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Explicitation 159 Table 5. Type/token ratios in the comparable corpus Sub-corpus Original Translated Mean Hungarian Hungarian 1. Literary 65.73 61.75 63.74 2. Non-literary 60.84 54.54 57.69 Mean 63.29 58.15 Difference 4.89 7.21 At this point I wish to comment on the genres investigated. The type/token ratios of the non-translated texts indicate a 5% difference between the two genres, whereas this difference is 7% in the translated texts. The convergence of these parameters might suggest – as we hypothesed at the outset of the research – that translators of technical texts, in their effort to convey the information given by the ST as closely and clearly as possible, will inevitably use explicitation strategies more often than translators of creative literature. Explicitation strategies then lead to lexical repetitions, consequently to less varied vocabulary. In other words, this characteristic may well reflect the norm which governs genre expectations. 5. Conclusions The research reported in this paper purported to test the explicitation hypothesis and to examine whether translations have a higher level of explicitness than non-translations. If we consider the structural differences between the two languages involved (the agglutinative Hungarian uses fewer words to express the same meaning than the analytical English, e.g. I love you → Szeretlek), translations from English into Hungarian would be expected to result in implicitation (making things more general, omitting linguistic or extralinguistic information of the ST) rather than in explicitation. With the 16 explicitation strategies, however, established in the parallel corpus, explicitation seems to be a strong tendency in the English – Hungarian translation direction. The findings of the second analysis indicate a higher level of explicitness throughout the comparable corpus. Most of the frequencies support the hypothesis that the explicitness of the translations is higher than that of nontranslated texts.
160 Vilma Pápai In addition, considering all the data, we can conclude that the third hypothesis should be rejected. The analysis did not provide evidence for the question concerning differences in genres. On the basis of the present findings we cannot claim that there is a clear-cut difference between literary and nonliterary texts, as far as the linguistic items investigated are concerned. As to the questions of type/token ratios, I am inclined to see the lower percentage in translated texts as a consequence of explicitation strategies. Apart from shifts on the logical-visual and textual – extra-linguistic levels (see Table 2), all the shifts inevitably lead to lexical repetitions, consequently to simplification in the vocabulary. For example, the addition of conjunctions, the addition of cataphoric reference + conjuncts, and the use of derivatives add up, indirectly, to the number of repeated items, i.e. the number of tokens, and therefore, lessen the number of types. Filling in ellipsis, reconstructing substitution, and replacing pronouns by nouns also contribute to a lower variety of vocabulary.Thiswould allow the claim that the notion of explicitation seems closely linked to the notion of simplification in translation. Summing up the analysis of the parallel and the comparable corpus we can conclude that, as the data suggest, in the period of 1969 and 1999 a translation norm was in play, according to which translators tended to adjust to target text standards and satisfy the target readers’ expectations. On the whole, this is the ultimate function of explicitation strategies. Appendix 1 Parallel corpus of English → Hungarian texts Literary texts Code Author Title Translator Title UP Updike, John 1977 Marry me Göncz Árpád 1981 Gyere hozzám feleségül CA Capote, Truman 1980 Music for Chameleons. Mojave PA Porter, Anna The Bookfair Murders ME McEwan, Ian 1999 Amsterdam Osztovics Levente 1982 Bart István 1998 Tandori Dezső 1999 Mozart és a kaméleonok. Mojave Gyilkosság a könyvvásáron Amszterdam
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Translation Universals
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Translation Universals Do they exis
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Table of contents Introduction 1 I.
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Introduction The search for univers
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Introduction 3 the main methodologi
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Introduction 5 tious corpus would w
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Introduction 7 of several frequent
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Introduction 9 For many, the term u
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Introduction 11 Toury, Gideon (1991
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Probabilistic explanations in trans
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Beyond the particular* Andrew Chest
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Beyond the particular 35 6. A trans
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Beyond the particular 37 characteri
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Beyond the particular 39 Contributi
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Beyond the particular 41 A crucial
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Beyond the particular 43 representa
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Beyond the particular 45 or unclear
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Beyond the particular 47 What we ne
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Beyond the particular 49 Schulte, R
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52 Silvia Bernardini and Federico Z
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Corpora, universals and interferenc
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Untypical frequencies in translated
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102 Jarmo Harri Jantunen Mauranen (
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104 Jarmo Harri Jantunen 2.2 Lexica
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106 Jarmo Harri Jantunen eighth day
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Page 136 and 137: Translation-specific lexicogrammar?
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Page 151 and 152: 144 Vilma Pápai It is in the last
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Page 155 and 156: 148 Vilma Pápai (Sinclair 1991:13-
Page 157 and 158: 150 Vilma Pápai Table 2. Summary o
Page 159 and 160: 152 Vilma Pápai 4.1.2 Shifts on th
Page 161 and 162: 154 Vilma Pápai part of speech and
Page 163 and 164: 156 Vilma Pápai his former prison
Page 165: 158 Vilma Pápai Table 4. Frequency
Page 169 and 170: 162 Vilma Pápai PA Porter, A. 1997
Page 171 and 172: 164 Vilma Pápai Ishikawa, Luli (19
Page 173 and 174: 166 Tiina Puurtinen (1996) and Bake
Page 175 and 176: 168 Tiina Puurtinen (1) Hän katsoi
Page 177 and 178: 170 Tiina Puurtinen conditional: jo
Page 179 and 180: 172 Tiina Puurtinen Table 2. Occurr
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Page 183 and 184: 176 Tiina Puurtinen Mauranen, Anna
Page 185 and 186: 178 Sonja Tirkkonen-Condit equivale
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Thefateof“TheFamiliesofMedellín
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Author index A Adab 1 Aijmer 131 Al
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Author index 217 Schäffner 1, 38,
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220 Subject index G generalization
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In the BENJAMINS TRANSLATION LIBRAR
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47. SAWYER, David B.: Fundamental A
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