定性研究
饱和(图论)
认识论
社会学
透明度(行为)
可转让性
扎根理论
论证(复杂分析)
数据科学
计算机科学
社会科学
数学
生物
生物化学
机器学习
组合数学
罗伊特
哲学
计算机安全
作者
Michelle O’Reilly,Nicola Parker
标识
DOI:10.1177/1468794112446106
摘要
Measuring quality in qualitative research is a contentious issue with diverse opinions and various frameworks available within the evidence base. One important and somewhat neglected argument within this field relates to the increasingly ubiquitous discourse of data saturation. While originally developed within grounded theory, theoretical saturation, and later termed data/thematic saturation for other qualitative methods, the meaning has evolved and become transformed. Problematically this temporal drift has been treated as unproblematic and saturation as a marker for sampling adequacy is becoming increasingly accepted and expected. In this article we challenge the unquestioned acceptance of the concept of saturation and consider its plausibility and transferability across all qualitative approaches. By considering issues of transparency and epistemology we argue that adopting saturation as a generic quality marker is inappropriate. The aim of this article is to highlight the pertinent issues and encourage the research community to engage with and contribute to this important area.
科研通智能强力驱动
Strongly Powered by AbleSci AI