Evaluating complex social interventions in a complex world
Evaluating complex social interventions in a complex world
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DOI：
10.1177/1356389013495617
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发表时间：
2013-07-01
期刊：
影响因子：
2.4
通讯作者：
Byrne, David
中科院分区：
文献类型：
--
作者：
Byrne, David
社会世界是复杂和紧急的。以建立普遍的经验规律为目的的探究（即本体探究），无法在这样一个世界中建立因果关系。如果不评估干预的整个背景，我们永远不能给任何干预分配因果效应。然而，如果我们采用的研究方法既能认识到将因果力量分配给情境的含义（现实主义采取评估的本质），也能认识到与“因果关系的社会类型”相关的人类能动性的重要性，我们就能发展出可概括的知识。有一些文献可以帮助我们发展这样的知识。这包括宏观政治学对时间顺序对结果的重要性的关注；拉金对因果关系的集合论理解及其系统比较理论的发展，为定性比较分析（QCA）解释因果关系奠定了基础；以及作为过程追踪基础的因果叙述的呈现。每一个复杂的社会干预都必须被视为一个“案例”。跨案例的系统比较使我们能够在有限的范围内进行概括——但这仍然意味着我们可以将知识转移到独特的表意文字描述的实例之外。我们永远不能通过使用随机对照试验（RCTs）等基于变量的方法来建立复杂系统中因果关系的普遍/规整性解释。然而，通过对复杂偶然因果关系的仔细比较和探索，我们可以开始掌握什么在哪里（在什么上下文中），什么时候（在什么时间上下文中）以及以什么顺序起作用。
The social world is complex and emergent. Inquiry, directed towards establishing universal empirical regularities (i.e. nomothetic inquiry), cannot establish causality in such a world. We can never assign a causal effect to any intervention without assessing the whole context of that intervention. However, we can develop generalizable knowledge if we adopt research approaches that recognize both the implications of assigning causal powers to context (the essence of the realist take on evaluation) and the significance of human agency in relation to 'the social type of causal nexus'. There are literatures that can contribute to developing such knowledge. These include macro-political science's concern with the importance of temporal ordering in relation to outcomes; Ragin's set theoretic understanding of causal relations and his development of systematic comparison as a basis for explicating those relations through Qualitative Comparative Analysis (QCA); and the presentation of causal narratives as foundation for process tracing. Every complex social intervention has to be considered as a 'case'. Systematic comparison across cases allows us to generalize within limits - but this still means we can transfer knowledge beyond the unique ideographically described instance. We can never establish universal/nomothetic accounts of causality in complex systems by using variable-based methods such as Randomized Controlled Trials (RCTs). However, through careful comparison and exploration of complex contingent causation, we can begin to get a handle on what works where (in what context), when (in what temporal context), and in what order.