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  1. A Precautionary Approach to Genetically Modified Organisms: Challenges and Implications for Policy and Science. [REVIEW]Anne Ingeborg Myhr - 2010 - Journal of Agricultural and Environmental Ethics 23 (6):501-525.
    The commercial introduction of genetically modified organisms (GMOs) has revealed a broad range of views among scientists and other stakeholders on perspectives of genetic engineering (GE) and if and how GMOs should be regulated. Within this controversy, the precautionary principle has become a contentious issue with high support from skeptical groups but resisted by GMO advocates. How to handle lack of scientific understanding and scientific disagreement are core issues within these debates. This article examines some of the key issues affecting (...)
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  • Theory-testing in psychology and physics: A methodological paradox.Paul E. Meehl - 1967 - Philosophy of Science 34 (2):103-115.
    Because physical theories typically predict numerical values, an improvement in experimental precision reduces the tolerance range and hence increases corroborability. In most psychological research, improved power of a statistical design leads to a prior probability approaching 1/2 of finding a significant difference in the theoretically predicted direction. Hence the corroboration yielded by "success" is very weak, and becomes weaker with increased precision. "Statistical significance" plays a logical role in psychology precisely the reverse of its role in physics. This problem is (...)
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  • The precautionary principle: Scientific uncertainty and type I and type II errors. [REVIEW]John Lemons, Kristin Shrader-Frechette & Carl Cranor - 1997 - Foundations of Science 2 (2):207-236.
    We provide examples of the extent and nature of environmental and human health problems and show why in the United States prevailing scientific and legal burden of proof requirements usually cannot be met because of the pervasiveness of scientific uncertainty. We also provide examples of how may assumptions, judgments, evaluations, and inferences in scientific methods are value-laden and that when this is not recognized results of studies will appear to be more factual and value-neutral than warranted. Further, we show that (...)
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  • (2 other versions)Error and the Growth of Experimental Knowledge.Deborah Mayo - 1997 - British Journal for the Philosophy of Science 48 (3):455-459.
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  • (2 other versions)Error and the growth of experimental knowledge.Deborah Mayo - 1996 - International Studies in the Philosophy of Science 15 (1):455-459.
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  • Error and the Growth of Experimental Knowledge.Deborah G. Mayo - 1996 - University of Chicago.
    This text provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own error-statistical approach as an alternative framework for the epistemology of experiment. It seeks to address the needs of researchers who work with statistical analysis.
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