The study
Verbal Dimensions of Gender-Equality in Contemporary Speech Forms: Issues and Opportunities. OIDA International Journal of Sustainable Development, Vol. 18(11), pp. 321–330 (2025). A comparative linguistic study of gender-inclusive language strategies in English and Ukrainian, using grounded theory, content analysis, and discourse analysis across official, scientific, and public communication.
Five co-authors from four institutions took part, including Sumy State Pedagogical University and Igor Sikorsky Kyiv Polytechnic Institute.
How Evidano fit the workflow
The publication describes a sequential, AI-assisted grounded theory workflow.
- 1Identify initial categories
At the first stage of sample formation, the authors applied Evidano to surface initial categories from the source pool.
- 2Refine search and selection
Those categories guided the final literature search and selection, reaching a sample of 35 sources.
- 3Researchers interpret
Pairing grounded theory and content analysis with the AI tool, the authors report it contributed to reducing internal bias, leaving interpretation to the researchers.
“At the first stage of sample formation, we applied AILYZE – AI-based software tool for grounded theory research. This allowed us to identify initial categories for further search.”
“The categories obtained with the help of AILYZE were used for final search and selection of literature.”
“The sequential use of grounded theory and content analysis, supported by an AI-based solution, helped to eliminate inherent biases in the publications.”
The workflow shift
Manual scanning of every source. Categories shaped by prior assumptions. Slow preliminary coding. Higher risk of internal bias.
AI-assisted initial categorisation. Data-driven initial categories. Automated preliminary coding. Reported support for bias reduction.
The AI tool was named transparently in a published methods section.
Researchers kept critical thinking and interpretation in their own hands.
Described as an AI-based software tool for grounded theory research.
The authors report the AI-backed workflow helped reduce internal bias.