A Multifactorial Analysis of Translation Universals in Management Forewords of Sustainability Reports

This paper compares the behaviors of translation universals (TUs) in native speakers’ writings with those of non-native speakers’ and examines how TUs contribute to discriminating non-native speakers’ writings from natives’. Two small but representative corpora are compiled with the management forewords in sustainability reports published in the USA and Korea, and 26 TU factors are manually encoded. Then, the data are analyzed with statistical analysis (a logistic regression after a multicolliearity analysis), and a reliable statistical model is obtained (C=0.945, classification accuracy=84.483). Through the analysis, the followings are observed: (i) TUs definitely contribute to distinguishing non-native speakers’ writings from natives’, (ii) Among 26 TU factors, only 4 factors belonging to the simplification group are statistically significant, and (iii) There is also an interaction between Type and STTR. The behaviors of TUs in the studied corpus are slightly different from the observations in previous studies, but they provide another evidence that TUs are excellent indicators which can distinguish non-native speakers’ writings from natives’ ones.