因果强度对人们因果推理违背隔断规则的作用研究
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- 英文论文题名：The Role of Causal Strength to the Violations of Screening-off Rule in the Causal Reasoning
- 论文作者：梁渊 ; 王墨耘
- 英文论文作者：Liang Yuan ; Wang Moyun ; School of Psychology ; Shaanxi Normal University
- 年：2015
- 作者机构：陕西师范大学心理学院;
- 论文关键词：隔断规则 ; 因果强度 ; 原型信息 ; 案例
- 英文论文关键词：Screening-off rule ; Causal strength ; Prototype information ; Case
- 会议召开时间：2015-10-16
- 会议录名称：第十八届全国心理学学术会议摘要集——心理学与社会发展
- 英文会议录名称：Proceedings of the 18th National Academic Congress of Psychology
- 语种：中文
- 分类号：B842.2
- 学会代码：ZGXG
- 会议名称：第十八届全国心理学学术会议
- 会议地点：中国天津
- 主办单位：中国心理学会
- 学会名称：中国心理学会
- 页数：3
- 文件大小：767k
- 原文格式：D
- 会议级别：全国
摘要
因果贝叶斯标准模型的假设是隔断规则(the screening-off rule),它是指在一系列变量X1,X2,X3,…,Xn中,变量Xi的状态是以它的直接原因变量的状态为条件而独立于所有其他变量。具体而言,变量Xi是它的直接原因变量的函数;如果直接原因变量的状态固定,那么Xi的状态与其他变量的状态没有关系;而如果直接原因变量的状态不固定,那么Xi的状态则不一定独立于其他变量的状态(Hausman&Woodward,1999)。根据隔断规则,共同原因结构(A←B→C)中,如果原因节点B的状态固定,那么它导致的两个结果 A与C的状态是彼此独立的。链式因果结构(A→B→C)中,如果中间节点B的状态固定时,那么链式的始端A与终端C的状态也是彼此独立的。目前的大多数研究说明人们实际的因果推理会违背隔断规则,而对违背隔断规则的理论解释尚未考虑到因果强度的作用。基于此,现在的研究用2个实验考察因果强度在违背隔断规则中的作用。增加因果强度信息控制较为严格的因果关系,采用神经元、炸弹爆炸和药物引起疾病材料等二分变量构建共同原因结构和链式因果结构。实验1通过操纵原型信息(有因果关系概率信息的原型VS.无因果关系概率信息的原型)和案例变量(3/4Case1 VS.1/4Case2),检验人们的因果推理是否违背隔断规则,结果发现在两种因果结构中,被试对目标节点状态的估计受到非目标节点状态的影响,在无因果关系概率信息条件下人们估计值的差异幅度大于有因果关系概率信息条件下的差异幅度。因果强度解释对因果推理提供了最佳预测。实验2要求被试先对共同原因事件或中间节点事件发生的因果强度进行估计,再对案例中目标节点的状态进行估计,结果发现被试对目标节点主观的可能性估计、主观的因果强度估计变化和客观的因果材料设置的变化方向是相一致的。客观的因果强度设置决定了人们主观的因果强度估计,而主观的因果强度估计又决定了对案例中目标节点的估计值。在人们知觉到因果强度发生变化时,其因果推理不违背隔断规则。
Causal Bayes nets theory implies that people should follow structural constraints like the Markov property in the form of the screening-off rule. The screening-off rule follows the formulation: For any variable Xi in a set of variables X1, X2, X3,…,Xn, the state of Xi is independent of all other variables in the set conditional on its own parents(direct causes) except for its direct effects. That is, Xi is the function of its direct causes. If the state of the direct cause of Xi was fixed, then the state of this variable was not related to the states of other variables. While if the state of the direct cause of Xi was not fixed, then the state of this variable was not independent of them. In the common cause structures(A←B→C), if the state of cause node B was fixed, then the relation between the state of effect node A and C was also independent. In the chain structures(A←B→C), if the state of middle node B was fixed, then the relationship between the state of initial node A and final effect node C was also independent. Whereas the previous work showedlittle evidence that people would follow the screening-off rule, and the theories of violation did not consider the role of causal strength. We used two experiments to investigate the screening-off rule, and admitted that people use causal strength to infer the state of target node. Experiment 1 tested whether the participants would follow the screening-off rule by examining whether probability judgment of target nodes would be influenced by the state of non-target nodes given prototype information with vs. without causal probability in common cause structures and chain structures. The result showed that in the two structures given prototype information with or without causal probability, the probability judgment of target nodes would be influenced by the state of non-target nodes. The causal strength explanation could offer the best prediction for people's causal inferences. The difference magnitudes of probability judgments as the function of case variable in the prototypes without causal probability were larger than those in the prototypes with causal probability. Experiment 2 examined whether probability judgment of target nodes would be influenced by causal strength judgment of their common cause in common cause structures(or of the middle node in chain structures) given prototype information with vs. without causal probability. Experiment 2 would offer direct and specific evidence to the causal strength explanation. The results indicated that the change direction of three variables that were participants' subjective probability judgments of target nodes, their subjective probability judgments of causal strength and the provided objective causal material were consistent with each other. The findings suggested that people's causal inferences to target node would depend on the Causal strength of their direct cause node. People's causal inferences did not violate the screening-off rule.
Causal Bayes nets theory implies that people should follow structural constraints like the Markov property in the form of the screening-off rule. The screening-off rule follows the formulation: For any variable Xi in a set of variables X1, X2, X3,…,Xn, the state of Xi is independent of all other variables in the set conditional on its own parents(direct causes) except for its direct effects. That is, Xi is the function of its direct causes. If the state of the direct cause of Xi was fixed, then the state of this variable was not related to the states of other variables. While if the state of the direct cause of Xi was not fixed, then the state of this variable was not independent of them. In the common cause structures(A←B→C), if the state of cause node B was fixed, then the relation between the state of effect node A and C was also independent. In the chain structures(A←B→C), if the state of middle node B was fixed, then the relationship between the state of initial node A and final effect node C was also independent. Whereas the previous work showedlittle evidence that people would follow the screening-off rule, and the theories of violation did not consider the role of causal strength. We used two experiments to investigate the screening-off rule, and admitted that people use causal strength to infer the state of target node. Experiment 1 tested whether the participants would follow the screening-off rule by examining whether probability judgment of target nodes would be influenced by the state of non-target nodes given prototype information with vs. without causal probability in common cause structures and chain structures. The result showed that in the two structures given prototype information with or without causal probability, the probability judgment of target nodes would be influenced by the state of non-target nodes. The causal strength explanation could offer the best prediction for people's causal inferences. The difference magnitudes of probability judgments as the function of case variable in the prototypes without causal probability were larger than those in the prototypes with causal probability. Experiment 2 examined whether probability judgment of target nodes would be influenced by causal strength judgment of their common cause in common cause structures(or of the middle node in chain structures) given prototype information with vs. without causal probability. Experiment 2 would offer direct and specific evidence to the causal strength explanation. The results indicated that the change direction of three variables that were participants' subjective probability judgments of target nodes, their subjective probability judgments of causal strength and the provided objective causal material were consistent with each other. The findings suggested that people's causal inferences to target node would depend on the Causal strength of their direct cause node. People's causal inferences did not violate the screening-off rule.
引文