Translation Universals.pdf - ymerleksi - home

42 Andrew Chesterman
Problem: testing. Tests of these claims sometimes produce confirmatory evidence,
sometimes not. But how rigorous are the tests? If you are investigating,
say, explicitation or standardization, you can usually find some evidence of it
in any translation; but how meaningful is such a finding? It would be more
challenging to propose and test generalizations about what is explicitated or
standardized, under what circumstances, and test those. To find no evidence
of explicitation or standardization would be a surprising and therefore strong
result. Stronger still would be confirmation in a predictive classification test,
as follows (based on a suggestion by Emma Wagner, personal communication,
2001). If these universals are supposed to be distinctive features of translations,
they can presumably be used to identify translations. So you could take pairs of
source and target texts, and see whether an analysis of some S-universal features
allows you to predict which text in each pair is the source and which the target
text. For each pair you would have to do the analysis in two directions, assuming
that each text in turn is source and target, to see which direction supports a
given universal tendency best. Or you could take a mixed set of texts consisting
of translations and non-translations and analyse them for a given T-universal
feature, and use the results to predict the category assignment of each text (=
translation or not). Some universals might turn out to be much more accurate
predictors than others.
Problem: representativeness. Since we can never study all translations, nor
even all translations of a certain type, we must take a sample. The more
representative the sample, the more confidence we can have that our results
and claims are valid more generally. Measuring representativeness is easier if
wehaveaccesstolargemachine-readablecorpora,buttherealwaysremainsa
degree of doubt. Our data may still be biased in some way that we have not
realized. This is often the case with non-translated texts that are selected as
a reference corpus. Representativeness is an even more fundamental problem
with respect to the translation part of a comparable corpus. It is not a
priori obvious what we should count as corpus-valid translations in the first
place: there is not only the tricky borderline with adaptations etc., but also
the issue of including or excluding non-professional translations or nonnative
translations, and even defining what a professional translation is (see
Halverson 1998). Should we even include “bad” translations? They too are
translations, of a kind.
Problem: universality. Claims may be made that a given feature is universal,
but sometimes the data may only warrant a subset claim, if the data are not