Finding reliable data analysis support for my Translation Studies dissertation

[HaroldJimen]

Recently, as a doctoral student deeply engrossed in the intricate world of Translation Studies, I found myself facing an unexpected hurdle in my research journey. While delving into cross-sectional analysis for my dissertation on Literary Translation and Cultural Transfer, I have unexpectedly struggled to find reliable data analysis support that aligns with the essence of textual fidelity and cultural adaptation - foundational aspects of my study within Translation Methods and Cultural Studies.

The need for robust data analysis methods that capture the nuances of translation theory while upholding the integrity of cultural transfer is paramount in ensuring the scholarly rigor of my research focused on literary translation. In light of this dilemma, I am earnestly seeking guidance from fellow scholars grappling with similar issues.

How can one effectively balance the intricacies of textual fidelity and cultural adaptation in data analysis methods for Translation Studies dissertations, particularly those centered on literary translation? Are there specific methodologies or tools that have proven effective in addressing these multifaceted concerns? As I navigate this unanticipated roadblock in my academic journey, any insights or suggestions from the esteemed members of this forum would be immensely appreciated.

 

[Samuel]

Your situation really resonates with me as I'm facing a similar challenge with my own research!

I'm actually a Master's student in Applied Linguistics, and I've been wrestling with how to analyze translation choices qualitatively without losing the cultural context. Have you considered using corpus-based tools like Sketch Engine or AntConc? They can help track patterns in word choice across translations while you maintain focus on cultural adaptation through close reading.

Also, maybe try thematic analysis with NVivo—it lets you code both linguistic features AND cultural elements side by side. This way, you're not sacrificing textual fidelity for statistical rigor. What theoretical framework are you using? That might guide which methods fit best. Hang in there—this is the messy but meaningful part of research!