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Campbell, S. (2017). Choice network analysis in translation research

This is one of the most interesting papers I have read so far. Campbell (2017) introduces a new method of using translations to examine translators behavior. This new approach is called Choice Network Analysis (CNA). Such an approach is rooted in the competition model in interpreting research which was initially developed to study language acquisition. This model is part of the connectionist model which assumes "the brain relies on a type of computation that emphasizes patterns of connectivity and activation" (Mcwhinney 1997:222), rather than on serial processing.  The paper is comprised of nine sections.

1.  In the introduction, Campbell summarizes research methods of mental processes in translation, namely; Think-aloud protocols, word-based experimental techniques (rooted in cognitive psychology), and neuroimaging. He refers to an 'overlooked' process which can shed light on the translator behavior; the target text itself.

2. The second part discusses (The basic architecture of mental processing), Campbell discusses his first attempted to model lexical decision-making based on the notion that translation involves sequential steps. Later, he concluded that the process of decision making involves the simultaneous sequencing of information of various types; lexical, semantic, syntactic, pragmatic, etc.

3. In the third section (Principles of choice network analysis), the paper lists five principles for CNA:
  • Target texts can be used as a tangible source of evidence of mental processing in translation, and an alternative to experimental data and think-aloud protocols.
  • The products of a sample of subjects translating the same text into the same language will reveal a range of differences and similarities in the behaviors of the subjects.
  • As the sample becomes larger, the complete range of behaviors of translators of that text between those languages is approached.
  • A model of the mental processing underlying the translation of that text in that language combination can be inferred through a comparison and  classification of the behaviors of the sample of subjects;
  • General principles about mental processing can be extracted from analyses of specific texts and language combinations, and used as hypotheses for examining other texts and language combinations'
4. In the fourth section (Examples of choice network analysis), examples of networks are presented covering translation between Arabic and English and Spanish and English in such areas as lexis, complex noun phrases, ellipsis, and passives. The study attempt intended to identify the mental processing underlying the translation of texts by multiple subjects. The products were compared, and a number of strategies identified; these strategies deal with, among other things, the treatment of metaphors and the extent to which subjects use information beyond the level of the word to inform their choices.

5. The fifth section (Range of applications of choice network analysis) dealt with the range applications of CNA and revealed among other four major areas:
  • CNA can be used to reveal contrasts between the translatability of specific language pairs, making this an empirically based rather than a  theory-driven exercise.
  • CNA is also useful for estimating the relative difficulty of parts of source texts. 
  • CNA can also be used to compare the strategies of novice and expert translators, and those of translators into the first and second language.
  • CNA is a valuable tool for generating hypotheses about translation that can be tested by other research methods.
6. In section six (Choice network analysis and theory), Campbell explains that CNA is a theory-free approach that generates are models, i.e. representations of complex systems. The researcher is free to make these models as simple or as complex as the hypothesis under investigation demands. The power of CNA, according to Campbell, lies precisely in the fact that it provides a test bench for testing a theory. 

7. Section seven tackled Principles for building networks which include:

  • The need for the network to account for every piece of data in the sample that is relevant to the domain of the theoretical framework of the investigator.
  • The network must be linguistically plausible.
  • It must be optimally parsimonious, i.e. it should contain the minimum number of nodes and branches that will account for all the data while remaining plausible
8. Section eight (Linearity) discusses the sequence of processing in a network which is a function of two factors:
  • Text processing is basically linear as we tend to process from the beginning of a string, despite subsequent passes and post-editing.
  • Choices at any point in the string may constrain subsequent choices; these constraints are the unavoidable product of grammar.
9. The paper concludes that:
  •  CNA is an empirical research procedure that takes the approach of comparing multiple subjects' translations of the same text. 
  • It complements and, in some respects, improves on current research paradigms in translation research such as think-aloud protocols and psychological word-based experiments. 
  • The procedure has a range of applications in contrastive translation research, in the study of difficulty, and in the investigation of translation competence.
  • It is a sound procedure for generating research hypotheses, and for testing psycholinguistic theories about translation.
This paper is a required reading for the Ph.D. in Translation Studies candidacy exam (Comps) at the Institute for Applied Linguistics at Kent State University. This Xmind map (you can view and download by clicking the Xmind icon) provides a summary of the main concepts presented in this paper: 

Campbell, S. (2017). Choice network analysis in translation research. Intercultural fault lines: research models in Translation Studies I, 29-42.


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