This paper proposes an extended version of the interventionist account for causal inference in the practical context of biological mechanism research. This paper studies the details of biological mechanism researchers’ practices of assessing the evidential legitimacy of experimental data, arguing why quantity and variety are two important criteria for this assessment. Because of the nature of biological mechanism research, the epistemic values of these two criteria result from the independence both between the causation of data generation and the causation in question and between different interventions, not techniques. The former independence ensures that the interventions in the causation in question are not affected by the causation that is responsible for data generation. The latter independence ensures the reliability of the final mechanisms not only in the empirical but also the formal aspects. This paper first explores how the researchers use quantity to check the effectiveness of interventions, where they at the same time determine the validity of the difference-making revealed by the results of interventions. Then, this paper draws a distinction between experimental interventions and experimental techniques, so that the reliability of mechanisms, as supported by the variety of evidence, can be safely ensured in the probabilistic sense. The latter process is where the researchers establish evidence of the mechanisms connecting the events of interest. By using case studies, this paper proposes to use ‘intervention’ as the fruitful connecting point of literature between evidence and mechanisms.

本文提出了在生物机制研究的实际背景下进行因果推断的干预主义解释的扩展版本。本文研究了生物机制研究人员评估实验数据证据合法性的实践细节，论证了为什么数量和多样性是这种评估的两个重要标准。由于生物机制研究的性质，这两个标准的认知价值源于数据产生的因果关系和所讨论的因果关系之间以及不同干预措施之间的独立性，而不是技术。前一种独立性确保对相关因果关系的干预不受负责数据生成的因果关系的影响。后者的独立性不仅在经验方面而且在形式方面确保了最终机制的可靠性。本文首先探讨了研究人员如何使用数量来检验干预的有效性，同时确定干预结果所揭示的差异化的有效性。然后，本文对实验干预和实验技术进行了区分，以便在各种证据的支持下，在概率意义上可以安全地确保机制的可靠性。后一个过程是研究人员建立连接感兴趣事件的机制的证据。通过案例研究，本文建议使用“干预”作为文献在证据和机制之间富有成效的连接点。