Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сравнительная автоэтнография× | Рефлексивный тематический анализ× | |
|---|---|---|
| Область | Качественные методы | Качественные методы |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1979 (autoethnography); comparative application formalized ~2013 | 2006 (seminal paper); explicitly named 'reflexive' from ~2019 |
| Автор метода≠ | Hayano (term); developed further by Ellis, Bochner, Chang, Ngunjiri & Hernandez | Virginia Braun & Victoria Clarke |
| Тип≠ | Qualitative research design | Qualitative research method |
| Основополагающий источник≠ | Chang, H., Ngunjiri, F. W., & Hernandez, K.-A. C. (2013). Collaborative Autoethnography. Left Coast Press. ISBN: 978-1598745948 | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ |
| Другие названия | collaborative autoethnography, multi-sited autoethnography, cross-cultural autoethnography, CAE | RTA, reflexive TA, Braun and Clarke thematic analysis, qualitative thematic analysis |
| Связанные | 6 | 6 |
| Сводка≠ | Comparative autoethnography is a qualitative design in which two or more researchers — or research participants — independently produce first-person self-narratives about a shared phenomenon and then systematically compare those accounts to generate broader cultural insight. By juxtaposing lived experiences that differ by context, identity, or setting, the approach moves beyond the single-voice limitations of traditional autoethnography while retaining its hallmark reflexivity and personal depth. | Reflexive Thematic Analysis (RTA) is a widely used qualitative method for identifying, analysing, and interpreting patterns of shared meaning — called themes — across a dataset. Developed by Virginia Braun and Victoria Clarke, it is theoretically flexible, works across epistemological positions, and foregrounds the researcher's active, interpretive role rather than treating themes as features that simply emerge from data. It differs from older 'codebook' approaches by treating the analyst's subjectivity as a resource rather than a source of bias to be suppressed. |
| ScholarGateНабор данных ↗ |
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