ON THE idea of a theory


Andrew Chesterman


MonAKO, Department of General Linguistics, Unioninkatu 40,

00014 University of Helsinki, Finland


[Published 2007 in Across 8, 1, 1-16.]

Abstract: This article is based on a lecture that has been given to several groups of doctoral students at various times and in various places. It outlines five notions of what has been taken to constitute a “theory”: myth, metaphor, model, hypothesis and structured research programme. The most fundamental of these is the hypothesis. These different ideas of what a theory can be are illustrated with examples from Translation Studies. Any theory aims at description and explanation, and these two concepts are also discussed. A final comment takes up the idea that translations themselves are theories, and that a translator is thus a theorist or theôros.


1. A way of seeing


The etymology of the word “theory” goes back to the Greek qewría ‘theoria’, meaning ‘a way of looking at something’, in order to contemplate it and understand it better. In this broad sense, we can say that a theory is a helpful point of view. I take (better) understanding to be the general goal of any theory. A theory of translation is thus a view of translation – or some part or aspect of it – which helps us to understand it better.

                  This is an instrumental notion of “theory”: a theory is an instrument of understanding. Good theories are useful instruments; bad ones are eventually discarded in favour of better ones. But theories are also goals or ends in their own right, in the sense that they are conceptual structures that need to be designed, formulated and tested. In other words, theories themselves are also forms of understanding. If understanding is the final goal, constructing a theory is an intermediate goal which can then serve as an instrument to that end, at the same time as it gives this understanding a form. In this context, it is useful to compare the notion of a method, from Greek meta hodos ‘after the way’. Methodology is, etymologically, the business of proceeding along  the way (hodos) to do something or to reach a goal. If a theory represents a form of understanding, methods are the ways in which one actually uses, develops, applies and tests a theory in order to reach the understanding it offers.





The general goal of understanding a phenomenon means that we need access to appropriate concepts, an ability to describe and explain, and often also the ability to predict. Appropriate concepts need to be defined, and justified in preference to other “shadow” concepts that might have been used instead but were not: i.e. the choice of concepts needs to be justified. (Compare the notion of “shadow translations”, used e.g. by Johansson 2004.) The concepts also need to be related to each other, as illustrated e.g. in the concept diagrams used in terminology. There are a great many concepts in Translation Studies (TS) which have been given competing definitions: we do not have a consistent terminology, in any language. Consider the variety of available definitions of the key concepts of “translation”, “equivalence” and  “strategy”, for instance; or the different typologies of these concepts that have been proposed (on strategies, see e.g. Chesterman 2005).

                  A description can be done from many perspectives. The linguist Kenneth Pike (1959) suggested trying at least three such perspectives: seeing the phenomenon as a particle (in isolation; and in comparison with similar particles);  as a wave (in which the phenomenon is seen as merging with other phenomena in space and time; this perspective also includes the historical, diachronic view); and as a field (where the phenomenon is related to its surrounding context). We could also look at it from a functional perspective: what use is it, what is its value? (Cf. Booth et al. 1995: 40.)

                  Explanations also come in many forms. We can explain for instance how something is possible (what are the necessary conditions?), or why it had to happen (what are the sufficient conditions?). Explanations work by showing relations of generalization, causality, or unification with other patterns of phenemona. Hypotheses about translation universals, for instance, aim to explain the occurrence of, say, explicitation in a given translation by positing a generalization: all (or most) translations manifest some explicitation, and this makes it easier to understand why this particular translation does as well, if there is indeed a general tendency. If the generalization is true, we are not surprised when we find explicitation, because the generalization offers an explanation of a kind. Causal explanations also increase our understanding of  why something happened, or why the form of something is as it is. And if we can show the relations between the explanandum (that which needs to be explained) and other phenemona, if we see it in the context of a more general pattern, we also feel we have found some kind of explanation. For instance, we can better understand why there have been several different German translations of the classic Finnish novel Seitsemän veljestä (‘Seven brothers’, by Alexis Kivi) if we look at the context of the different social and political conditions at different periods in Germany, different translators with different intentions and ideologies, different publishers, different translation norms, different German images of Finland at different times, and so on (Kujamäki 1998, 2001). These conditioning factors are all weakly causal, but, as is often the case in the human sciences, our sense of understanding here comes more from seeing the broad picture than from evidence of causality in a strict sense. To the extent that we can relate these factors within a single model, we can arrive at an explanation via unification. (On explanation via unification, see Salmon 1998.)

