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Translational Behaviour at theFrontiers of Scientific KnowledgeMark Shuttlewortha

a Imperial College London, UKPublished online: 21 Feb 2014.

To cite this article: Mark Shuttleworth (2011) Translational Behaviour at the Frontiers ofScientific Knowledge, The Translator, 17:2, 301-323, DOI: 10.1080/13556509.2011.10799491

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The Translator. Volume 17, Number 2 (2011), 301-23 ���N �7�-1-�0�7�3-27-� ���N �7�-1-�0�7�3-27-�

Translational Behaviour at the Frontiers of Scientific KnowledgeA Multilingual Investigation into Popular Science Metaphor in Translation1

MARK �HUTTLEWORTHImperial College London, UK

Abstract. This study is based on an analysis of 1354 translated metaphor examples drawn from a corpus consisting of the official published translations into French, Italian, German, Russian and Polish of 62 �cientific American articles that appeared between January 2003 and July 2004. It investigates what happens to metaphor in scientific discourse when translated into another language, on both micro- and macro-levels. Since one of the main advantages of a data-rich multilingual study of this kind is that it can potentially produce results that allow us to draw conclusions about this aspect of scientific translation at a high level of gener-alization, particular attention is paid to tendencies that appear to be common to translators regardless of the target language. The study distinguishes between macro-level mappings and micro-level metaphorical expressions and examines individual mappings and clusters of mappings in the English source text and their renderings into all five languages. It adopts a bottom-up approach, in that all mappings and other high-level structures are posited on the basis of the metaphorical expressions identified rather than trying to fit the metaphorical expressions into a pre-determined framework of categories.

Keywords: Metaphor; Scientific American; English; French; German; �talian; Polish; Russian.

This article reports on part of a larger study that involves a multi-parameter analysis of a corpus of English popular science texts and their translations into a number of European languages. The investigation takes place on two levels of generality – those of the individual metaphorical expression and the

1 � should like to thank Professor Charles Drage and Professor Kirsten Malmkjær for their invaluable comments on this article at various stages in its development. �t goes without saying that any shortcomings are entirely my own responsibility.

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metaphorical mapping – and seeks evidence as to whether modifications to a higher-level metaphorical structure all tend in a particular direction (‘shifting’) rather than pointing in conflicting directions (‘scattering’). This should in turn provide a provisional answer to the question of whether metaphor translation poses a problem in popular scientific texts.

More specifically, the methodology involves examining relatively large vol-umes of data on a global level and from a wide range of angles, using numerical techniques where necessary, in the hope that each successive view will throw a different aspect of the data into relief and reveal a different set of insights. �dentified features are investigated and interpreted in the light of the choices available to the translator. As is the case with research into translation-specific patterning, the motivation for most of what follows is very much that of iden-tifying types of translator behaviour that are consistently attested irrespective of the particular language pair involved.

1. Metaphor

The approach to metaphor taken in this article is broadly in line with what is known as conceptual metaphor theory. This was first proposed in its current form by Lakoff and Johnson (1��0), since which time it has been considerably developed both by these authors (Lakoff 1��7a, 1��3, Johnson 1��7, 2007, Lakoff and Johnson 1���, Lakoff and Turner 1���) and by scholars such as Gibbs (1��4) and Kövecses (200�, 2010). According to those who subscribe to this approach, a metaphor can be thought of not as an isolated figurative expression in a text, but as a ‘mapping’ from one domain of experience onto another – a kind of mental connection made between two unrelated concepts or areas of experience that allows one to think and talk about one of these concepts or areas in terms usually reserved for the other and that potentially sanctions an open-ended number of individual ‘metaphorical expressions’ relating to that particular area (Lakoff 1��3:203, Evans and Green 200�:2��). A mapping can be highly specific to a particular context or even a single word (e.g. ‘when to start sheathing those axons’ implies the mapping an axon is a sword); 2 or it may be more productive, as is the case with most of the mappings to be examined in this article. The distinction between macro-level mappings and micro-level metaphorical expressions will be of central importance in what follows.

Within this view, metaphor is generally seen as a means of explaining dif-ficult, unusual or abstract concepts. Normally, the less familiar is modelled in terms of the more familiar, as in ‘unneeded synapses get pruned’, where neurons are depicted as trees or plants. �imilarly, the more abstract concept is

2 � follow the convention here of marking all mappings in small capitals. � also use bold to indicate the metaphorical elements in an example and underlining to show where these are replaced by non-metaphorical renderings.

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modelled in terms of the less abstract, as in ‘artificial genetic letters’, where genetic material is portrayed as if it were text. The fact that this mapping exists for genetic material does not preclude other mappings being used in parallel, and indeed other examples in the corpus under examination model this concept in terms of circuitry, code, data, instructions, language, machinery or software. Each member of this ‘cluster’ of mappings highlights certain characteristics attributed to genetic material and conceals others, depending on the author’s particular communicative purpose. �n addition, a mapping tends to be par-tial in nature (Kövecses 2010:103), as many aspects of it generally remain undeveloped. While most metaphors conform to this pattern, one category, known as image metaphors, does not. Very little has been written on this type of metaphor (Lakoff 1��7b, Caballero 2002, 2003), in which the mapping is not between domains, but between images – as in portraying a bulbous axon terminal as if it were a bud, or a cell-free void as if it were a highway divid-ing two areas of burning forest. �n other words, the underlying mapping of an image metaphor is generally based on similarities of appearance.

