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Assumptions of the Deficit Model Type of Thinking: Ignorance, Attitudes, and Science Communication in the Debate on Genetic Engineering in Agriculture created by Marko Ahteensuu

By: Material type: TextTextSeries: ; Volume , number ,Turku Springer 2011Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
Subject(s): Online resources: Summary: This paper spells out and discusses four assumptions of the deficit model type of thinking. The assumptions are: First, the public is ignorant of science. Second, the public has negative attitudes towards (specific instances of) science and technology. Third, ignorance is at the root of these negative attitudes. Fourth, the public’s knowledge deficit can be remedied by one-way science communication from scientists to citizens. It is argued that there is nothing wrong with ignorance-based explanations per se. Ignorance accounts at least partially for many cases of opposition to specific instances of science and technology. Furthermore, more attention needs to be paid to the issue of relevance. In regard to the evaluation of a scientific experiment, a technology, or a product, the question is not only “who knows best?,” but also “what knowledge is relevant and to what extent?.” Examples are drawn primarily from the debate on genetic engineering in agriculture.
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This paper spells out and discusses four assumptions of the deficit model type of thinking. The assumptions are: First, the public is ignorant of science. Second, the public has negative attitudes towards (specific instances of) science and technology. Third, ignorance is at the root of these negative attitudes. Fourth, the public’s knowledge deficit can be remedied by one-way science communication from scientists to citizens. It is argued that there is nothing wrong with ignorance-based explanations per se. Ignorance accounts at least partially for many cases of opposition to specific instances of science and technology. Furthermore, more attention needs to be paid to the issue of relevance. In regard to the evaluation of a scientific experiment, a technology, or a product, the question is not only “who knows best?,” but also “what knowledge is relevant and to what extent?.” Examples are drawn primarily from the debate on genetic engineering in agriculture.

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