                  Predictions can be used to test explanations. But not all explanations imply the corresponding ability to predict. However, even if precise predictions are not possible, an explanation reduces our surprise that the phenomenon in question has occurred, and perhaps allows us at least to anticipate other occurrences in future. An explanation thus allows us to “make sense” of something. (For further discussion of this general theme, see e.g. Chalmers 1999.)


3. Kinds of theory


It is helpful, I suggest, to distinguish five types or notions of theory. I outline them here. Examples from Translation Studies follow below.

                  Some of the first theories were myths: they were symbolic narratives which offered some way of “making sense” of something mysterious. “We are meaning-seeking creatures,” writes Karen Armstrong (2005: 2); “[...] from the very beginning we invented stories that enabled us to place our lives in a larger setting, that revealed an underlying pattern [...]”. Think of the many myths of creation, in different cultures, for instance. Or the 20th-century Gaia myth which invites us to see our planet as a living organism. A myth can have enormous effects on a person or a society.

                  Theories can also take the form of metaphors or similes. To see something strange as something more familiar (or as being like something more familiar, or as a kind of something more familiar) is one way of making sense of it. Physicists have learned to see light, for instance, as particles; or as waves; or, nowadays, as both at the same time. “Metaphor is one of our most important tools for trying to comprehend partially what cannot be comprehended totally,” say Lakoff and Johnson (1980: 193). But a metaphor only sheds light on one side of a phenomenon: every metaphor also hides what it does not highlight. We do not see the dark side of the moon.

                  Myths and metaphors are often said to represent the kind of knowledge which Plato called mythos, as opposed to logos. Mythos is the form of knowledge that is symbolic, intuitive, figurative, imaginative; logos is rational, explicit.

                  Scientific theories often involve metaphors and myths, but they typically aim to be more explicit, based on evidence, and empirically testable. One kind of scientific theory is a model, which seeks a relation of similarity with whatever it is a model of. Models represent what are taken to be the main elements of a phenomenon, their main functions, and the main relations between the elements. Think of models of our planetary system, before and after Copernicus. Or models of the brain (like the model of the brain as a black box, with input and output); or models of cognitive processes (decision-making, for instance, is sometimes represented as an algorithm of yes/no choices, a view which is implicitly based on the metaphor of the mind as a computer).

For some philosophers, theories are seen as hypotheses. A hypothesis is, roughly speaking, an educated guess at the best answer to a question, based on the most reliable facts available. Popper’s general model (sic!) of scientific progress centres around the idea of generating and testing hypotheses (e.g. Popper 1959). To solve an intitial problem, a tentative theory (a hypothesis) is proposed, then this is tested (the stage of error elimination), and the result is usually a new problem; and so the process continues. The original invention of the idea of a hypothesis has been a major step in the development of the scientific method, because it means that empirical claims need to be tested against evidence rather than believed on the basis of the authority of the claimer, or on tradition, or on intuition alone.

There are various basic types of hypothesis (illustrations coming below).


Descriptive hypotheses: all Xs have feature F / belong to class Y.

Explanatory hypotheses: X is caused by / made possible by, Y; Y explains X..

Predictive hypotheses: in conditions ABC, X will (tend to) occur.

Interpretive hypotheses: X can be (usefully) interpreted as Y.


The first three types are self-explanatory; they are all empirical hypotheses. Predictive hypotheses are used to test (some) explanatory ones.

