Epistemic Landscapes: Models of Cognitive Labor

认知景观：认知劳动模型

• 批准号: 0957189
• 负责人: Michael Weisberg
• 金额: $ 15.59万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0957189&HistoricalAwards=false
• 关键词: Epistemic; Landscapes; Models; Cognitive; Labor

The PI will use computational models of the social structure of science to study several issues associated with the division of cognitive labor. Those issues include the following. How do individual scientists allocate their cognitive labor given research costs and limited access to information? How does drawing on the cognitive resources of the scientific community enhance or retard the discovery of significant truths? How should the scientific community as a whole optimally allocate its cognitive labor?The notion of the division of cognitive labor may be characterized as follows. Scientists are not lone agents, cut off from the outside world, responding only to information generated in their laboratories. Rather, they make decisions about what to investigate by integrating what they discover for themselves with what they learn from others. They also take into account external factors such as grants, prizes, and prestige. This feedback leads scientists to divide their resources among differing approaches to studying phenomena of interest. While this coordination is neither planned nor explicit, it seems to enhance the ability of scientific communities to discover significant, true things about the world. Although the results of this research project will primarily contribute to the philosophy of science literature, it has three major areas of potential broader impact. First, it will involve training undergraduate students in the use of computational modeling to investigate philosophical problems. Second, while the models developed in this project are not appropriate for making direct policy advice, they can investigate sets of incentives that would change the division of cognitive labor in more epistemically productive ways. Finally, the project will generate materials that can be reformulated for use in secondary and higher education with the goal of making citizens more informed consumers of science, especially in fields such as evolution and climate modeling where critics prey on public misunderstanding of how theories are tested.

PI将使用科学社会结构的计算模型来研究与认知劳动分工相关的几个问题。这些问题包括以下内容。考虑到研究成本和有限的信息获取途径，科学家个体如何分配他们的认知劳动？利用科学界的认知资源是如何促进或阻碍重要真理的发现的？科学界作为一个整体应该如何最优地分配其认知劳动？认知劳动分工的概念可以概括如下。科学家不是孤立的代理人，与外界隔绝，只对实验室里产生的信息作出反应。相反，他们通过整合自己的发现和从别人那里学到的东西来决定调查什么。他们还考虑了外部因素，如补助金、奖品和声望。这种反馈导致科学家将他们的资源分配给不同的方法来研究感兴趣的现象。虽然这种协调既没有计划也没有明确，但它似乎增强了科学界发现世界上重要而真实事物的能力。虽然这个研究项目的结果将主要有助于科学文献的哲学，它有三个主要领域的潜在更广泛的影响。首先，它将包括训练本科生使用计算建模来研究哲学问题。其次，虽然本项目中开发的模型不适合直接提出政策建议，但它们可以研究以更有认识生产力的方式改变认知劳动分工的激励机制。最后，该项目将生成可用于中等和高等教育的材料，其目标是使公民成为更知情的科学消费者，特别是在进化论和气候模型等领域，批评者利用公众对理论测试方式的误解。