Applying Ragin's Crisp and Fuzzy Set QCA to Large Datasets: Social Class and Educational Achievement in the National Child Development Study
Applying Ragin's Crisp and Fuzzy Set QCA to Large Datasets: Social Class and Educational Achievement in the National Child Development Study
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将 Ragin 的清晰模糊集 QCA 应用于大型数据集：国家儿童发展研究中的社会阶层和教育成就
DOI：
10.5153/sro.1068
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发表时间：
2005
影响因子：
1.6
通讯作者：
B. Cooper
中科院分区：
文献类型：
--
作者：
B. Cooper
本文探讨了查尔斯·拉金的定性比较分析(QCA)在其清晰版本和模糊集版本中的应用，以研究社会阶层起源、性别、能力和后续教育成就之间的关系。报告的工作是一个更大的正在进行的项目的一部分，该项目正在使用QCA来比较两个出生队列中的这些关系。这里的数据来自英国国家儿童发展研究，即来自1958年出生的儿童。这篇论文有一个方法论的重点，提出了优势，但也出现了困难时，使用QCA与这种类型的大型数据集。特别地，说明了在没有详细案例知识的情况下模糊集隶属度的校准问题。它还显示了如何使用Ragin的FS/QCA软件逐步增加的阈值，可以揭示各种因素在解释成绩方面的相对重要性。基于QCA的分析表明，教育成就的过程充其量只能被视为部分属于“精英管理”的描述。这也是希望这篇论文将作为一个有用的介绍QCA的潜力，为读者还不熟悉它。
The paper explores the use of Charles Ragin's Qualitative Comparative Analysis (QCA) in both its crisp and fuzzy set versions in the study of the relations between social class origin, sex, ‘ability’ and subsequent educational achievement. The work reported is part of a larger ongoing project which is employing QCA to compare these relations within two birth cohorts. Here data are used from the British National Child Development Study, i.e. from children born in 1958. The paper has a methodological focus, bringing out the strengths but also the difficulties that arise when employing QCA with a large dataset of this type. In particular, the problem of calibrating membership in fuzzy sets in a context where detailed case knowledge is not available is illustrated. It is also shown how the use of gradually increasing thresholds with Ragin's fs/QCA software can bring out the relative importance of various factors in accounting for achievement. The QCA-based analysis suggests that the processes of educational attainment can, at best, only be seen as partly falling under a ‘meritocratic’ description. It is also hoped that this paper will serve as a useful introduction to the potential of QCA for readers not yet familiar with it.