on

the inferential activities of “competent and informed” users of

representation.

What is interesting about these pragmatic approaches is that they

agree that no more than a minimalist account of representation can be

given, since representation is essentially an accomplishment of the

users of the representation. Users make the model to represent that

which it is modelling, relying, of course, on the properties of the

model. Thus it may seem that the model becomes a model first when it

is used as such, i.e. representing something with its help (see the

discussion above). However, it appears to me that taking the

pragmatic approach seriously actually implies that the link between

the models and representation is looser than is usually supposed. I

suggest that, rather than being representations, models should be

approached as epistemic artefacts, as self-contained artificial objects

that can be used in scientific endeavour in a multitude of ways. This

makes room for the observation that from the point of view of scientific

practice the representative links to reality provided by models are

often more indirect, hypothetical and preliminary than we have

thought. Moreover, the very same models can be used to represent

different kinds of things. Consequently, in “Models, Representation,

and Mediation” I end up articulating a two-fold approach to

representation. My main idea is to approach representation as a dual

phenomenon, comprised of both a material sign-vehicle and an

intentional, three-place relation of representation that connects the

sign-vehicle to whatever is being represented.

This two-fold approach makes it possible to study scientific

representation from two different angles. On the one hand one should

study the artefacts, the models, themselves: their specific constraints

and affordances, as well as the media, methods and previous

knowledge they rely on. On the other hand one should study how the

representative relation between the sign-vehicle and its object is

achieved. Besides, I find the distinction between representation as a

sign-vehicle and as a relation illuminating because the word

“representation” is frequently used in both of these senses, causing

them easily to coalesce into another. This is in fact what happens in

dyadic accounts of representation, for example in the structuralist

approach, which assumes that representative vehicles are able to

create the relation of representation by themselves, due to their

inherent properties.

An Overview of the Original Articles

62 Tarja Knuuttila

Study 5:

Knuuttila, Tarja

“From Representation to Production: Parsers and

Parsing in Language Technology”

(in press) in Johannes Lenhard, Günther Küppers

and Terry Shinn (eds.)

Simulation: Pragmatic Constructions of Reality.

Sociology of the Sciences Yearbook. New York: Springer, (2006).

In Study 4 I claimed that one of the reasons to treat models as

epistemic artefacts is to loosen their epistemic value from their

representative function. Consequently, the task of this article is to

show what other epistemic roles besides representation a scientific

model can have. I proceed by presenting a case study of the Constraint

Grammar Parser, a computational model of a syntax whose primary

goal is to give a morpho-syntactic analysis of a running text. In Study

3 the principles of building a slightly different kind of parser, the

Finite-State Constraint Grammar, were presented. The parser was

introduced by a linguist, who has himself been fabricating it. Here my

goal is somewhat different: as I attempt to paint a down-to-earth

picture of the place of a parser in language technological research, the

study is based on the publications of a group of scientists making

parsers, as well as on interviews conducted with them.

As a language technological artefact the parser can be claimed to

imitate human performance in the sense that its task is to give same

kind of analyses to a text that a human linguist can. Thus it is a

simulation both in the sense of being a stand-in for a human linguist

and being a computer program that executes the grammatical

constraints of a specially devised language description. Yet, even

though the task of a parser is to simulate the “output” of a human

linguist, it cannot be taken as a realistic representation of the linguistic

competence of a linguist. The parser thus presents us a clear case of

being a model for something instead of being a model of something (Fox

Keller 2000). It is, rather, a new kind of thing in itself than a

representation of something that exists already. If the epistemic value

of models were tied to representation, the parser would not appear to

be a very interesting epistemic thing in the first place. One might even

question its status as a model, as already suggested in “A Parser as

an Epistemic Artefact: A Material View on Models“. In my opinion,

this does not show that there is something wrong with the parser as an

example of a model but rather with the philosophical outlook on

models. As I have already argued, it is unclear in the case of many

scientific models what exactly they are models of. Thus I would not

make being a representation a criterion for what being a model

amounts to, which has also the additional problem of how then to

distinguish models from the other scientific representations which we

would not prefer to characterise as models. The answer to this

question is, as I have already claimed and will claim in this article

especially, that we usually take as models such purposefully

fabricated things that we can work, interact and experiment with—

and it seems that computer simulations even radicalise this aspect of

modelling.

