Is linguistic decision-making constrained by the same cognitive factors in student and in professional
translation?
Evidence from subject placement in French‑to‑Dutch news translation
This article analyses the extent to which four well-known general cognitive constraints – syntactic priming,
cognitive routinisation, markedness of coding and structural integration – impact the linguistic output of translation students
and professional translators similarly. It takes subject placement variation in Dutch as a test case to gauge the effect of the
four constraints and relies on a controlled corpus of student and professional French-to-Dutch L1 news translations, from which
all declarative main clauses with either a preverbal or a postverbal subject were extracted. All corpus instances were annotated
for four random variables, the fixed variable expertise and ten other fixed variables, which were considered good proxies
for the cognitive constraints. A mixed-effects regression analysis reveals that by and large the cognitive constraints have an
identical effect on student and professional translators’ output, with priming and structural integration having the strongest
impact on subject placement. However, students diverge from professionals when translating French clauses with a left-dislocated
adjunct into Dutch, which is interpreted as an indication of a difference in automatisation when dealing with specific
French-Dutch cross-linguistic differences.
Article outline
- 1.Introduction
- 2.Subject placement variation in Dutch: General characteristics, determinants, constraints and expertise
- 3.Data and methodology
- 3.1Corpus design and processing
- 3.2Data extraction and annotation
- 3.3Operationalisations of the constraints (fixed variables)
- 3.3.1Markedness of coding
- 3.3.2Cognitive routinisation
- 3.3.3Structural priming
- 3.3.4Syntactic integration
- 3.4Hypotheses
- 3.4.1Expertise
- 3.4.2Markedness of coding
- 3.4.3Cognitive routinisation
- 3.4.4Structural priming
- 3.4.5Structural integration
- 3.5Statistical analysis
- 4.Results
- 4.1Random effects
- 4.2Fixed effects
- 4.2.1The interaction effect of intertextual priming and subject length
- 4.2.2The interaction effect of intertextual priming and complexity of the VP
- 4.2.3The interaction effect of indirect intertextual priming and expertise
- 4.2.4The interaction effect of subject discourse status and complexity of the VP
- 4.2.5The interaction effect of subject discourse status and subject length
- 5.Discussion
- 6.Conclusion
- Acknowledgements
- Notes
-
References