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Analyzing and Comparing Model-Authoritative and Model-Democratic
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Analyzing and Comparing Model-Authoritative and Model-Democratic
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Independent Research Projects
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Analyzing and Comparing Model-Authoritative and Model-Democratic
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Analyzing and Comparing Model-Authoritative and Model-Democratic
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Hal Eden
on 2010/08/20 11:32
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<h2>Project: Analyzing and Comparing Model-Authoritative and Model-Democratic</h2> Investigate two basic and fundamentally different models for knowledge creation, accumulation, and sharing: <h4>MODEL-AUTHORITATIVE - identify its strength and weaknesses</h4> This model is characterized by a small number of experts acting as contributors and a large number of passive consumers. In such cultures, strong input filters exist and creates barriers based on the following: * large organizations and high investments for production are required (e.g., film studios such as those in Hollywood, newspaper production facilities); * substantial knowledge is necessary for contributions (e.g., the need to learn highly specialized high-functionality tools); and * extensive quality control mechanisms exist (e.g., strict review criteria leading to low acceptance rates for conference papers and journal articles). * quality and trustworthiness of the accumulated information is high because the strong input filters will reject unreliable and untrustworthy information * Based on the smaller size of the resulting information repositories, relatively weak output filters are required. <h4>MODEL-DEMOCRATIC - identify its strength and weaknesses + describe and create new input filters</h4> * characterized by weak input filters allowing users not only to access information but some passive users become prosumers. * The weak input filters of MODEL-DEMOCRATIC result in much larger information repositories, with the World Wide Web being the prime example. * major limitation: the potential reduction in trust and reliability of the content of the information repositories based on the weak input filters. * large information repositories are a mixed blessing ** exploit existing and develop new output filters (e.g., powerful search mechanisms to find relevant information, collaborative filtering, recommender and tagging systems, and user and task models to personalize information
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