The uneasy status of models as representations has of course been

noticed by some philosophers of science and thus there has been some

discussion of models as tools in addition to that of models and

representation (see e.g. Cartwright, Shomar and Suárez 1995, Klein

2001). Indeed, it is a typical move in the general discussions concern-

ing representation and representationalism that the things we take to

be representations are claimed to be tools rather than representations.

Thus, for instance, Rorty’s critique of representationalism asserts that

linguistic expressions, and consequently language itself, should be

considered as tools. Considering representative artefacts as tools

offers a convenient way for him to circumvent the variously

intertwined notions of representation, realism and truth. The

Constraint Grammar Parser I consider in this article is obviously a tool,

but I argue that it is other things, too. It can be also considered as a

worthy research object in its own right and as an inferential device.

The fact that parsers are also research objects of computational

linguistics and language technology serves to underline the fact that

models need not be treated just as surrogates for reality proper. In its

role as an inferential device, the parser comes closest to functioning like

a representation of some kind. However, since it cannot be taken to

offer any realistic representation of human linguistic competence, it

gives indirect evidence of it instead.

An Overview of the Original Articles

64 Tarja Knuuttila

Last but not least, I have tried to make the work of representation

characteristic of modelling visible in my treatment of the parser

construction. This is because the discussions of models and

representation have been by and large neglectful of the way models

are themselves products of various representative procedures. As they

are results of the work of representation, they present us something,

although it is uncertain how that something is supposed to represent

something else in the external world. Looking at the way models are

built offers also new insights into representation. Here representation

appears as a mediative activity that conveys something that is already

known or assumed, transforming it with the help of diverse

representative means. Consequently, the cognitive problem of

modelling concerns not only what is being represented but also how

that can be done. Thus in addition to depicting the multifacetedness of

parsers as epistemic artefacts, the article “From Representation to

Production: Parsers and Parsing in Language Technology” tries to

convey the flavour of the laborious work of representation that is

inherent in modelling and of the expertise that is born in the very

process.

Study 6:

Knuuttila, Tarja and Timo Honkela

“Questioning External and Internal Representation:

The Case of Scientific Models”

(in press) in Lorenzo Magnani (ed.),

Computing, Philosophy, and Cognition.

London: King’s College Publishing, (2005).

One way to put that what I have attempted to say in the previous

articles on models and representation is that the things we treat as

representations do not always act representationally and their

epistemic value need not derive from their ability to represent. Models

are a case in point. I have argued that they give us knowledge in many

ways and that they can be made to bear on our knowledge of the

world even if they cannot be taken as straightforward representations

of external phenomena. The rationale for treating models as epistemic

artefacts lies exactly in the potential of this approach to explain the

epistemic value of models without recurring to their representative

function. The target of my criticism is not representation itself, but

representationalism, which in the case of models has such a firm grip

on us that it has seemed nearly beyond doubt that models give us

knowledge because they succeed in representing something external to

themselves. This has led, as we have seen, to claims that to be a model

is to represent. In my opinion this eventually leads us to ask why we

believe that to know is to be in command of a representation that

depicts something that already exists rightly, in relevant respects or

aspects.

Why is representation so important? An answer already hinted at

is provided by the representationalist theory of knowledge, which

seems to be deeply ingrained in our epistemological thinking. Thus,

for instance, the author of a recent monograph on models and

representation does not hesitate to claim that: “Science aims at giving

us empirical knowledge. If models are to serve this purpose, they must

be representational. … They can instruct us about the nature of reality

only if we assume that (at least some of) the model’s aspects have

counterparts in the world. Hence in order to be a source of knowledge

An Overview of the Original Articles

66 Tarja Knuuttila

models must be representational.” (Frigg 2003, 19). As already noted

earlier, the roots of representationalism lie in the idea that the external

world is not directly presented to the consciousness, but only through

mental content that can be regarded as a collection of internal repre-

sentations of some kind. Thus knowledge is identified with internal

representation, which poses the question of the relationship between

internal and external representation.