Interpretive hypotheses have a different status from the other types, because they are not tested directly against empirical evidence (are they true?) but against pragmatic criteria (are they conceptually useful, insightful?). My claim that there are five types of theory, for instance, is this kind of hypothesis. I find it useful, as a way of clarifying the picture. But if someone proposes a competing hypothesis – say, that it makes more sense to classify types of theory into seven, or seventeen groups – we simply have to see which classification seems more useful, which “catches on”, which gives rise to better research. Interpretive hypotheses are nevertheless an integral part of doing science. All definitions and classifications, for instance, are based on them, not to speak of data interpretion. If birds and dinosaurs are classified as belonging to the same zoological class, we shall probably “see” them rather differently than we would otherwise. Do you define a tomato as being a fruit or a vegetable? Is Pluto a planet nowadays or not? Alternative classifications illustrate the enormous variety of ways in which we human beings can conceptualize our world (for a classic study, see Lakoff 1987).

                  My fifth type of theory is the structured research programme. This view is argued for especially by Lakatos (e.g. 1970). Such a theory has two main components. At the centre, there is a “hard core” of fundamental principles and assumptions which are not questioned within the programme but taken for granted (although they may be questioned by people outside the programme). Outide this core, there is a “protective belt” of supplementary assumptions and hypotheses to be tested, protecting the hard core.

                  Of these five types of theory, the hypothesis is the fundamental one. Myths and metaphors can be seen as interpretive hypotheses, to be tested in use. Models are hypotheses too, to be tested against evidence; and the same can be said of the cluster of hypotheses and assumptions which make up a research programme: you try them out, and if they do not work adequately, you eventually try something else.

                  Let us now look at how these kinds of theories are represented in Translation Studies.


4. Myths of translation


In the West, the dominant myth of translation is the Babel myth (Genesis 11). This myth has had major consequences for our perception of translation. We see it as tainted by the Fall from the Paradise of perfect communication, by failure; it is always second-best, never as good as the original; and so on.

                  But we do not have to see translation through the eyes of this pessimistic myth. In the East, apparently, translation can be seen in terms of the myth of metempsychosis, or the transmigration of souls (Devy 1999). It can thus be associated with the idea of rebirth, spiritual progress: as a soul returns to live again in a new body, so a text may be born again in a new language, and perhaps in a form that is in some way better than its previous existence. This is rather a more optimistic view, looking not at what is lost in translation but what might be gained. Traces of this alternative myth can also be found in Renaissance writings on translation in the west, as when translators are described as having some spiritual affinity with their authors, as if the two had a shared soul (Hermans 1985b: 127).


5. Metaphors of translation


The history of Translation Studies is full of metaphors and images of translation. Here is a selection from the Renaissance period in Europe, all having to do specifically with literary translation (paraphrased from Hermans 1985b, where exact sources are given).


Translation is (like) imitation.

The translator is like a painter who shows a person’s body but not his soul.

The translator digests the original, turning it into blood and food.

To translate is to follow in the footsteps of the original.

A translation is the rival of the original, striving to beat it at its own game.

The translator is the servant or slave of the original.

A translator is a magpie among peacocks (i.e. trying to look like a peacock but failing).

The translator is like Phaeton, who wanted to drive the chariot of the sun and was punished for his presumption (i.e. if he dares to challenge the mastery of the original).

A translation is the echo of a song.

A translation offers false pearls in place of diamonds.

A translation is like the reverse side of a tapestry.

A translation is a plain garment (whereas the original is a rich cloth).

A translation is like candlelight compared with the sun.

Translations are shadows of beautiful bodies.

Translation opens windows to let in the light.

The translator brings treasures which were hidden in the earth.

A translation is a jewel in the rough casket of language.

Translating is like pouring a precious liquid from one vessel into another.


Such conceptualizations reveal implicit theories about translatability, the relation between meaning and form, translation equivalence and translation quality.

My own preferred metaphor is from memetics (Chesterman 1997). I find it interesting to see translations as ways of carrying the evolution of ideas (memes) from one culture to another, like biological organisms carry the evolution of genes. Translations help memes to survive and spread. This metaphor thus allows me to see translation within the framework of cultural evolution.

                  Translation has also been seen as a kind of something else which is more familiar: as a kind of rewriting, for instance (Lefevere 1992). This placing of translation under the more general term highlights its similarities with other kinds of rewriting, such as paraphrasing, summarizing, or anthologizing (and correspondingly downplays other kinds of similarities). Sometimes there are serious disagreements about these hierarchies. There is currently some debate about whether translation is a kind of localization, or whether localization is a kind of translation (see e.g. Pym 2004). To some extent such interpretive hypotheses are expressions of power and status: if translation is the higher term, it seems to be more important, and localization is demoted to being a mere type of translation. And vice versa. So the debate is partly an institutional, territorial one, with consequences concerning research funds, jobs, salary levels and so on.


