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The limitations and extent of category generalization within a partially learned hierarchical structure

Description
Most people are experts in some area of information; however, they may not be knowledgeable about other closely related areas. How knowledge is generalized to hierarchically related categories was explored. Past work has found little to no generalization to categories closely related to learned categories. These results do not fit…

Most people are experts in some area of information; however, they may not be knowledgeable about other closely related areas. How knowledge is generalized to hierarchically related categories was explored. Past work has found little to no generalization to categories closely related to learned categories. These results do not fit well with other work focusing on attention during and after category learning. The current work attempted to merge these two areas of by creating a category structure with the best chance to detect generalization. Participants learned order level bird categories and family level wading bird categories. Then participants completed multiple measures to test generalization to old wading bird categories, new wading bird categories, owl and raptor categories, and lizard categories. As expected, the generalization measures converged on a single overall pattern of generalization. No generalization was found, except for already learned categories. This pattern fits well with past work on generalization within a hierarchy, but do not fit well with theories of dimensional attention. Reasons why these findings do not match are discussed, as well as directions for future research.
ContributorsLancaster, Matthew E (Author) / Homa, Donald (Thesis advisor) / Glenberg, Arthur (Committee member) / Chi, Michelene (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2013
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A Closer Look into the Best Value (BV) Approach to RFP Contract Negotiation

Description
With the help of some Information Measurement Theory (IMT), Kashiwagi Solutions Model (KSM), and deductive logic background, supply chain managers can start utilizing a new way to effectively and efficiently negotiate contracts. Developed by Dr. Dean Kashiwagi, the Best Value Approach has been 98% successful with over 1,800 projects for…

With the help of some Information Measurement Theory (IMT), Kashiwagi Solutions Model (KSM), and deductive logic background, supply chain managers can start utilizing a new way to effectively and efficiently negotiate contracts. Developed by Dr. Dean Kashiwagi, the Best Value Approach has been 98% successful with over 1,800 projects for the past 20 years. The process gives vendors/suppliers the power to use their expertise. In return for not having to follow the rules set by the client/buyer, the vendor must show documentation and plans of risk management, value added processes, and metrics.
ContributorsPhan, Alice (Co-author) / Holtzman, Krista (Co-author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / School of International Letters and Cultures (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05