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Use when selecting sampling strategies for qualitative research — purposeful, theoretical, snowball, criterion, maximum variation.
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基于 SOC 职业分类
Use when writing academic prose for qualitative research — findings, methods, discussion sections with appropriate voice and conventions.
Use when conducting participatory action research (PAR) involving collaborative inquiry, cycles of action and reflection.
Use when formatting academic work in APA 7th edition style — citations, references, headings, tables, and manuscript structure.
Use when designing or conducting case study research following Yin's multiple case study methodology or Stake's approach.
Use when developing and densifying categories with properties, dimensions, conditions, and consequences.
Use when formatting academic work in Chicago/Turabian style — notes-bibliography or author-date systems.
| name | sampling-strategies |
| description | Use when selecting sampling strategies for qualitative research — purposeful, theoretical, snowball, criterion, maximum variation. |
Qualitative sampling prioritizes information-rich cases and analytic progression over statistical representativeness. Your sampling chapter should explain logic, not pretend to randomize for generalization in a positivist sense.
Purposeful sampling selects cases that illuminate the phenomenon intensely. Common variants:
After initial coding, theoretical sampling seeks data to elaborate properties, dimensions, conditions, and consequences of emerging categories. You sample for analytic gaps, not demographic quotas (unless demographics are theoretically relevant). The question is: “What data do I need next to develop this category?”
Use when populations are hard to reach or trust is network-based. Mitigate bias from seed participants by using multiple entry points and monitoring whose voices dominate. Document referral chains in audit materials.
Maximum variation guards against provincial theory; typical case helps communicate mundane patterning. In GT, these are tools in service of emergent categories—choose based on what the evolving theory demands.
Convenience sampling is acceptable only when limitations are transparent and you take compensatory steps (prolonged engagement, triangulation, negative case search). Never dress convenience up as theoretical sampling without analytic justification.
“How many?” depends on study scope, data richness, and saturation. A focused GT project may achieve workable saturation with fewer cases if incidents are dense; a comparative multi-site study may need many more. Report saturation reasoning and disconfirming efforts, not a fake power analysis.
Saturation means no new properties/dimensions are emerging for a category (in the Glaserian sense), not mere repetition of wordings. Track saturation by category, not only globally—some categories saturate early while others remain thin.
In proposals, distinguish initial purposeful sampling (who can get you started) from later theoretical sampling (who/what you need next as categories form). This shows methodological maturity in GT.