6. Models of translation


I have elsewhere (Chesterman 2000) distinguished three types of models used in Translation Studies.

                  Comparative models show translations in a relation to other texts, which may be

• source texts (> the equivalence relation),

• non-translated comparable texts in the target language (> the naturalness relation),

• other translations (> research on translation universals), or

• non-native texts, learners’ texts.

Examples of comparative models are those developed by e.g. Catford, Koller, Vinay and Darbelnet; those based on contrastive research; and corpus-based work on translation universals. Catford’s model (1965) is based on an analysis of the various kinds of relations holding between source texts and translations, on his theory of equivalence and his classification of types of shift. An equivalence typology also lies at the centre of Koller’s model (1979); he distinguishes denotative, connotative, text-type, pragmatic and formal types of equivalence. Vinay and Darbelnet (1958) were primarily interested in the contrastive syntactic and rhetorical differences between English and French, and proposed a number of “procedures” as ways of conceptualizing the kinds of changes that translators make when moving from one language to another. For instance, the procedure of “transposition”, which involves changing the word class. Although Vinay and Darbelnet framed their procedures in dynamic terms, these are usually seen as ways of conceptualizing the results of these various procedures. What we see, empirically, is the result of a change of word class, for instance, when a verb in English is translated as a noun in French.

With the advent of corpus methodology, scholars began looking empirically at other kinds of relations. Translations into, say, English can be compared to matched (i.e. with same subject matter and text type, etc.) non-translated texts originally written in English, in order to see whether there are systematic differences between the two corpora. In other words, we can measure the naturalness of the translations. We can also compare translations into English with translations into other languages, from a variety of source languages, and see whether we find evidence of recurrent features (universals?) of the translations, regardless of language or text-type, which might therefore be due to the translation process itself. (Examples will be given below of some claims that have been made as a result of such research.) We might also want to compare translations to texts produced by non-native speakers: perhaps the effect of the extra constraint of the translation situation is similar to that of having to produce a text in a non-native language.

In all versions of these comparative models, then, we are dealing with two sets of texts and looking at the relations between them. The relations are basically static and contrastive.

                  Process models, on the other hand, represent the temporal sequence of stages in the translation process, either at the cognitive level of translation decisions, or the sociological level of working procedures. An early and influential process model was the one proposed by Nida (e.g. 1969). He suggested that translation was like crossing a river (note the image!), but added that a translator does not actually cross at the point where the source text is. The translator first analyses the source text (reduces it to a simplified form, i.e. looks for an easier place to cross the river), then makes the transfer to the target language, and then “restructures” the translation, which means stylistically polishing it so that it corresponds to the stylistic profile of the original and to the expectations of the audience. He thus modelled the translation process in terms of the three stages of analysis, transfer and restructuring.

                  Other scholars have modelled the process differently. Sager (1993) bases his analysis on four working procedures: specification (understanding the client’s instructions, checking that the brief is appropriate and feasible); preparation (finding the necessary resources, terminology, and so on); translation; and evaluation (revision). Nord (1991: 32f) argues for what she calls a looping model. Here, step one is analysis of the translation skopos; step two is analysis of the source text; and step three is the production of the target text. Nord calls this model a looping one, because it illustrates the way in which the translator continually loops back and forth between the three elements of the model: skopos, source text analysis and target text synthesis. This model is thus more complex than a linear one going directly from source to target.

                  Process models are also evident in cognitive research using think-aloud protocols (TAPs), where the aim is to model the translator’s decision-making process (for surveys, see e.g. the special issues of Across Languages and Cultures 3, 1, 2002; and Meta 50, 2, 2005). Work using the TRANSLOG program also tracks the translation process: here, the computer records the translator’s every key-stroke against a clock, producing a time record of the translator’s typing actions. When this is combined with a think-aloud protocol and perhaps a video recording, and a retrospective interview, we can arrive at a fairly detailed picture of the observable translation process and make some inferences about what happens at the cognitive level. (For some recent TRANSLOG work, see Hansen 2002 and other papers in the same volume; and Hansen 2005.)

