儿童基于心理本质论的种族认知及其影响因素

心理本质论将类别成员视为由共同的本质所决定,且这些本质对应着一些表面的不可改变的属性。其中,种族本质论就是心理本质论的一种。研究种族本质论的发展对于了解儿童的种族认知具有重要意义。种族本质论者认为,种族具有遗传不变性、有较强的归纳强度和标签具有客观性等特征。但是,基于不同特征的种族本质论的发展存在差异。类属语言、社会文化背景和群体地位,均可能影响儿童种族本质论的发展。这些影响因素提示,可通过减少类属语言的描述和促进民族融合等方式改变儿童的种族本质论。比较儿童对种族本质论的建构与自然世界的建构之间的差异,方便我们探索类别学习跨领域的一致性问题。如何确保种族本质论的发展是适宜的,这需要未来开展一些干预性的研究。     

Is teaching Jung within university possible?: a response to David Tacey

Until recently, Jungian psychology has been suspicious of academia and remained almost exclusively connected with analytical practice. Attempts by analytical psychologists towards a rapprochement have, by and large, failed because they were based either on inappropriate efforts to fit Jung within an unsuitable paradigm of science or on omnipotent expectations that academics accept the Jungian 'wisdom' unquestionably. By distinguishing two different Jungian epistemologies (an open and closed one) it is argued that the emergence of the new paradigm in social and human sciences (based on constructivist and non-essentialist ideas) offers now a unique opportunity to connect the epistemologically open Jung with these new developments in the academy. Thus, Jungians should now face the challenge of open dialogue with academics which can result in mutual benefit.     

Sociology and psychology within the scope of scientific dishonesty

A survey is undertaken based on qualitative analyses of the cases of scientific misconduct from the Danish Committee on Scientific Dishonesty’s first five years of collecting data, with additional information from selected international sources, in which underlying psychological motivations can be judged. An carlier version of this paper was presented at a symposium, Scientific Misconduct. An International Perspective, organised by The Medical University of Warsay, 16 November, 1998.     

Values and Science: An Argument for Why They Cannot Be Separated

A distinction between facts and values is often assumed when people in the modern West talk about science. The biologist Stephen Gould, for example, famously argued that religion covers questions of meaning and moral value, but science deals with empirical facts. This paper challenges the traditional fact/value distinction by questioning the presuppositions about science upon which it depends. It begins by describing the origins of the fact/value distinction in the Scientific Revolution and then gives three reasons for the inseparability of facts and values in scientific inquiry, drawing upon themes from the “practice turn” in recent scholarship on the sciences.     

Kuhnian Revolutions Revisited

I re-examine Kuhn’s account of scientific revolutions. I argue that the sorts of events Kuhn regards as scientific revolutions are a diverse lot, differing in significant ways. But, I also argue that Kuhn does provide us with a principled way to distinguish revolutionary changes from non-revolutionary changes in science. Scientific revolutions are those changes in science that (1) involve taxonomic changes, (2) are precipitated by disappointment with existing practices, and (3) cannot be resolved by appealing to shared standards. I argue that an important and often overlooked dimension of the Kuhnian account of scientific change is the shift in focus from theories to research communities. Failing to make this shift in perspective might lead one to think that when individual scientists change theories a scientific revolution has occurred. But, according to Kuhn, it is research communities that undergo revolutionary changes, not individual scientists. I show that the change in early modern astronomy is aptly characterized as a Kuhnian revolution.     

"What if…": The Use of Conceptual Simulations in Scientific Reasoning

The term conceptual simulation refers to a type of everyday reasoning strategy commonly called "what if" reasoning. It has been suggested in a number of contexts that this type of reasoning plays an important role in scientific discovery; however, little direct evidence exists to support this claim. This article proposes that conceptual simulation is likely to be used in situations of informational uncertainty, and may be used to help scientists resolve that uncertainty. We conducted two studies to investigate the relationship between conceptual simulation and informational uncertainty. Study 1 was an in vivo study of expert scientists; the results suggest that scientists do use conceptual simulation in situations of informational uncertainty, and that they use conceptual simulation to make inferences from their data using the analogical reasoning process of alignment by similarity detection. Study 2 experimentally manipulated experts' level of uncertainty and provides further support for the hypothesis that conceptual simulation is more likely to be used in situations of informational uncertainty. Finally, we discuss the relationship between conceptual simulation and other types of reasoning using qualitative mental models.     

Private Interests Count Too

Along with concerns about the deleterious effects of politically driven government intervention on science are the intrusion of private sector interests into the conduct of research and the reporting of its results. Scientists are generally unprepared for the challenges posed by private interests seeking to advance their economic, political, or ideological agendas. They must educate and prepare themselves for assaults on scientific freedom, not because it is a legal right, but rather because social progress depends on it.

Building to discover: a common coding model

I present a case study of scientific discovery, where building two functional and behavioral approximations of neurons, one physical and the other computational, led to conceptual and implementation breakthroughs in a neural engineering laboratory. Such building of external systems that mimic target phenomena, and the use of these external systems to generate novel concepts and control structures, is a standard strategy in the new engineering sciences. I develop a model of the cognitive mechanism that connects such built external systems with internal models, and I examine how new discoveries, and consensus on discoveries, could arise from this external-internal coupling and the building process. The model is based on the emerging framework of common coding, which proposes a shared representation in the brain between the execution, perception, and imagination of movement.