Conceptual metaphor theory in the form in which it is propounded by Lakoff and Johnson tends to play down the extent of interlingual variation in metaphorical patterns motivated by linguistic or cultural factors, a weakness that became more pronounced over the course of the first twenty years of the theory’s development (Engstrøm 2000:2��). �nstead, the emphasis is gener-ally laid on what is termed embodiment, or what is argued to be our cognitive system’s dependence on our bodily experiences in forming the categories by means of which we make sense of the world around us (Kövecses 2010:107-20). One of the main insights of conceptual metaphor theory is consequently somewhat at odds with some of the conclusions that have been reached by translation scholars over the last two decades: while most conceptual metaphor theorists emphasize the universality of metaphor, the notion of interlingual and intercultural variation is part of the lifeblood of translation studies. That said, a number of writers continue to draw on at least some of the method-ologies and concepts of conceptual metaphor theory while recognizing that language and culture are vital factors in determining metaphor use (Gibbs 1���, Dobrovol’skij and Piirainen 200�, Kövecses 200�, 200�). �t is this ‘extended’ version of conceptual metaphor theory that is adopted in this article.

1.1 Metaphor in translation

�ince the discussion of metaphor in translation was initiated more than forty years ago by Kloepfer (1��7), a number of important debates have been pur-sued. Among the earliest of these were the extent to which metaphor constituted a problem for translators (whether there was ‘no problem’ or ‘no solution’; Dagut 1�7�:2�) and the fallout from Kloepfer’s controversial remark that “the bolder and more creative the metaphor, the easier it is to repeat it in other lan-guages” (1��7:11�, cited in �nell-Hornby 1���:�7). �esides this, many writers

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(for example, Newmark 1���:304-11) have proposed lists of procedures for translating metaphor – reproducing the original image, replacing the metaphor with a simile, converting it to sense, etc.

An interesting experiment conducted by �nell-Hornby in the 1��0s focused on the simile chosen by groups of her German- and English-speaking students to fill a gap left in a German-language newspaper article describing the way in which Catholic and Protestant communities in �elfast are arrayed around the city centre (1���:��-�0). Almost unanimously, the German-speaking group correctly supplied the word that had been removed. On the other hand, when asked verbally most English speakers opted for a strikingly different alternative, but then chose a literal rendering when translating the text into English. This highlighted the inherent tension between what native speakers consider to be the correct situational equivalent in their target language and what often ends up appearing in a translation because of the influence of the source text (ibid.).

�n the mid 1��0s, Mandelblit observed that the treatment of metaphors in translation studies was “thoroughly at odds with the findings of the Cognitive Linguistics research on metaphor” (1���:4��). Thereafter, scholars interested in metaphor in the context of translation have sought to draw increasingly systematically on the insights of that discipline. �nteresting work that has sought to incorporate concepts and insights from cognitive linguistics includes Dickins (200�), who proposes not one but two detailed models for describing metaphor in translation. Revised lists of translation procedures, now based on categories derived from metaphor theory, have been elaborated not only by Mandelblit (1���) but also, more recently, by Al-Harrasi (2001), �chaeffner (2004) and Papadoudi (2010). There is clearly great scope for further interac-tion between the two disciplines.

2. Scope of current study and parameters of analysis

The current study is based on an analysis of 13�4 examples of translated meta-phorical expressions drawn from a corpus consisting of the official published translations into French, German, �talian, Polish and Russian (appearing in Pour la science, Spektrum der Wissenschaft, Le Scienze, Świat nauki and V mire nauki, respectively) of �2 Scientific American articles that appeared between January 2003 and July 2004. Scientific American is a monthly popular science magazine that publishes original articles written by research scientists. The fact that an English-language journal should be so widely translated reflects the de facto position of English as the global language of science.

Although much of the content of the various international editions is a fairly direct translation of the original English-language material, the exact relationship between source and target texts varies from one language edition to another, some being almost cover-to-cover reproductions of the original edi-tions, and others adding significant amounts of new content and implementing a range of other changes. �imilarly, on the micro-level we see a wide range

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of shifts occurring between �T expressions and their various TL equivalents. No style guides or internal instructions for the translators were made available for the different international editions, despite my request to be given access to any such documents. � therefore have no direct information regarding the editorial policies or projected readerships of the various international editions, although some – such as an apparent German tendency to paraphrase and re-organize and a French inclination to abridge – can be inferred in broad terms by studying macro- and micro-level changes. Furthermore, no information about the translators is available over and above what could be discovered from the pages of the magazines themselves. Each issue of the �talian edition gives the names of around three to five individual translators and attributes to them the particular articles they have worked on. The German edition lists between four and seven translators in each issue but gives no indication of how the various articles were apportioned. A single translator – the same person in each issue – is identified for Polish, under the heading ‘Translators, Authors and Consultants for the Current �ssue’, although because of the way in which the information is presented it is quite possible that other people also con-tribute to the translation work.3 No information about translators is provided in the French and Russian publications. Consequently, it is only possible to piece together a partial picture of the numbers of translators working on the various language editions: nine for �talian, more than forty for German, but an unknown number for the other three languages. These numbers are reflected in the trends analyzed below. On the other hand, most of the examples presented are drawn from the work of only two �talian and up to four German translators, and presumably a similarly small number for the other languages.

Scientific American articles have been the subject of several studies (Rey 2000, �owker and Pearson 2002, Hoorickx-Raucq 200�, �harkas 200�, Liao 2010) and offer a rich resource in terms of the quantity of material and the number of target languages covered. The choice of specific target languages in the current study was determined in the first instance by the fact that these are all languages of which � have some knowledge. Like the source language, all five TLs belong to the �ndo-European family of languages, although within this broad grouping they represent a reasonable degree of diversity, not only in terms of their ‘proximity’ to English but also, for example, by virtue of the different resources that they use to form their scientific terminology (e.g. ancient languages vs. modern word-forms) and the impact that this has on the transparency of many metaphors.