                  On a much larger time-scale, a process model also underlies work on translation history. Here, though (as also with some of the cognitive research) there is an overlap with causal models, in which the focus is not only on the temporal relation of what came before or after what, but on the cause-and-effect relation.

                  Causal models, in their simplest form, look like this:


Causal conditions   >  Translations   >  Effects


Translations themselves are both the result of preceding causal conditions and themselves the cause of consequences. These consequences may range from acceptance or rejection of the text by the client, or feedback from critics, to major cultural developments. Think of the role played by translation in the history of science, for instance. In the human sciences, however, causality can seldom if ever be represented as a simple linear chain. What we usually find is a whole complex of factors and contributory conditions, some of which are more powerful than others, and many of which also affect each other. In a very broad sense, the causal conditions of translations range from the cognitive to the socio-cultural. The immediate cause of a given word in a translation, for instance, must be that the translator decided to write that word: the proximate cause is cognitive. But we can continue asking “why?”. Perhaps he made that decision because of his working conditions (a bad dictionary? not enough time?). Why were the conditions like that? (The client didn’t care? The client chose a poorly qualified, cheap translator?) What are the norms for that kind of translation task in that culture? What are the underlying values and ideologies? And so on – the questions never end, but answers to them can contribute something to our wish to understand “why” something occurred in this translation. Similar lists of questions can be made for other starting-points. Why, for instance, did a given translation have such-and-such an effect on the client / on the readers / on society / on cultural development as a whole?

                  Causal models are used explicitly in several current theories. Skopos theory, for instance, assumes as axiomatic that the single most important cause of the form of a given translation is (or should be) its skopos, its purpose. (See e.g. Vermeer 1996, Nord 1997.)

Scholars who have applied relevance theory to translation, on the other hand, propose that the fundamental explanatory cause is the principle of relevance itself. Roughly speaking, this is defined as the cost-benefit relation between the reader’s effort to understand (= cost) and the cognitive effects the message has (= benefit): the more benefit and less cost, the more relevance; and speakers are assumed to aim for optimal relevance. Relevance theory claims to offer a cognitive explanation for why people communicate as they do (and also why they translate as they do, since translation is seen here as being simply one form of the interpretive use of language, i.e. like reported speech). (See Gutt 2000.)

Norm theory takes a different view of causation, looking more broadly at the socio-cultural conditions and norms, including for instance the translation tradition in a given culture, which affect translator’s decisions. (A classic source is Toury 1995.) In translation training, translators are typically socialized into the current norms in their society; but not all translators receive formal training, and need to pick up the norms in other ways. Norms are based on values, which in turn lead us to translation ethics: a translator’s professional ethics also affect his decisions about how to act as a translator. Reception studies (also represented in Kujamäki 1998, cited above) also use a causal model to analyse why a given translation had a given effect.

From this point of view, it is evident that all work on translation quality has an underlying causal model, too. This is apparent in translation quality control, where checking and documentation of procedures aim at assuring the quality of the various stages of the translation process, on the assumption that if the process is OK the resulting product will also be OK. (See e.g. the new CEN standard for translation services, EN 15038: 2006, e.g. via <www.cen.eu>.) It is also apparent in quality assessment, whether during training or in working life. A given translation fails, or is rejected by the client, because it has given defects; in other words, it causes a negative effect on someone. One could even say that research on machine translation uses an implicit causal model: if the aim is to produce a better automatic translation program, the focus is on adjusting the program to produce an optimal-quality result – you vary the causal conditions and check the effects.


7. Hypotheses of translation


Interpretive hypotheses abound, of course. All operationalization decisions are based on them. An example might be a decision to interpret the concept of translation quality, in a given research project, as “grades from 1 to 5 given by translation trainers using a matrix of defined error types and weightings”; as opposed for instance to “impressionistic grading by peers” or “acceptance or rejection by the client”.

