Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Извадка на отклоняващи се случаи в естествена среда× | Избор на отклоняващи се случаи× | |
|---|---|---|
| Област | Методология на проучванията | Методология на проучванията |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1980s–1990s (purposive/deviant case sampling literature) | 1990 |
| Създател≠ | Michael Quinn Patton; Yvonna Lincoln & Egon Guba | Michael Quinn Patton |
| Тип | Purposive qualitative sampling strategy | Purposive qualitative sampling strategy |
| Основополагащ източник | Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage Publications. ISBN: 978-0761919711 | Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage Publications. ISBN: 978-0761919711 |
| Други названия | field deviant case sampling, outlier case sampling in field research, extreme case sampling in fieldwork, in-situ deviant case sampling | extreme case sampling, outlier sampling, negative case sampling, deviant-case selection |
| Свързани | 5 | 5 |
| Резюме≠ | Field-based deviant case sampling is a purposive strategy that deliberately selects cases deviating markedly from an established pattern or norm, with data collected through direct fieldwork — observation, in-situ interviews, and ethnographic engagement — in the participants' natural settings. By studying outliers on-site, researchers gain contextually grounded insight into why and how certain cases diverge from the typical pattern. | Deviant case sampling is a purposive qualitative sampling strategy in which the researcher intentionally selects cases that are unusual, exceptional, or markedly different from the norm — outliers, extreme successes, or conspicuous failures. The goal is not statistical representation but deep learning from cases that illuminate the boundaries of a phenomenon, challenge prevailing assumptions, or reveal processes that typical cases obscure. |
| ScholarGateНабор от данни ↗ |
|
|