The process of identifying metaphorical expressions is fraught with diffi-culties. �n many cases it is no easy matter to decide whether or not a linguistic expression possesses a metaphorical meaning. For instance, is a population of glial cells being referred to in terms of a human ‘population’? When cocaine

3 �ndeed, it is almost inconceivable that a single person could undertake the entire transla-tion effort single-handed.

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targets the brain’s reward system are we witnessing a (very slight) figurative extension of meaning? The corpus contained a scattering of such marginal instances. �n general terms, if a usage contrasts with a “more basic contem-porary meaning” – one that is more concrete, related to bodily action, more precise or historically older (Pragglejaz Group 2007:3) – the expression is considered metaphorical, although in making this judgement a certain element of subjectivity is inevitably involved.

The process of metaphor identification adopted in the current study is broadly in line with the ‘Metaphor �dentification Procedure’ proposed by the Pragglejaz Group (2007:3). The approach is bottom-up, in that all mappings and other high-level structures are posited on the basis of the metaphorical expressions identified rather than trying to fit the metaphorical expressions into a pre-determined framework of categories (ibid.:33-34). The process in-volved two native speakers of English – myself and Professor Charles Drage of �mperial College London – identifying English candidate metaphorical expres-sions, an individual wording only being included on the list if agreement was reached. Decisions regarding the expressions in the various target languages were generally taken by myself alone, but with suitable reference material and/or native-speaker informants being consulted where the need arose.

The multilingual examples are stored in an Excel spreadsheet along with meta-information and classification according to translation procedure, as well as a range of other theoretical parameters. This database of examples comprises a total of 30� rows. Of these, 2�� contain an English metaphorical expression along with between three and five translations, depending on the number of languages into which the specific article has been translated. The other nineteen rows consist of non-metaphorical English phrases that are translated by a metaphor in one (or occasionally two) languages. �n all, the data consists of a total of 13�4 TL examples.

The English metaphorical expressions are drawn from a total of twenty articles, with most being taken from six, arranged in Table 1 in decreasing order of frequency.

Article (publication date) Number of English metaphor-ical expressions

The Other Half of the Brain (April 2004) 107Evolution Encoded (April 2004) �3The Addicted Brain (March 2004) 37Synthetic Life (May 2004) 3�Freud Returns (May 2004) 2�Decoding Schizophrenia (January 2004) 10

Table 1. The six articles that contain the greatest number of metaphors listed in the corpus

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Each of the articles is written by a different author, an expert in his or her field. Unfortunately, not all of the most interesting articles to study are translated into all five target languages, a fact that needs to be borne in mind when making comparisons across languages.

The larger project on which this study is based focuses on a total of seven parameters in identifying and classifying metaphors: mapping, typological class, purpose, level of categorization, richness, provenance and convention-ality. For reasons of space, the discussion here will be restricted to mapping. A brief summary of another parameter, purpose, is however necessary as a starting point since it informs the analysis of mapping in section 3.

Metaphor in popular science fulfils a number of different functions, which are reflected in this parameter. These functions may be summarized as follows:

• exegesis expressions have an explanatory function – ‘neurons as the brain’s prime communicators’ (�oyd 1��3:4��);

• theory-constitution metaphors constitute an “irreplaceable part of the linguistic machinery of a scientific theory” (ibid.:4��) – ‘creating … biological devices’;

• terminology: terms are coined on the basis of a metaphor, even if this is hidden in a word from an ancient language – neurotransmitter; disor-der; dendrite;

• evaluation metaphors engage the non-specialist reader through the use of vivid evaluative or culture-bound language – ‘TinyO� is stingy with power’; ‘tiny cellular butlers’;

• shorthand metaphors refer to complex scientific concepts and processes in simple, easy-to-understand terms – ‘amino acids like to cluster to-gether’; ‘ATF is neatly packaged inside the tips of axons’.

�n scientific terms, evaluation and shorthand can be thought of as of less ‘core’ importance than the other three categories as they are more geared towards engaging a non-specialist readership than contributing to processes of concept-formation and explanation.

3. Mapping

While individual metaphorical expressions represent the micro-level, mappings are structures that belong to the macro-level. �t is often necessary to posit a unique mapping to describe a single metaphorical expression. However, mappings associated with a larger number of metaphorical expressions will have greater explanatory power; the most widespread mapping within the corpus is associated with as many as 21. One of the interesting things about the data in the corpus is the different degrees to which the various mappings are realized in English and each of the five target languages. The main aim of this article is to investigate what if any translation trends can be observed on the level of mapping.

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Expressed by convention in the form a is b, the precise formulation of a mapping is proposed by the researcher on the basis of his or her analysis of the data. �t goes without saying that finding the right verbalization for a mapping is not always easy and inevitably involves an element of subjectivity. The way it is verbalized needs to encapsulate its metaphorical force and correspond to what the researcher judges to be the most appropriate level of generality on the basis of its likely range of applicability. Humanizations, for example, can range in generality from the very broad brain cells are humans to the highly specific nature is a blind designer, this depending on the mapping’s precise contextual motivation. More specific mappings (e.g. nature is a blind designer and nature is a software designer) can coexist with more general ones (e.g. nature is a designer and nature is a human), inheriting some of their entail-ments. �n addition, where related mappings of a single target domain appear to exist, individual metaphorical expressions need to be assigned carefully to the most appropriate mapping. For example, it is necessary to distinguish between genetic material is text and genetic material is language, and decisions thus need to be taken on how to assign expressions containing lexical items such as editing out, libraries and transcript (all genetic material is text) and acid meanings, nonsense and synonyms (all genetic material is language).