                  Descriptive hypotheses have come much more to the fore with the interest in corpus studies on translation universals, mentioned earlier. All claims about universals are descriptive hypotheses. A well-known example is the explicitation hypothesis, that translators tend to make explicit what was only implicit in the source (originating from Blum-Kulka 1986). Another is the law of increasing standardization, that translations tend to use a more unmarked style than their source texts (Toury 1995). A third example is the claim that translators tend to reduce repetition. (For a recent selection of work on these hypotheses, see Mauranen and Kujamäki 2004.) Yet another well-tested example is the retranslation hypothesis, that later translations of a given text into a given target language tend to be closer to the source than its first or earlier translations. This hypothesis does not seem to be finding much confirmation (see most recently Brownlie 2006).

                  Explanatory hypotheses are also common, but have so far tended to refer to individual case studies. A given translation, it is argued, has particular features because of a number of given factors. Brownlie (2003), for instance, proposes the following factors which seem to explain much of her material: the individual situation and context of production, including the translator’s attitudes; the conditions determining the textuality of a translation, the way it is subject to different textual and intertextual constraints; translators’ norms; and the effects of intersecting fields such as publishing and academia (in the case of academic texts). An example of a more general explanatory hypothesis is the claim that translators tend to start their mental processing with a literal translation: the literal translation hypothesis. This would explain the progression from more literal towards freer versions evidenced in studies of the revision process, where the analysis focuses on sequences of interim draft solutions (e.g. Englund Dimitrova 2005). Another explanatory hypothesis has emerged from TAP research: that the quality of a translation can (sometimes) be (partly) explained by the translator’s mood and emotional state (see e.g. Jääskeläinen 1999).

                  Predictive hypotheses are less common in Translation Studies, where experimental research is not widespread. (It is more usual in Interpreting Studies: see e.g. Pöchhacker 2004.) One example is the claim (or assumption?) that if a translator has more time the translation will be of a better quality. This is an idea that has been challenged at least by Hansen (2002). Implicitly, of course, every translator proposes a predictive hypothesis when he or she delivers a translation: the prediction is that the client will accept it as a good (or at least adequate) translation; and the test is the reaction of the client.

                  Formulating a hypothesis explicitly is crucial. There is a big difference between e.g. “translation shapes the formation of cultural identity” and “translation reflects the formation of cultural identity”. The first is an explanatory, cause-and-effect hypothesis, which suggests that translation is a (presumably contributory) condition of cultural identity formation. It is presumably not a necessary or sufficient cause, however. And precisely when translation would be a contributory condition is not made explicit in this formulation. The second formulation is an interpretive hypothesis: translation can be interpreted as reflecting cultural identity formation. Anyone wishing to disagree would need to counter-argue that, in their view, translations are more usefully regarded as signs of something else, or that some other signs of cultural identity formation are more important.

                  Good empirical hypotheses are testable against evidence; they are internally coherent, simpler or more powerful than competing hypotheses, bring added value, and raise new questions and hypotheses.

                  It is a good idea either to start a research project with a hypothesis (better: a pair of contrasting hypotheses), or else end with a claim that can function as a hypothesis to be tested in  a future research project.


8. Structured research programmes (?)


We can find some examples in TS which seem to be structured research programmes in Lakatos’ sense, but perhaps only to some extent. Polysystem theory, for instance, has a set of “hard-core” assumptions, including the following (from Hermans 1985a). We can analyse cultures in terms of polysystems, i.e. systems of systems. A system is a structured complex of elements that can be distinguished from its environment. Systems can be identified, but they are not static; each system has a centre (e.g. of canonized forms) and a periphery, and it has  conservative and innovatory elements, which are in a constant state of flux. Within a polysystem, different systems and subsystems struggle for central status. One such system is that of literature, which itself contains other systems, such as genres. Translations show what can happen at the interface of systems; they can be part of the centre or of the periphery. Perhaps the most innovative and provocative assumption in polysystem theory is that all translation involves some manipulation, for a given purpose, such as the intended function of a translation in the target system. – Research based on these assumptions has given rise to a large number of descriptive case studies, but general empirical hypotheses have not been much in evidence, with the exception of general claims about the ubiquity of interference.