In order to know how internal and external representation are

linked to each other, one would need to know what internal

representations are like and how they are connected to the external

world (including external representations). Unfortunately, there is

even less agreement concerning internal representation than external

representation. Whereas we are empirically acquainted with the

external representations we produce and use, the same is not true of

internal representation. There is no agreement as to what kind of

representations our minds house. Such being the case, the article

“Questioning External and Internal Representation: The Case of

Scientific Models” approaches the question of internal representation

by examining what can be inferred about our cognition from our

external practices of representation. Study 6 examines in particular a

special kind of model, the self-organising map (SOM), which is

approached as a multifunctional epistemic artefact. Timo Honkela, a

computer scientist experienced in building and studying SOMs, has

characterised them in this article. What gives a special twist to the

case of the SOM in the context of internal and external representation

is that it can also be used, among other things, as a model of the mind.

Thus it can be conceived of as an external representation, which

conveys us knowledge of our supposed internal representations.

However, even in this capacity the SOM, rather than being a

representation of our brains, functions as a device with which some

interesting results concerning the adaptive cognitive processes can be

shown. Consequently, it rather demonstrates and exemplifies than

really represents.

As for the question of internal and external representation, we

argue that the idea of models as epistemic artefacts finds support in

recent trends in cognitive science according to which cognition is

distributed between embodied humans and their environment. This

human environment is largely artefactual, and thus the distinctively

human kind of knowledge can be regarded as a product of our

artefactual practices (including language). Thus both external and

internal representations should be understood rather performatively

than representationally, as oriented towards action, and as parts of

complicated causal, cultural and inferential webs. This of course sets

limits on how well the notion of representation itself can be expected

to explain cognitive and epistemic processes. Our conclusion is that

the explanatory power of the representationalist paradigm is

diminishing as a consequence of such developments as distributed

cognition, which ultimately relativises the strict division between the

internal and external representation.

An Overview of the Original Articles

68 Tarja Knuuttila

5. Conclusions

It seems that the crisis of representation emerges from the uneasy

encounter of our representationalist epistemological heritage with the

observation that our representations are artificial and conventional

constructs. The conception of knowledge of the modern era has been

representationalist in the sense that correspondence with the world

“as it is” has provided the criterion for whether a representation is

true or not. From this point of view any traces of artifice must make the

representation seem less truthful and more contrived. Yet, as the

representations we produce and use cannot be but artificial,

suspicions concerning their “objectivity” start to abound. How can

our obviously constructed and media-specific representations really

stand for reality in the sense of depicting some aspects of it accurately?

The answer, I suggest, is not to doubt the artificiality of

representation but rather our representationalist convictions. As I

have argued in this dissertation, our representationalist heritage ties

together several different ideas in assuming that knowledge consists

of a collection of representations that correspond accurately to reality,

which is comprised of a fixed totality of representation-independent

objects. What I have attempted to do here is to join others in untying

the knots that are characteristic of representationalism: the conflation

of knowledge and representation, representation and correspondence,

and finally representation and (metaphysical) realism. Even though I

have been inspired and motivated by these big questions my work has

remained largely in the sphere of modelling and scientific

representation.

In this dissertation I have developed a practice-oriented artefactual

approach to models that loosens the epistemic value of models from

representation (understood in the representationalist sense). Treating

models as epistemic artefacts attributes their epistemic value to the

interplay of their material and intentional dimensions, which is due to

their being both purposefully constrained and materially defined, yet

interpretatively open things. What is new about my approach is its

stress on the materiality and artefactuality of models—properties that

have been of secondary importance for the philosophical tradition,

which values the abstract, theoretical and conceptual. From my

naturalist point of view, we do not however represent with the help of

structures or conceptual ideas alone. These ideas they have to be built

into, and with the help of, specific media, which partly determines

that what can be conveyed through models and representations.

As to the question of modelling and scientific representation, this

dissertation draws the following conclusions:

Our understanding of modelling should not be restricted to the

view that models represent some external target systems accurately.

Apart from being representative things, models are typically also

productive things whose workability and experimentability are

crucial for their epistemic value. Models can function not only as tools

and inference generators, but also as research objects in their own

right. In the capacity of inference generators models can be used as

representations. In scientific practice, however, they also function as

exemplifications, proofs of existence, demonstrations and test-beds.