3.1 Source and target language mappings

The English metaphorical expressions identified in the current corpus may be categorized into 113 different mappings; of these, the most frequent ten are listed in Table 2.

Table 2. Most frequent mappings in the corpus

Mapping Number of expressionsbrain cells are humans 21genetic material is text 1�neurons are trees 14the nervous system is circuitry 12genetic material is machinery 12neurons are communicators 11genetic material is code 11genetic material is language 10genetic material is software �nature is a creator of code �

Within these 113 English-language mappings there are three clusters of thematically related ones, centring around genetic material (eight mappings), nature (seventeen) and neurons (five). �n what follows � will focus principally on

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mappings that reflect relatively large numbers of metaphorical expressions.Far fewer than the total of 113 different mappings identified in the English

data can be found in each of the target languages (�� for German, 70 for Rus-sian, �0 for Polish, 71 for French and �� for �talian). This is in spite of the fact that each target language features some new mappings (17 in German, 14 in Russian, 2� in Polish, 1� in French and 14 in �talian), which means that of the original 113 English mappings the following totals are retained in each TL: �2 in German, �� in Russian, �4 in Polish, �� in French and �4 in �talian, all of which are far below the original figure for English, even allowing for the existence of untranslated articles in German, French and �talian. These startling figures are largely explained by the fact that there are 71 English mappings that are only represented by a single example; these are more vulnerable to deletion. At the same time, the mean number of metaphorical expressions per mapping is 2.03 for German, 2.2� for Russian, 2.1� for Polish, 2.01 for French and 2.�3 for �talian, as against 2.�7 for English. This may well imply that individual metaphorical expressions are lost in translation more frequently than entire mappings (particularly in German and French, but not in �talian), indicating a greater stability at the level of mapping than at that of individual metaphorical expressions, in spite of the considerable depletion in numbers of mappings.

There is, then, relative instability on both mapping and individual expres-sion levels, but one measure indicates a greater stability at the former level than at the latter. However, what is of particular interest is whether the data indicates an overall tendency on the part of translators not to intervene on the macro-level, i.e. whether they refrain from taking global decisions regarding the acceptability (or otherwise) of a particular mapping in the target context. This requires looking at individual mappings to ascertain such tendencies.

The ten most frequent mappings identified in the corpus and listed in Table 2 are shown in Table 3 for all languages. Among them, there are no examples of a mapping that is not translated at all, and very few of one being seriously depleted in translation. Thus, for example, genetic material is text is the sec-ond most frequent mapping in the English data, with a total of 1� metaphorical expressions, and one of the two most frequent in Russian (together with brain cells are humans), with 13 examples.4 Mappings that make the top ten in one or more target languages but not in English are included below the dotted line along with their ranking in the other languages for comparison. On the face of it, the languages that demonstrate the most radical reductions appear to be German, Russian and French. �n order to exemplify the kinds of phenomena that occur in the translation process, two mappings, brain cells are humans and neurons are trees, are analyzed in detail below.

4 The reduction from 1� to 13 examples is not considered significant as it reflects overall high levels of removal and omission observed in the corpus.

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Mapping English German Russian Polish French Italian

brain cells are humans 1 21 1= � 1= 13 1 17 1= 10 1 1�

genetic material is text 2 1� 1= � 1= 13 2 13 4 � 2 1�

neurons are trees 3 14 �= � � 7 4 10 10= 2 �= �

the nervous system is circuitry

4= 12 �= 4 �= � �= � 1= 10 3 13

genetic material is machinery

4= 12 3 � 3 11 3 11 1�= 1 4 10

neurons are communicators

�= 11 �= 4 �= � 10= 4 �= 7 �= �

genetic material is code �= 11 �= � 4 10 �= � �= 7 7 �

genetic material is language

� 10 4 7 �= � 7 � 3 � �= �

genetic material is software

�= � �= � 10 4 �= � 1�= 1 �= �

nature is a creator of code

neurotransmitters are messengers

�=

11=

�

7

12=

�=

3

4

11=

�=

3

�

27=

�=

1

�

�

�=

�

7

13=

�=

3

�

neurons are eavesdroppers

13= 4 24= 1 27= 1 10= 4 � 4 11= 4

genetic material is inheritance

- 0 �= 4 - 0 - 0 - 0 - 0

Table 3. The most frequent mappings in all languages; for each language, the figure in the first column is the order of frequency for that language and

that in the second the number of occurrences of each mapping

3.2 brain cells are humans

brain cells are humans, which features at the top of the list, encompasses a wide range of different kinds of humanization normally conveyed by a single word used in a figurative sense, as can be seen from the following examples:

other glia residing at the axon’s synapseaxon’s synapse synapsechemical signals that neurons did not recognizehow exactly would glia be affected by what theyaffected by what they by what they heard?�chwann cells perform myelinationmyelination dutieshow an immature �chwann cell ...cell ... ... knows which axons will need

myelinglial cells merely nurtured themthemthe overall behavior of nerve cellscells

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Of the 21 examples in English, 1� are classified as shorthand and � as evalu-ative in terms of purpose, which means that this mapping is used exclusively for non-core scientific purposes. Twenty of the 21 examples are taken fromTwenty of the 21 examples are taken from the article The Other Half of the Brain and one from The Addicted Brain. To all intents and purposes, what happens to the mapping in each language thus seems to be in the hands of a single translator. �e that as it may, the extent of its depletion in French and German (only 10 and � examples retained, respectively) appears at first sight to be remarkable.