Corpus research on translation universals could also be said to share some basic assumptions, such as the idea that features specific to translations are worth seeking in their own right, not as evidence of poor translations; that translations constitute a text-type of their own, a “third code”, neither source nor wholly target; that we have a (potentially) universal concept of translation available which can apply to all cultures and all ages; and that there is some reliable way of deciding what translations to include in a corpus and what to exclude (for instance on the parameters of professional vs. amateur, native vs. non-native, or even good vs. bad: after all, a bad translation is still a translation, of a kind...). (For some criticism of these assumptions, see Tymoczko 1998.) The empirical hypotheses are then the various claims about possible universal features, referred to above.

                  One lesson we can draw from this view of a theory is the importance of distinguishing between what is assumed, what is being asked or tested, and what is finally being claimed. Assumptions can be challenged, and hidden assumptions can be exposed. Hypothesis-testing procedures and operationalization decisions can also be challenged. And claims may be met with counter-evidence and counter-claims, or suspected of being illogical. The difference between assumptions, hypotheses and claims is thus a question of their status in a given research project, not of their propositional content as such.

                  But there is certainly not one shared paradigm in TS, which would allow the development of a single research programme covering the whole field. (See the Target debate, starting with Chesterman and Arrojo 2000.) We share very general aims – to understand translation and the significance of the work of translators – but we do not all work with the same sets of concepts, nor even the same types of data. The lack of a single shared paradigm is also reflected in our heterogeneous methodologies. (See Gile’s provocative division between the Empirical Science Paradigm and the Liberal Arts Paradigm, on the EST website at http://www.est-translationstudies.org/  > Research issues.)


9. Contributing to theory


The five types of theory I have outlined are not mutually exclusive. By this I mean that a given research project may make use of different types. It might use a causal model and propose or test an explanatory hypothesis, within a broader structural framework of other assumptions and hypotheses, for instance. Or it might focus on a descriptive hypothesis framed in a comparative model and formulated in terms of a striking metaphor. One way of contributing to theory is indeed to show the relations between different existing theories and theory-types, and thus try to develop a still more general theory.

One can also contribute to theory in other ways. By providing new data (in order to test existing theories), for instance. Or by offering a better interpretation of existing data; by clarifying and relating concepts and assumptions. Or by proposing a better model or a new hypothesis. Or by testing or refining a given hypothesis, or proposing a  new way of testing one, a new methodology. In other words: one can contribute by suggesting a new or better answer to an interesting question, by pointing out a new path which might lead to a better answer, or by raising a new interesting question or problem.

Ultimately, the aim (as I see it) is to link various substantiated claims in terms of more general laws, in the same field or in other fields, in steps towards the possible unification of knowledge: consilience.


10. A translation is itself a theory


This final comment is really only a footnote. I suggest that a translation itself can be seen as a theory of how the source text can be translated, in all the five senses outlined above.

It usually represents the source text as a linear narrative, like a myth.

It is usually taken “to be” metaphorically the source text (etymologically trans-late = meta-phor). When I say ‘I have read Tolstoy’ (albeit in English translation), I am not lying, for my War and Peace “is” the Tolstoy novel.

A translation usually models the source text isomorphically, both holistically and in terms of its parts.

It constitutes a hypothesis about the source text, about how it can be interpreted, usually about its meaning. A translator implictly makes a claim that his translation is equivalent in some relevant way to the source text, a claim that is tested by the reception of the translation by clients, readers and perhaps critics (cf. Pym 1995).

And the whole process of translating is like a structured research programme, with a clearly defined problem to be solved, a set of assumptions (such as translation norms), and a multitude of individual hypotheses to be tested, for each segment of the text.

                  So translators theorize all the time (see also Pym 1992). But they theorize also in a deeper sense. As Carol Maier (2006) suggests, the translator is a theôros, i.e. a person who makes a “journey” in order to seek knowledge, a better way of seeing; perhaps even wisdom. Maier writes (168-9): “the traveller witnessed things and events with which he was unfamiliar. To see, then, in this context was to theorize. [...] Moreover, to theorize those unfamiliar things was to be affected by them, to be moved to wonder.” This wondering contemplation takes us to the very roots of philosophical enquiry.




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