درخت حوزه‌های تخصصی

The extensive training data of ChatGPT has facilitated theorizing in the field of Translation Studies, particularly during the cultural turn. Following this theorizing, a standardization framework was proposed. This study employed a qualitative and interdisciplinary approach, utilizing a descriptive method to interpret the data. The validated questions were based on the works of theorists associated with the cultural turn. Two scholars participated in structured and semi-structured interviews, employing a three-point Likert scale to capture their opinions on the proposed theory. Data analysis focused on the accuracy of ChatGPT-4’s responses in relation to the scholars’ opinions and references. The findings associated with the Likert scale were linked to task-oriented benchmarks, including factual/contextual understanding, coherence, and resolution of ambiguity. The results indicated a 29.3% weakness in ChatGPT-4’s data analysis. The resolution of ambiguity resulted in a total of neutral responses at 44.8%. Scholars unanimously endorsed the cultural interaction theory, demonstrating a 100% capacity for theorizing by ChatGPT-4. In terms of coherence and summarization, the data suggested a stronger correlation with prompt engineering. The potential for theorizing concerning existing theory was found to be 77.7%, while the standard of theorizing by ChatGPT-4 was assessed at 68.9%. Surah Al-Fatiha was selected to exemplify cultural translation according to CIT, illustrating the theory’s effectiveness in translating cultural-ideological texts. A comparison of ChatGPT-4’s translations with those of six Quranic translators underscored its synthesizing abilities, with the incorporation of cultural interaction theory into prompts significantly enhancing its translation skills.