�n French, all eight instances of omission involve extracts longer than a single metaphorical expression (a sentence, a photograph and its caption and, in the case of six expressions, an entire section). This means that the loss of metaphorical expressions observed here seems to be simply a side effect of the need to abridge the article in question. �n German, while a total of 10 ex-while a total of 10 ex-amples are omitted and 2 replaced by non-metaphorical textual material, it is difficult to identify an underlying pattern as to whether the appearance or non-appearance of a particular metaphorical expression can be attributed to purely metaphorical considerations. On the one hand, the following four metaphorical instances of the verb ‘to sense’ are not transferred into German:

English: more glia had lit up, because they had sensed the signalsGerman: Clause containing this item is omitted.

English: glia began to light up, indicating they sensed the messageGerman: begannen auch Gliazellen zu scheinen. �ie hatten also die Nervenimpulse registriert [glia cells also began to shine. �o they had registered the nerve

impulses]

English: �chwann cells at intact synapses somehow sensed that a neigh-boring synapse was in trouble

German: Clause containing this item is omitted.

English: CRE� is a transcription factor, a protein that regulates the ex-pression, or activity, of genes and thus the overall behavior of nerve cells.

German: Dabei hilft das Protein »CRE�« mit, das als ein so genannter Transkriptionsfaktor die Aktivität bestimmter Gene reguliert.

[This process is assisted by the protein CRE�, which as a so-called transcription factor regulates the activity of particular genes.]

Entire second part of the sentence is omitted.

�n three further examples, it was not even possible to identify where in the text the metaphorical expression would have occurred. On the other hand,On the other hand, something akin to the metaphorical force of the original word is retained in two other target expressions:

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English: how glia around an axon sense neuronal activityGerman: wie die Glia, die ein Axon umhüllt, einen Nervenimpuls erfasst [how the glia that wraps round an axon understands a nerve

impulse]

English: glia sense axon activityGerman: dass Gliazellen neuronale �mpulse wahrnehmen [that glial cells are aware of neuronal impulses]

Thus, while there are instances in which this particular mapping is retained, the data clearly indicates a lack of close item-for-item correspondence between �T and TT, a situation that appears to be typical of at least some German Scientific American translations. Where a longer omission occurs it may well be the case that the loss of the metaphor is entirely ‘incidental’, as in none of these examples would the presence of a metaphorical expression have been likely to trigger such a major deletion of textual material. Conversely, the possibility is by no means ruled out that the presence of a metaphor may be a contributing factor in the case of phrase-length (or shorter) omissions.

The brain cells are humans mapping is best preserved in Polish. �ndeed, not only are very few instances omitted or replaced with non-metaphoricalinstances omitted or replaced with non-metaphoricalomitted or replaced with non-metaphorical material, but there is one instance where a new expression is added:

English: we found a contrasting situation with the oligodendrocyte gliaPolish: stwierdziliśmy,żezupełnieinaczejzachowują się oligodendro-

cyty neurogleju [We established that the oligodendrocyte glia behaved com-

pletely differently]

On the whole, it appears that this mapping survives well in the various target languages, once adjustment has been made for the incidental factors discussed above. This claim is made on the basis that at least five different translators working with different language pairs have in most cases translated relevant metaphorical expressions with TL expressions that reflect the same mapping.

3.3 neurons are trees

The second mapping to be analyzed, neurons are trees, is realized in seven English metaphorical expressions from The Other Half of the Brain and seven from The Addicted Brain. Here, the attributes and component parts of neurons are equated with those of trees on the basis of their appearance, as in the following examples:

Each neuron has a long, outstretched branchunneeded synapses get prunedthe �chwann cells�chwann cells cells sprouted branches that extended to the damaged

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synapse, forming a bridge�ut those who become addicted to cocainewho become addicted to cocaine become addicted to cocaine sprout additional spines

on the branches, which consequently look bushier

This mapping is therefore based on an image metaphor, unlike the previous mapping discussed, brain cells are humans. �t is worth noting that the currentworth noting that the current corpus features only 22 image metaphor expressions, including the 14 reflected in this mapping. With � examples classified as exegetical in terms of purpose (giving readers a clear idea of the appearance and structure of a neuron) and 3 as terminological, the overall function of this mapping is of central importance: its purpose is not simply one of embellishment as one might have expected. The remaining two examples are evaluative.

The figures for retention of this metaphor in German and �talian (Table 3) are as low as they are because only one of the two relevant articles is translated into each of those languages. �imilarly, the reason for the low figure in French is the omission of an entire section and an image and its caption. The Russian data presents a mixed bag of different procedures, but with only one extended omission. Many of the renderings, however, show the translator choosing a more general word or phrase or a solution more loosely associated with the neurons are trees mapping than the source text:

English: to buds at its endRussian: ��: �� расширенным участ��ам на его ��онце – а��сонным

терминалям [to enlarged areas at its end – the axon terminals]

�n this instance, the �T metaphorical expression is removed and replaced by a more general phrase (buds→enlarged areasareas). Like many of the modifications we see in the corpus this is not an obligatory change, as the translator could theoretically have used the Russian word for ‘buds’, pochki. The metaphorical term aksonnye terminali is then appended, adding a degree of explicitation and, arguably, raising the technical level of the sentence.

