The space between the data and the concepts

Kirjoittajat

• Andrew Chesterman University of Helsinki

DOI:

https://doi.org/10.61200/mikael.129661

Avainsanat:

hypotheses, research methodology, significance, literal translation, explanation

Abstrakti

The space between data and concepts is filled with hypotheses, which make up everything we call methodology. This claim is explained via a discussion of the role of interpretive, descriptive and explanatory hypotheses in methodology. The discussion is followed by an examination of the criteria that make any hypothesis a significant one, worth testing. As an example we take the well-known literal translation hypothesis. This states that as translators process a given text segment, they tend to proceed from more literal versions to less literal ones. The main criteria on which a hypothesis can be justified as significant are: explicitness, multiple testability, theoretical implications (links with other hypotheses), applicability to other research problems, surprise value, and explanatory power. Several other hypotheses in Translation Studies will be referred to en route, including Toury’s laws, Seleskovitch’s deverbalization, Tirkkonen-Condit’s unique items, Halverson’s gravitational pull and Pym’s risk avoidance.