• Health physics · Jul 1999

    Radiation protection information: can you trust the government's risks or risk the government's trust?: 1997 G. William Morgan lecture.

    • P L Ziemer.
    • School of Health Sciences, Purdue University, West Lafayette, IN 47907, USA.
    • Health Phys. 1999 Jul 1; 77 (1): 9-15.

    AbstractPublic acceptance of information concerning radiation risks has been impacted by the erosion of trust in government agencies and by societal images that personify radiation or its effects in terms of monsters and ogres. The loss of trust in government agencies, particularly the Atomic Energy Commission and later the Department of Energy, has been influenced by a number of key events and individuals. Examples of these are given, including the anti-Viet Nam war movement, the Watergate incident, the activities of the Union of Concerned Scientists, Ralph Nader and the Critical Mass movement, the claims of Ernest Sternglass, and the widely publicized views of John Gofman and Arthur Tamplin. The use of negative images, pictures, and symbols in the mass media has reinforced the public perception of radiation as a thing to be feared. There is growing evidence that the public perception of radiation risks is related more to mistrust and negative images than it is to the technical information health physicists provide or to the issue of whether or not the linear no-threshold theory of radiation risks is correct. Attempts by federal agencies to regain public trust in radiation risk information generated by health physicists or other radiation scientists appear to be largely unsuccessful. If health physicists hope to be successful in changing such public perceptions, they may have to focus efforts on the next generation and concentrate on assuring that elementary and secondary school children receive sound instruction on radiation risks. Additional research at the molecular biology level is needed to elucidate the risks, if any, at low doses so that the practice of extrapolating low dose responses from high dose data can be eliminated.

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