English: the �chwann cells sprouted branchesRussian: �ог�а они �ру�но: �ог�аони�ру�новыпустили в его сторону отростки [Then together they put out shoots towards it]

Here, the unambiguous sprouted becomes the more general ‘put out’, and branches is changed to ‘shoots’. We are still in the domain of plants, but not specifically that of trees.

English: �ut those who become addicted to cocaine sprout additional spines on the branches, which consequently look bushier.

Russian: �� �и�отны�, �ристрасти�ши�ся �� ��о��аину,: �� �и�отны�, �ристрасти�ши�ся �� ��о��аину, шипиков на дендритахгораз�обольше

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[Animals addicted to cocaine have far more spines on their dendrites]

Once again, sprout disappears (as does bushier), while branches now becomes the less semantically immediate but more terminologically precise dendrites.

English: dendritic branches with normal numbers of signal-receiving projections called spines

Russian: дендриты собычным��оличест�омши�и��о�– �ыросто�,– �ыросто�, �ыросто�,ула�ли�ающи�нер�ныесигналы

[dendrites with the usual number of spines – projections that catch nerve signals]

Here again the more semantically concrete branches is deleted, leaving just the semantically opaque metaphor dendrity (which is derived from Greekfrom Greek dendritēs, ‘pertaining to a tree’). The Russian examples thus reveal a definite. The Russian examples thus reveal a definite weakening of the mapping, not only through the depletion of numbers of ex-pressions but also because of a tendency towards greater generalization. generalization..

Finally, the mapping is best preserved in Polish, with only two examples re- best preserved in Polish, with only two examples re- only two examples re-placed by non-metaphorical textual material and two omitted. There is a strongThere is a strong tendency to retain expressions essentially unaltered, with some evidence of a preference for generalizing solutions similar to those witnessed in Russian.generalizing solutions similar to those witnessed in Russian. solutions similar to those witnessed in Russian.

Across languages, overall, there is a higher than average number of modified expressions within this mapping (1�.1% as against an average of 11.�% for all mappings), indicating that at least the five or more translators represented in the corpus may be reluctant to retain this stark image in their target texts. On the whole, most mappings undergo some depletion. At theOn the whole, most mappings undergo some depletion. At the same time, there is no clear shift from one mapping to another, but rather a kind of piecemeal dissipation.

4. Mapping clusters

As stated above, an inspection of the complete list of mappings reveals that there are three significant thematically-linked groups of mappings clustered around the concepts of genetic material, nature and neurons, consisting of �, 17 and 4 English mappings respectively (excluding neurons are trees), with a significant number of new ones added in the various TLs. �n all, these account for a total of ��, 3� and 23 English expressions respectively. For reasons of space, � will only consider the first two: genetic material and nature.

4.1 Genetic material

The concept of genetic material gives rise to a group of very common map-pings, five of which are present in the top-ten list. Genetic material is mapped in the following ways, arranged in decreasing order of frequency:

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genetic material is text (1� examples): ‘a six-letter genetic alphabet’genetic material is machinery (12): ‘evolution will tend to break

genetic machines’genetic material is code (11): ‘the rules of life’s underlying code’genetic material is language (10): ‘the genetic sentence … must

first be translated from one system of symbols into an entirely different kind of system’

genetic material is software (�): ‘The aim … was to reprogram cells’

genetic material is circuitry (3): ‘rewire cells to glow in the presence of a particular toxin’

genetic material is instructions (3): ‘how [genes’] instructions affect the behavior of the protein molecules they describe’

genetic material is data (1): ‘This kind of data compression’

The fact that all but two of the �� expressions occur in the two articles Evo-lution Encoded and Synthetic Life demonstrates that it is possible for several different models of a particular concept to be used in parallel in individual texts. The purposes for which metaphorical expressions within these mappings are used are predominantly exegesis (4�) and theory constitution (1�), with very few examples of evaluation or terminology, and none of shorthand. This suggests that these mappings are central to the core tasks of communicating science and structuring our understanding of scientific concepts. �nterestingly, all the examples of theory-constitutive metaphorical expressions in the entire corpus are found in this cluster of mappings.

�n all, and possibly because of the purpose of most of the metaphorical expressions related to the theme of genetic material, this appears to be a re-markably stable area in terms of the retention of mappings. Table 4 summarizes the different translation procedures adopted in each language.

Language Modified Omitted Replaced with non-metaphorical material

Retained Total

German 1 22 3 3� ��Russian � 11 � 44 ��Polish 2 � 10 4� ��French 2 4 3 27 3��talian 4 � � 4� �4

Table 4. Translation procedures used for genetic material metaphorical expressions

With the exception of genetic material is circuitry, which is absent from the French data because all examples appear in Synthetic Life, an article that is

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not translated into that language, none of the original eight mappings vanish in translation, although a number are depleted – genetic material is text in German, genetic material is software in Polish and genetic material is language in Russian, this final example providing further evidence of the diversity of the modifications that occur.