Thus conceiving of models as representations loses the sight of many

of their distinctive properties. What is more, it gets the cognitive

challenge of modelling the wrong way, as it assumes that we already

knew what our relevant target systems were and had the appropriate

means at hand to represent them.

Representation can be approached both from the use and the

production points of view. Philosophical analyses of scientific

representation have so far concentrated rather one-sidedly on the use

of ready-made models. From this starting point, I have argued that

representation should be approached as a two-fold phenomenon that

is based both on the medium-specific affordances of the material sign-

vehicle and on the intentional process of relating the sign-vehicle to

whatever it is that is being represented. The fact that a sign-vehicle is

a materially constructed historical artefact leads us to consider the

complex culturally constructed artefactual chains through which our

knowledge of the world is actually mediated. As no sign-vehicle is

representative of anything in and of itself, the intentional process of

relating it to its object is needed for the representation to become

accomplished.

Treating models as artefacts makes their production processes

visible. Seen from this angle a large part of the work of representation

that is taking place in sciences is conveying into another form that

what is already represented and modelled somehow. Looking at

representation from this point of view stresses the methods,

ingredients and various representative devices that are needed in

producing models. The production point of view on representation

Conclusions

70 Tarja Knuuttila

seems to me an important complement to the use point of view. It

shows how any ready-made model is already a complex

representative achievement in itself and not an isolated theoretical

entity. I think that this has a certain sobering effect: one needs not be

puzzled about what connects the model and its supposed target

system since the model is from the very outset a result of various

procedures of connecting. Thus representing lies indeed at the heart of

the modelling enterprise, but not where it has been conventionally

taken to be.

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Full-text available

Jan 2017

Ausgangspunkt und Zielsetzung des Beitrags ist die Notwendigkeit eines medienpädagogischen Perspektivwechsels vom Einsatz von Medien im Unterricht zur Kultur der Digitalität, bzw. kollektiven Praktiken. Theoretischer Bezugspunkt ist ein Verständnis der Digitalisierung aller Lebensbereiche unter Bezugnahme auf praktiktheoretische Überlegungen, bzw. Theorien sozialer Praktik. Durch den Perspektivwechsel ergeben sich mindestens die drei im Weiteren näher ausgeführten Fragestellungen/ Forschungsschwerpunkte: (1) Das Individuelle und das Kollektive: Wie bedingen individuelle und kollektive Medienpraktiken einander? (2) Digitalisierung und Bildungsinstitutionen: Die handlungstheoretische Weltinterpretation bildungs- politischer Akteure und die Idee der Generalisierung von Praktiken trifft mit Wucht auf die Kontingenz und Immanenz medialer Praktiken (3) Mensch und Algorithmen: Wie verhält sich Mensch und Algorithmus sowie Struktur und Praxis zueinander? (4) Bildung als gestaltende Auseinandersetzung mit Unbestimmtheit: Welche Implikationen ergeben sich für den (Medien-)Bildungsbegriff. Der Beitrag endet mit der Feststellung, dass Medienpädagogik unter dieser Perspektive und mit dem Bezug auf Materialität, Unbestimmtheit und Kollektivität zentral für die weitere Exploration und Untersuchung allgemein pädagogischer Fragen wird.

Models and Theories: A Philosophical Inquiry

Book

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Jun 2022

Roman Frigg

Teorilere İlişkin Semantik Görüşün Bilimsel Temsil Anlayışı

Article

Apr 2022

Onur KABİL

Aspects and Abilities of Science Literacy in the Context of Nature of Science Teaching

Article

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Jan 2022
Sci Educ

In the last decades, science literacy has been progressively emphasised as an aim of science education. However, the science education literature does not present a consensus about both the meaning of science literacy. By studying such literature, we identified some of these aspects that may also be relevant for promoting students’ critical education. These are decision-making, critical thinking, critical positioning, and self-awareness-raising. Based on this review of the literature, our main goal has been that of discussing how these aspects could be inter-related and favour science literacy in the context of nature of science teaching. This does not mean coming up with a new ready definition for science literacy, but rather enhancing the discussion and supporting its understanding as something more complex, resulting from an intricate interaction of many components and that may be constantly promoted and developed in science lessons. Such a perspective can help teachers’ perceptions that science literacy of their students is an attainable aim, as well as encourage them to foster it.

