| Summary: | The present work reports on an empirical study aimed at investigating the difficulties emerging in the translation of scientific texts from English into Italian for a group of student translators at an advanced level of training. The study is based on the assumption that scientific discourse presents a set of lexico-grammatical features (a 'syndrome', in M.A.K. Halliday's words) that contribute to making it opaque for non-specialists. This syndrome is largely the result of what Halliday calls 'grammatical metaphor', which is manifested principally as a tendency towards heavy nominalisation. In particular, it was hypothesised that as the density of grammatical metaphor, and the heavy nominalisation this leads to, increases, so does the difficulty experienced by translators, especially as regards text comprehension. The hypothesis is investigated by analysing a range of datasets related to the translation process and the translations produced by a small group of subjects (N=5) for three English source texts, chosen with a view to presenting increasing degrees of nominalisation. Specifically, the analysis looks at the editing performed by the translators on their own drafts, the degree of inter-translator variation manifest in the target texts and the errors identified in the target texts. Relevant signals of processing effort are sought in each set of data, and these signals are taken to point to the difficulty experienced by the student translators. After triangulating findings form each dataset, it was concluded that the hypothesis underlying the study could only partially be supported: the two more nominalised texts were associated with a high number of difficulty indicators but no further differentiation emerged between them. From a methodological viewpoint, the combination of data sources and methods employed for analysing the data (Choice Network Analysis and Error Analysis) proved to be reliable for identifying a cluster of ST segments observed to be difficult for translators on account oftheir high nominal density.
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