Models of causation and the semantics of causal verbs

This research examines the relationship between the concept of CAUSE as it is characterized in psychological models of causation and the meaning of causal verbs, such as the verb cause itself. According to focal set models of causation (; ), the concept of CAUSE should be more similar to the concepts of ENABLE and PREVENT than either is to each other. According to a model based on theory of force dynamics, the force dynamic model, the concepts of CAUSE, ENABLE, and PREVENT should be roughly equally similar to one another. The relationship between these predictions and the meaning of causal verbs was examined by having participants sort causal verbs and rate them with respect to the dimensions specified by the two models. The results from five experiments indicated that the force dynamic model provides a better account of the meaning of causal verbs than do focal set models of causation. Implications for causal inference and induction are discussed.     

对精准医学批评的辨析

首先澄清我国网站上发表的两篇有关精准医学博文中事实上的错误和概念上的混淆。接着讨论了对精准医学提出的批评及对这些批评的分析。指出精准医学术语本身容易引起误解和引起人们过高的期望;对精准医学的论述和实施中存在基因决定论倾向, 即过分夸大基因在健康和疾病中的作用, 而忽视环境、生活方式、社会因素的作用, 这在政策上就会导致在发展高端医学与发展大众医学上不能保持平衡的问题;将巨大的资源投入精准医学研究未进行认真的成本-效果分析, 也未考虑到精准医学研究成果的公平可及, 以避免加深社会不公正问题;最后, 在吸引商家参与精准医学研究计划时未考虑如何力求避免可能引起的利益冲突问题。     

高自尊的异质性研究述评

自尊不只有高低之分,很多研究者分别从实证研究的结果矛盾性、对自尊的概念及其测量方法的理论思考等方面论述了高自尊异质性存在的可能性,并分别从不同角度提出了高自尊的不同类型及其测量方法,如,不稳定的高自尊与稳定的高自尊、防御的高自尊与真诚的高自尊、相倚的高自尊与真正的高自尊、高外显低内隐自尊与高外显高内隐自尊、脆弱的高自尊与安全的高自尊等,其测量方法也因不同类型而不同。这些研究均说明高自尊存在异质性,需在未来的自尊研究中加以注意     

Two metamodels of causal effects

Two metamodels, termed Model S and Model V, are proposed for definition, measurement, and generalization of quantitative causal effects. The effect is defined as a part change in score in Model S and as a part change in variance in Model V. Two additional changes, total and remainder change, are defined. The latter is due to all other factors or variables than the cause, while total change is the sum of remainder and effect change. Furthermore, it is shown how contrafactual concepts, which imply that some parts of the study situation are supposed to be otherwise, enter into the metamodels. Casual effects are defined and measured in terms of non-contrafactual concepts, except that statistical induction includes contrafactual as well as non-contrafactual inferences. Non-statistical generalization involves both kinds of inferences. Contrafactual definitions are considered inadequate, and a contrafactual interpretation of statistical adjustment is unnecessary and should be replaced by a non-contrafactual one.