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Apply grounded theory for theory development from data. Process following Charmaz constructivist approach: 1. Theoretical sampling: purposeful sampling to develop theory, not for generalization. 2. Initial coding: line-by-line coding to stay close to data, use gerunds (action words). 3. Focused coding: select most significant initial codes, test against more data. 4. Theoretical coding: specify relationships between categories, identify core category. 5. Memo writing: capture thoughts about codes, categories, relationships throughout process. 6. Theoretical saturation: continue sampling until no new insights emerge. 7. Literature integration: compare emerging theory with existing literature at end. Constant comparative method: compare data to data, data to codes, codes to categories. Use theoretical sensitivity to see conceptual possibilities in data.
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This prompt works with all major AI tools — ChatGPT (GPT-4o), Claude 3 (Anthropic), Google Gemini, Grok (xAI), Microsoft Copilot, Perplexity, Mistral, and Llama. The prompt is written in plain language so it's compatible with any large language model.