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Explicitation 157
(discourse particle and also additive adjunct) but, of course, needs further
investigation on a larger corpus.
We understand, therefore, that it is not, or not only, the translators who
include elements thought to be translation-specific into technical texts. These
patterns can be explained by the aim of technical writers who want to load
a text with as much information as possible or, by their effort, conscious or
not, to produce as clear a text as possible or, most probably by the influence of
translated texts existing in the language community.
As for explicitness in the two genres we can observe higher frequencies in
non-literary than in literary texts. However, only 65% of the cases (3 out 20)
confirm the hypothesis, with the group of derivatives and conjunctions totally
supporting Hypothesis 3 and with the items from the discourse particle group
rejecting it. Explicitness of genres has to be investigated in more detail and
corpora definitely can serve this aim.
To sum up, we can conclude that the frequency data in HHC provide
evidence for the assumption that translated Hungarian texts show a higher level
of explicitness than non-translated texts (Hypothesis 2). This can also mean
that explicitation is likely to be a universal feature of translated texts, i.e. this
set of data supports Blum-Kulka’s hypothesis.
4.3 Type/token ratio in the comparable corpus
The type/token ratio is an indicator of lexical complexity as found on the
surfaceofatext.Thetermtoken refers to the total number of running words,
while the term type refers to the number of distinct word-forms in the text. The
higher the percentage the more varied the vocabulary (Baker 1995; Munday
1998). The type/token ratio is considered to be very sensitive to the length
of the text. I used the standardised type/token ratio because the texts of the
ARRABONA corpus display the same number of sentences but reveal quite
different word counts.
The findings of the statistical analysis indicate, as shown in Table 5, two
tendencies. Firstly, that translations of the comparable corpus show a lower
percentage type/token ratio than non-translations (58.15–63.29). This points
to the conclusion that vocabulary used in the translated texts is less varied than
that of the non-translated texts.
Secondly, non-literary texts of the comparable corpus show a lower
type/token ratio than literary texts (57.69–63.74). This suggests that the vocabulary
used in the non-literary texts is less varied than that of the literary texts.