Expertise and category-based induction.
Expertise and category-based induction.
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专业知识和基于类别的归纳。
DOI：
10.1037//0278-7393.26.4.811
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Medin,DL
中科院分区：
文献类型：
--
作者：
Proffitt,JB;Coley,JD;Medin,DL
作者研究了一个领域内专家的归纳推理。三种类型的树木专家（园艺师、分类学家和公园维护人员）完成了3个推理任务。在实验1中，参与者推断出两种新疾病中哪一种会影响“更多其他种类的树木”，并为他们的选择提供理由。在实验2中，作者使用了修改后的指令，并询问哪种疾病更有可能影响“所有的树木”。在实验3中，结论类别被完全取消，参与者被要求生成其他受影响树木的列表。在这些种群中，典型性和多样性效应较弱或不存在。相反，专家的推理受到“局部”覆盖范围（将财产扩展到同一民间家庭成员）和因果生态因素的影响。作者得出的结论是，领域知识导致使用各种推理策略，而不是当前基于类别的归纳模型所捕获的。（PsycINFO数据库记录(c) 2016 APA，版权所有）
The authors examined inductive reasoning among experts in a domain. Three types of tree experts (landscapers, taxonomists, and parks maintenance personnel) completed 3 reasoning tasks. In Experiment 1, participants inferred which of 2 novel diseases would affect" more other kinds of trees" and provided justifications for their choices. In Experiment 2, the authors used modified instructions and asked which disease would be more likely to affect" all trees." In Experiment 3, the conclusion category was eliminated altogether, and participants were asked to generate a list of other affected trees. Among these populations, typicality and diversity effects were weak to nonexistent. Instead, experts' reasoning was influenced by" local" coverage (extension of the property to members of the same folk family) and causal-ecological factors. The authors concluded that domain knowledge leads to the use of a variety of reasoning strategies not captured by current models of category-based induction.(PsycINFO Database Record (c) 2016 APA, all rights reserved)