Meaning-Making in Cross-Language Research: The Dialogic-Differentiated Translation (DDT) as a Qualitative Method for (Re)interpreting China’s Nation-Building Discourse

Conducting cross-language qualitative research involves translating textual and interview data. Often, translation is treated as an adjunct to data collection and analysis, undervaluing its role in shaping interpretations of findings. This article presents Dialogic-Differentiated Translation (DDT), a distinct qualitative method inspired by Bakhtin’s concept of dialogism, Derrida’s concept of différance, and Hermans’ concept of the dialogical self. DDT emphasizes differentiation and dialogue, including self-dialogue, highlighting the meaning-making process of translation. Rather than basing interpretations on a single translation, DDT shows that interpretations should stem from the meaning-making possibilities ignited and inhabited by contexts. DDT meets all five qualitative method criteria and follows a non-discrete, 4-Stage, 6-Step procedure: (1) searching and documenting, (2) retranslating and differentiating, (3) elucidating and dialoguing, and (4) evaluating and reflecting. The 6 steps enhance DDT’s traceability and audibility. Step 2 applies semantic, intent, and sentiment annotations to help reach translation exhaustion. Step 3 applies annotations to specify translation approaches. Step 5 applies dialogue-targeting annotations. Step 6 uses inter-reflexive annotations to help employ DDT in collaborative research. With those steps, DDT enables more nuanced interpretations of cross-language textual and (potentially) interview data. This is demonstrated in an illustrative case that shows how to reinterpret China’s nation-building discourse. Potentially, DDT would lay the first stepping stone to having multimodal artificial intelligence (AI) considered in cross-language data analysis and interpretation.