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Expert and public perceptions of gene-edited crops: attitude changes in relation to scientific knowledge

Author

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  • Naoko Kato-Nitta

    (The Institute of Statistical Mathematics
    Nagoya University
    Joint Support-Center for Data Science Research, Research Organization of Information and Systems)

  • Tadahiko Maeda

    (The Institute of Statistical Mathematics
    Joint Support-Center for Data Science Research, Research Organization of Information and Systems)

  • Yusuke Inagaki

    (The Institute of Statistical Mathematics
    Joint Support-Center for Data Science Research, Research Organization of Information and Systems)

  • Masashi Tachikawa

    (Nagoya University)

Abstract

This study empirically examined expert and public attitudes toward applying gene editing to agricultural crops compared with attitudes toward other genetic modification and conventional breeding technologies. Regulations regarding the application of gene editing on food are being debated around the world. New policy measures often face issues of public acceptance and consensus formation; however, reliable quantitative evidence of public perception toward such emerging breeding technologies is scarce. To fill this gap, two web-based surveys were conducted in Japan from December 2016 to February 2017. Participants (N = 3197) were categorised into three groups based on the domain-specific scientific knowledge levels (molecular biology experts, experts in other fields, and lay public). Statistical analysis revealed group differences in risk, benefit, and value perceptions of different technologies. Molecular biology experts had higher benefit and value perceptions, as well as lower risk perceptions regarding new technologies (gene editing and genetic modification). Although the lay public tended to have more favourable attitudes toward gene editing than toward genetic modification, such differences were much smaller than the differences between conventional breeding and genetic modification. The experts in other fields showed some characteristics that are similar to the experts in molecular biology in value perceptions, while showing some characteristics that are similar to the lay public in risk perceptions. The further statistical analyses of lay attitudes revealed the influence of science literacy on attitudinal change toward crops grown with new breeding technologies in benefit perceptions but not in risk or value perceptions. Such results promoted understanding on distinguishing conditions where deficit model explanation types are valid and conditions where they are not.

Suggested Citation

  • Naoko Kato-Nitta & Tadahiko Maeda & Yusuke Inagaki & Masashi Tachikawa, 2019. "Expert and public perceptions of gene-edited crops: attitude changes in relation to scientific knowledge," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-14, December.
  • Handle: RePEc:pal:palcom:v:5:y:2019:i:1:d:10.1057_s41599-019-0328-4
    DOI: 10.1057/s41599-019-0328-4
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    References listed on IDEAS

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    1. Xiaoqin Zhu & Xiaofei Xie, 2015. "Effects of Knowledge on Attitude Formation and Change Toward Genetically Modified Foods," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 790-810, May.
    2. Dan M. Kahan & Ellen Peters & Maggie Wittlin & Paul Slovic & Lisa Larrimore Ouellette & Donald Braman & Gregory Mandel, 2012. "The polarizing impact of science literacy and numeracy on perceived climate change risks," Nature Climate Change, Nature, vol. 2(10), pages 732-735, October.
    3. Lucia Savadori & Stefania Savio & Eraldo Nicotra & Rino Rumiati & Melissa Finucane & Paul Slovic, 2004. "Expert and Public Perception of Risk from Biotechnology," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1289-1299, October.
    4. Paul Slovic, 1999. "Trust, Emotion, Sex, Politics, and Science: Surveying the Risk‐Assessment Battlefield," Risk Analysis, John Wiley & Sons, vol. 19(4), pages 689-701, August.
    5. Lynn Frewer & Chaya Howard & Richard Shepherd, 1998. "The influence of initial attitudes on responses to communication about genetic engineering in food production," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 15(1), pages 15-30, March.
    6. Massimiano Bucchi & Federico Neresini, 2002. "Biotech remains unloved by the more informed," Nature, Nature, vol. 416(6878), pages 261-261, March.
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    Cited by:

    1. Yuwan Malakar & Justine Lacey & Paul M Bertsch, 2022. "Towards responsible science and technology: How nanotechnology research and development is shaping risk governance practices in Australia," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    2. Alessandro Natalini & Nazzareno Acciarri & Teodoro Cardi, 2021. "Breeding for Nutritional and Organoleptic Quality in Vegetable Crops: The Case of Tomato and Cauliflower," Agriculture, MDPI, vol. 11(7), pages 1-21, June.
    3. Ujiie, Kiyokazu, 2021. "Discussion: Food Consumption to Embody Multidimensionality: The Role of Information: Viewpoints and Issues," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 23.
    4. John C. Beghin & Christopher R. Gustafson, 2021. "Consumer Valuation of and Attitudes towards Novel Foods Produced with New Plant Engineering Techniques: A Review," Sustainability, MDPI, vol. 13(20), pages 1-17, October.
    5. Lyn Kathlene & Debashish Munshi & Priya Kurian & Sandra L. Morrison, 2022. "Cultures in the laboratory: mapping similarities and differences between Māori and non-Māori in engaging with gene-editing technologies in Aotearoa, New Zealand," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    6. Robin Siebert & Christian Herzig & Marc Birringer, 2022. "Strategic framing of genome editing in agriculture: an analysis of the debate in Germany in the run-up to the European Court of Justice ruling," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(2), pages 617-632, June.

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