English: the cellular machinery translating DNA’s messageRussian: ��леточного а��арата��леточного а��аратаа��аратаа��арата декодирования [of the cellular decoding apparatus]

Even though apparat translyatsii would have been an acceptable alterna-tive to apparat dekodirovaniya, the translator’s selection of the latter variant transforms genetic material is language into genetic material is code; this is one of two instances where Russian adds an example of this mapping. �n the following example, on the other hand, it is the genetic material is language mapping itself that is strengthened:

English: the genetic sentence … must first be translated from one sys-tem of symbols into an entirely different kind of system

Russian: то генетичес��ое �ослание мо�но �рочесть, толь��о: тогенетичес��ое�осланиемо�но�рочесть,толь��опереведя его с языка,ис�ользующегоо�нусистемусим�оло�,на со-вершенно другой язык

[the genetic message can be read only if it is translated from a language that uses one system of symbols into an entirely dif-ferent language]

Only one new mapping appears in the course of translation, and that is genetic material is inheritance. Four examples of this mapping are added in German, each of which involves the use of a word starting with the morpheme Erb- ‘heredity’, as in the following example:heredity’, as in the following example:’, as in the following example:

English: Twisted ladder of DNAGerman: »�trickleiter« des Erbmoleküls DNA [“rope ladder” of the heredity molecule DNA]

Erbmolekül is not needed here; der DNA (of DNA) would have been an accept-able translation. Metaphorically speaking, this is the most obvious instance of Metaphorically speaking, this is the most obvious instance of innovation identified in any of the target languages. Otherwise, nearly all the mappings identified are depleted through replacement with non-metaphorical material and omission in what appears to be a non-consistent manner, as seen elsewhere.

4.2 Nature

There are far more mappings relating to nature in the corpus, but each only accounts for an average of slightly more than two metaphorical expressions.

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The expressions that exemplify the mappings are drawn from a total of 1� texts (but with nearly half coming from Evolution Encoded). As with the genetic material cluster, this cluster of humanizing mappings appears to be a remarkably stable area in terms of retention of mappings, although, unlike the genetic material cluster, many of the mappings and expressions feature a clear culture-specific element. The commonest 7 of the 17 – those represented by more than one metaphorical expression – are as follows:

nature is a creator of code (�): ‘Nature’s code minimizes the effects of genetic errors’

nature is an exerciser of choice (4): ‘the solution that nature has chosen for the dark matter problem’

nature is a giver of gifts (3): ‘Cosmic acceleration may be … ‘a gift from nature’

nature is a spendthrift (3): ‘What precisely would nature be wasting?’

nature is a blind designer (2): ‘Natural selection is a “blind designer”’nature is a helper (2): ‘Fortunately, nature has helped again’nature is a software designer (2): ‘nature’s skill as a primordial

software designer’

To the extent to which one can claim that the overall effect of these mappings is to produce a coherent ‘image’ of nature, one can characterize their main en-tailments as presenting nature as a sentient, communicating, generous, guiding creator or designer. Although the purpose of the expressions is predominantly either evaluation or shorthand, it is tempting to suggest that the overall picture of nature that emerges is more in line with the notion of ‘intelligent design’ than with the theory of evolution that is presumably subscribed to by all Scientific American authors. �n other words, in their efforts to communicate as clearly and graphically as possible they have, presumably unconsciously, portrayed nature in a manner that flies in the face of their consciously held beliefs.

�t should be no surprise that here too a number of mappings, including many of the ten one-expression mappings, are lost in one or other TL (�talian being the most conservative in this respect). More significantly, there appears to be a certain backing away from the �L tendency to humanize nature. �t is first of all interesting to observe what happens to the nine examples of the mapping nature is a creator of code, as in each TL numbers of occurrences of this mapping are greatly depleted (the precise numbers of examples surviving in each TL are � in French, 3 in German, Russian and �talian, and 1 in Polish). The original metaphorical expressions can all be found in a single �L article, Evolution Encoded (which is translated into all five TLs). Two typical exam-ples of this mapping are as follows:

Nature’s code minimizes the effects of genetic errorsAt least 1� organisms … deviate from nature’s standard code

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The possessive construction is not only found in all � examples, but is vital for the functioning of this mapping: convert it to another construction (the natural code, for example) and the (albeit weak) entailment that nature has created this genetic code vanishes. �ndeed, this is precisely what we see hap-pening in a number of TLs:

English: only 100 of one million alternatives had a lower error value than nature’s code

German: von einer Million künstlicher Codes reagierten nur hundert we-niger empfindlich auf Fehler als der natürliche

[of one million artificial codes only one hundred reacted to er-rors with less sensitivity than the natural one]

Polish: tylko100kodównamilionmaniższywspółczynnikbłęduniżkod naturalny

[only 100 codes in a million have a lower level of error than the natural code]

French: sur un million de codes alternatifs, une centaine seulement avait un taux d’erreur inférieur à celui du code naturel

[out of one million alternative codes, only about a hundred have an error rate less than that of the natural code]

�talian: solo 100 su un milione erano migliori di quello naturale [only 100 out of a million were better than the natural one]

�nterestingly, a quick check on Google indicates that direct equivalents of the phrase nature’s code do not occur very frequently in most TLs. At the same time, this also seems to be the case for many of the alternative variants settled on by the translators. �n other words, in this instance the four translators seem to avoid close translations that in most cases are not commonly used in their TL; instead, they use ad hoc solutions that also do not enjoy a high degree of currency.

�n all, there are only � examples of a direct equivalent of nature’s code be-ing used in any language (1 in German, 4 in French and 1 in �talian) out of a theoretical maximum of 4�. However, the grammatical restructuring illustrated above is not the only way in which this mapping is replaced by alternative phrasings. �n Russian, for example, nature’s code is paraphrased as follows:

Russian: толь��о у 100 альтернати�ны� ��о�о� из миллиона цена ошиб�: толь��оу100альтернати�ны���о�о�измиллионаценаошиб-��именьше,чему��аноничес��ого

[only in 100 alternative codes is the price of an error lower than in the canonical one]

The same variant, kanonichesky kod, is used to render a second instance of this mapping, and on a third occasion a similar solution, genetichesky kod (‘the genetic code’), is opted for. Along similar lines, the �talian text uses the expressions presente in natura (‘present in nature’) and esistente in natura

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(‘existing in nature’) on a total of three occasions. The �talian translator may have been motivated here by the fact that the usage of (il) codice della natura, the direct equivalent of ‘nature’s code’, may indeed be extremely marginal (as suggested by Google), although this explanation does not hold in the case of the Russian wording.

