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Use when conducting member checking or participant validation to enhance credibility of qualitative findings.
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SOC 職業分類に基づく
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 | member-checking |
| description | Use when conducting member checking or participant validation to enhance credibility of qualitative findings. |
Member checking invites participants to review or react to researcher representations of their experience. Done well, it can deepen interpretation; done poorly, it can confuse empirical grounding with consensus or epistemic authority.
A structured process where participants engage with transcripts, themes, interpretations, or draft findings and provide feedback. It is not a statistical validation step; it is a dialogic or confirmatory practice depending on design.
Each type serves different goals: accuracy vs meaning vs overall story fidelity.
Glaser cautions against letting participants define theory or veto concepts that fit data but feel uncomfortable. In classic GT, the analyst earns categories through constant comparison, not through participant sign-off as a gold standard. This does not forbid member checks—it warns against substituting participant agreement for theoretical elaboration.
Appropriate when: factual accuracy matters; collaborative ethics prioritize shared sense-making; stakeholder feedback improves practice or implementation; you need to catch misreadings of local language or norms.
Risky when: power dynamics make “agreement” coerced; revising interpretations to please gatekeepers would misrepresent data; revisiting traumatic content harms participants without benefit; institutional timelines pressure shallow “checkbox” validation.
Disagreement is data: it may signal variation, identity performance, positional difference, or analytic error. Do not automatically overwrite analysis. Instead, compare the disagreement against the full corpus, seek negative cases, and document your reasoning.
Re-contacting may re-trigger harm; obtain ongoing consent. Be transparent that you cannot guarantee confidentiality if others helped produce the original account. For group contexts, avoid exposing one participant’s statements to another without consent.
Describe: who was invited; response rate; what materials they saw; how feedback altered (or did not alter) analysis and why. In GT, explain how member checking complemented rather than replaced constant comparison.