Um caso histórico sobre a vida de Marie Curie

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Jan 2021

A atividade visa promover o desenvolvimento, por parte dos estudantes, do pensamento crítico sobre alguns aspectos de NdC a partir da história de Marie Curie. Para isto, propomos o uso de um caso histórico, uma vez que tal abordagem de ensino nos possibilita promover uma reflexão sobre alguns aspectos de NdC a partir de um contexto científico que envolve parte da história de Marie Curie. Nesta atividade, os estudantes podem refletir sobre alguns aspectos de NdC, principalmente os históricos e antropológicos (influência cultural) cuja discussão não é favorecida no capítulo anterior e, consequentemente, ampliar suas visões sobre Ciências.

A análise de um caso contemporâneo em aulas de Ciências

Chapter

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Jan 2021

Esta atividade visa promover a mobilização e/ou desenvolvimento, por parte dos estudantes, do pensamento crítico sobre e com alguns aspectos de NdC a partir da análise da tragédia ambiental que ocorreu em Brumadinho/MG. Para isto, propomos o uso de um caso contemporâneo, uma vez que tal abordagem requer o engajamento dos estudantes na discussão de uma situação-problema que envolve um contexto sociocientífico. Portanto, ao retomar tal tragédia ambiental, por meio de um caso contemporâneo, os estudantes podem refletir sobre alguns aspectos de NdC, principalmente os econômicos e filosóficos (ética), e aplicá-los na análise do caso. Isto porque o caso histórico (apresentado no capítulo 3), diferentemente deste que é de natureza argumentativa e proporciona um ambiente favorável para isto, não possibilita esta última ação (aplicação de alguns aspectos de NdC para se posicionar criticamente e/ou tomar consciência de outros aspectos, situações-problema e/ou problemas) e, consequentemente, ampliar suas visões sobre Ciências.

A introdução de aspectos de Natureza da Ciência em contextos de ensino a partir de um filme

Chapter

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Jan 2021

Esta sequência de atividades tem como objetivo introduzir aspectos de Natureza da Ciência (NdC) de maneira contextualizada e explícita em contextos de ensino para estudantes do Ensino Médio. Propomos três atividades que envolvem etapas diferentes de uma intervenção, sendo elas: (i) Atividade 1, etapa inicial, que visa favorecer a explicitação das ideias iniciais de estudantes sobre Ciências; (ii) Atividade 2, etapa principal, que objetiva introduzir aspectos de NdC de maneira contextualizada e explícita; e (iii) Atividade 3, etapa final, que visa identificar se, e em que extensão, houve uma ampliação da visão de estudantes sobre Ciências.

Educação em Ciências a partir da elaboração de modelos pelos estudantes

Chapter

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Jan 2021

Esta sequência visa promover a tomada de consciência por parte dos estudantes com relação à existência de alguns aspectos de NdC a partir da vivência de práticas científicas e epistêmicas análogas às que cientistas vivenciam ao produzir conhecimentos científicos. Para isto, propomos o uso de atividades de modelagem, uma vez que esta abordagem de ensino engloba uma série de outras práticas científicas como as relacionadas à investigação, experimentação, argumentação, entre outras, utilizadas por cientistas para produzir conhecimentos científicos.

The Mechanical Mind: A Philosophical Introduction to Minds, Machines and Mental Representation

Book

Dec 2003

Tim Crane

Being There: Putting Brain, Body, and World Together Again

Book

Jan 1996

Andy Clark

Genesis and Development of a Scientific Fact

Book

Jan 1981

KNOWING AND MAKING: KANTIAN THEMES IN HINTIKKA’S PHILOSOPHY

Article

Aug 1994

Matti Sintonen

Embodied, Situated, and Distributed Cognition

Chapter

Aug 2017

Andy Clark

Biological brains are first and foremost the control systems for biological bodies. Biological bodies move and act in rich real‐world surroundings. These apparently mundane facts are amongst the main driving forces behind a growing movement within cognitive science – a movement that seeks to reorient the scientific study of mind so as to better accommodate the roles of embodiment and environmental embedding.

The Disorder of Things: Metaphysical Foundations of the Disunity of Science.

Article