AI, Social Justice, and Methodological Integrity in Qualitative Research Across Linguistic and Cultural Contexts

Closes:
Journal
Qualitative Research Journal
Guest editor(s)
Shuangyu Li, Edward Ademolu, Sandro Radovanović,

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Introduction

Aim: This special issue advances methodological clarity on how artificial intelligence (AI) reshapes the production, interpretation, and validation of qualitative knowledge across linguistic and cultural contexts. Moving beyond abstract ethical debate, it centres on research design, methodological reflexivity, and innovation. We invite empirical studies, methodological frameworks, validation protocols, hybrid human–AI workflows, cross-linguistic interpretation, translation fidelity, interpretive limits, and governance practices. The issue foregrounds linguistic inequality, as AI tools provide uneven support across languages. We seek international perspectives on how researchers mobilise AI despite infrastructural and linguistic constraints and how methodological innovation can mitigate exclusion, including co-design with Indigenous and Global South researchers to amplify marginalised voices and counter-narratives. The aim is practicable, internationally grounded standards for responsible AI-assisted qualitative inquiry. 

Originality: AI-assisted qualitative analysis is expanding rapidly, yet scholarship often polarises between technological optimism and broad ethical critique. Sustained methodological work on cross-linguistic and cross-cultural qualitative inquiry remains limited, especially under uneven infrastructures and linguistic inequality. This issue advances a decolonial approach by foregrounding co-designed architectures with Indigenous and Global South researchers and treating linguistic inequality as a structural design problem. It focuses on methodological integrity in practice and epistemic justice with empirical accounts of how researchers mobilise AI under constraints. Its originality lies in linking social justice directly to research design, validation standards, and methodological solutions rather than general ethical commentary. 

Topicality: Large language models now support transcription, translation, coding, summarisation, and thematic analysis (Riisla & Gruda, 2025; Cook et al., 2025). Evidence suggests they perform reliably for descriptive coding but struggle with culturally embedded, context-dependent meaning, particularly in non-English datasets (Sakaguchi et al., 2025). Reviews show training-data imbalance and dominant-language bias shape outputs, raising concerns about epistemic inequality and cognitive imperialism (Maurya et al., 2025; Jiang et al., 2025). Although AI is promoted as scalable for low-resource settings, uneven infrastructure and language support can reinforce hierarchies of knowledge production (Isangula, 2025). Methodological standards for cross-linguistic validity, decolonial tool design, and AI-augmented epistemic justice are urgently needed. 

Impact: This issue addresses societal challenges in epistemic justice, digital inequality, and responsible AI development. Qualitative research informs policy, organisational practice, and public discourse. When AI-assisted methods misinterpret culturally situated narratives or under-serve linguistic groups, distorted findings can reinforce inequality. Conversely, culturally grounded and rigorously validated AI-assisted approaches can expand inclusion by enabling multilingual, cross-contextual analysis and amplifying marginalised voices and counter-narratives.​

List of Topic Areas
  1. ​​​Human-in-the-loop approaches for AI-assisted qualitative analysis  
  2. Translation and cross-linguistic interpretation: preventing losing culturally embedded meaning in AI-assisted analysis
  3. Participatory and community-led AI governance and co-designed research protocols
  4. Infrastructure inequalities and AI adoption in low-resource settings
  5. Transparent reporting standards and audit trails for AI-assisted qualitative research ​​ 
Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here: https://mc.manuscriptcentral.com/qrjnl 
Author guidelines must be strictly followed. Please see here: https://www.emeraldgrouppublishing.com/journal/qrj 
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”. 
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key Deadlines

Closing date for abstract submission: ​01/03/2027​    
Email for abstract submissions: ​​Shuangyu Li shuangyu.li@kcl.ac.uk; Edward Ademolu edward.ademolu@kcl.ac.uk, Sandro Radovanović sandro.radovanovic@fon.bg.ac.rs   

Closing date for manuscripts submission  ​01/09/2026​