An expert-performance perspective to highly accomplished translators’ uncertainty management process: a case study

Abstract

This case study takes an expert-performance perspective, investigates the cognitive process of translation uncertainty management (TUM), and hopes to gain insight into the constituents of translation expertise. Four highly accomplished translators were selected by following a combined criteria for expertness, namely, a lengthy domain-related experience, an excellence level of social evaluation, and a consistently high level of self-evaluation. TUM process data were collected in a triangulated manner and data analysis followed the analytical framework of data reduction, data display, and conclusion drawing and verification. Altogether, nine types of TUM-related categories were identified through data reduction, three of which, translation uncertainty types, TUM strategies, and TUM cognitive process steps, were displayed and discussed in this paper. Results showed that experts share some commonality in their TUM process. They were found to encounter by far the most sentence-level transfer translation uncertainties (TUs), implying a macro-approach in managing TUs; to share nine strategies that help optimize the TUM process; and to demonstrate a common cognitive pattern that can be simulated in a process model. In other words, literal replication was successfully achieved within this expert case group, and TUM parameters established in this study promise to be applicable to future similar researches.