At the same time, however, in the instances of this mapping that survive in the TLs there is a strong tendency towards intensification, as can be seen in the following examples:

English: many came to view nature’s real code as little more than a ran-dom accident of history

French: on en vint à considérer le code élaboré par la nature comme un aléa de l’histoire

[people came to consider the code elaborated by nature as a chance of history]

English: Nature’s code minimizes the effects of genetic errorsRussian:: Код, созданный природой, с�о�ит �� минимуму �осле�с-

т�ияошибо�� [The code created by nature leads to the most minor conse-

quences of errors]Polish: Stworzony przez przyrodę kodminimalizuje efekty błędów

genetycznych [The code created by nature minimizes the effects of genetic

errors]

The intensification that we observe is accompanied in each case by explicita-tion of the mapping’s implicit entailment. The examples above, along with a handful of other similar instances, indicate that translators may opt for bolder, more definite instantiations of the mapping in preference to more direct render-ings. That said, there are other examples where intensification is accompanied by a change in mapping.

One other more minor phenomenon worth drawing attention to is the modest increase in reification – where a mapping from an abstract entity to an inanimate object occurs – that we see in the German data. There is only one, highly conventionalized, instance of the mappingthe mapping nature is a mechanism in the English texts:

English: we really understand, at a deeper level than ever before, how nature works

German: dass wir tatsächlich tiefer als je zuvor verstehen, wie die Natur funktioniert

[that we really understand more deeply than ever before how nature functions]

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�n this case the use of the word funktioniert is to a large extent obligatory as it is the standard way to translate the English works in this particular context.

Explicitation and intensification feature in the translation of another, non-metaphorical English expression, producing a second, new example of the mapping in German:

English: why nature chose these basic rules and why they have survived three billion or so years of natural selection

German: wie [dieser Code] 3 Milliarden Jahre strenger Prüfung durch die unerbittliche Maschinerie der natürlichen Auslese überstand

[how for 3 billion years [this code] withstood rigorous testing by the relentless machinery of natural selection]

�n addition, two new German examples instantiate nature is a structure, a mapping that is not attested in the English data:

English: superstrings, which they hypothesize to be the most fundamen-tal entities

German: [�uperstrings] seien die fundamentalsten Bausteine der Natur [[�uperstrings] are the most fundamental constituents [= build-

ing stones] of nature]

The second example also involves the use of the same word, Bausteine.Overall, what we observe (admittedly across small numbers of examples

from four different articles) is a slight shift away from humanization towards slight shift away from humanization towards reification in the German data. Alongside this, what we have seen in the other examples is a tendency to lose some mappings through apparently unmotivated rewording, but also some instances of individual expressions being intensified through explicitation. On the whole, however, the picture of nature as an agent of intelligent design remains basically intact, if different in detail and slightly more restricted, in all TLs.

5. Conclusions

This study has attempted to find at least partial answers to certain questions by examining the mapping and purpose of metaphors and linking these with a metaphor’s chances of surviving the translation process. The approach adopted involves both the use of statistics and the application of human intuition in interpreting them. As a report on a section of a larger research project there is much interesting material that had to be omitted; in particular, for reasons of space it has not been possible to include a discussion of all the various param-eters employed in the study for identifying and classifying metaphors.

Throughout the article � have deliberately not tried to hide the complex nature of the data or simplify the sometimes ambiguous or even contradictory

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messages that it seems to convey regarding metaphor in translation. Each ex-ample presented represents one of a potentially unlimited number of possible solutions that the translator(s) could have opted for, and we must therefore be careful not to overgeneralize any conclusions drawn. �n addition, statisticaltatistical data has to be interpreted carefully, not least because of the fact that not all �L articles have been translated into all five TLs.

�t is not possible to report that translators generally treat metaphorical mappings as high-level entities in their own right and take global decisions regarding how best to render into a particular TL the metaphorical expressions associated with them. � therefore have to concur with �nell-Hornby’s (1���) conclusion that the influence of the �T can frequently override a translator’s feelings as to what is most in line with existing TL metaphorical patterns.

Larger metaphorical structures such as mappings are generally preserved in translation, although there will be differences of detail between the extent and number of �T and TT mappings. Metaphorical expressions tend to be dealt with on an individual basis, with some inconsistency in how similar examples are handled. �n terms of the question of whether mappings are shifted (i.e. tend in a particular direction) or scattered (i.e. point in conflicting directions), the former result obtains with many one-example mappings, although there is little significance in this result, while the latter describes what happens with multiple larger mappings because of the frequently inconsistent handling of individual examples. �n general, the large number of omissions and replace-ments with non-metaphorical material is worthy of note, and results in some mappings being neither shifted nor scattered, but lost. Overall, there is little clear evidence of obvious manipulation or subversion of �T metaphors. This is not to say that such manipulations do not take place, but perhaps this negative finding is not surprising given that the analysis has mainly taken place at the level of mapping (rather than individual expressions), where most translators are unlikely to make conscious decisions.

On the whole, there is little evidence to suggest that metaphor presents a major problem to translators of popular science texts.

MARK �HUTTLEWORTHDepartment of Humanities, Imperial College London, South Kensington Campus, London SW7 2AZ, UK. m.shuttleworth@imperial.ac.uk

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