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Public awareness of science

(Redirected from Public understanding of science)
"Public understanding of science" redirects here. For the journal, see Public Understanding of Science.

Public awareness of science (PAS) is everything relating to the awareness, attitudes, behaviors, opinions, and activities that comprise the relations between the general public or lay society as a whole to scientific knowledge and organization. This concept is also known as public understanding of science (PUS), or more recently, public engagement with science and technology (PEST). It is a comparatively new approach to the task of exploring the multitude of relations and linkages science, technology, and innovation have among the general public.[1] While early work in the discipline focused on increasing or augmenting the public's knowledge of scientific topics, in line with the information deficit model of science communication, the deficit model has largely been abandoned by science communication researchers. Instead, there is an increasing emphasis on understanding how the public chooses to use scientific knowledge and on the development of interfaces to mediate between expert and lay understandings of an issue.[example needed] Newer frameworks of communicating science include the dialogue and the participation models.[2] The dialogue model aims to create spaces for conversations between scientists and non-scientists to occur while the participation model aims to include non-scientists in the process of science.

Major themes

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Photo taken during a Citizen Science Bioblitz

The area integrates a series of fields and themes such as:

Important lines of research are how to raise public awareness and public understanding of science and technology. Also, learning how the public feels and knows about science generally as well as individual subjects, such as genetic engineering, or bioethics. Research by Matthew Nisbet highlights several challenges in science communication, including the paradox that scientific success can create either trust or distrust in experts in different populations and that attitudes of trust are shaped by mostly socioeconomic rather than religious or ideological differences.[3] A 2020 survey by the Pew Research Center found varying levels of trust in science by country, political leanings, and other factors.[4]

Bodmer report

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The publication of the Royal Society's' report The Public Understanding of Science[5] (or Bodmer Report) in 1985 is widely held to be the birth of the Public Understanding of Science movement in Britain.[6] The report led to the founding of the Committee on the Public Understanding of Science and a cultural change in the attitude of scientists to outreach activities.[7]

Models of engagement

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Contextualist model

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In the 1990s, a new perspective emerged in the field with the classic study of Cumbrian Sheep Farmers' interaction with the Nuclear scientists in England. Brian Wynne demonstrated how the experts were ignorant or disinterested in taking into account the lay knowledge of the sheep farmers while conducting field experiments on the impact of the Chernobyl nuclear fallout on the sheep in the region.[8] Because of this shortcoming from the side of the scientists, local farmers lost their trust in them. The experts were unaware of the local environmental conditions and the behaviour of sheep and this has eventually led to the failure of their experimental models. Following this study, scholars have studies similar micro-sociological contexts of expert-lay interaction and proposed that the context of knowledge communication is important to understand public engagement with science. Instead of large scale public opinion surveys, researchers proposed studies informed by sociology of scientific knowledge (SSK). The contextualist model focuses on the social impediments in the bidirectional flow of scientific knowledge between experts and laypersons/communities.

Deliberative model

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Scholars like Sheila Jasanoff have advanced the debate around public engagement with science by leveraging the theory of deliberative democracy to analyze the public deliberation of and participation in science through various institutional forms. Proponents of greater public deliberation argue it is a basic condition for decision making in democratic societies, even on science and technology issues.[9] There are also attempts to develop more inclusive participatory models of technological governance in the form of consensus conferences, citizen juries, extended peer reviews, and deliberative mapping.[10]

Civic science model

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Some scholars have identified a new era of "post-normal science" (PNS) in which many scientific discoveries carry high stakes if risks are estimated incorrectly within a broader social context that has a high degree of uncertainty.[11][12] This PNS era requires a new approach to public engagement efforts and requires a reevaluation of the underlying assumptions of "public engagement", especially with emerging science and technology issues, like CRISPR gene editing, that have the potential to become "wicked problems".[13][14] These "wicked" issues often require regulatory and policy decisions that have no single correct solution and often involve numerous interest groups – none of whom are clearly positioned to decide and resolve the problem. Policy and regulatory decisions around these scientific issues are inherently political and must balance trade-offs between the scientific research, perceptions of risk, societal needs, and ethical values.[15] While scientists can provide factual answers to research questions and mathematical estimates of risk, many considerations surrounding these wicked science and technology issues have no factual answer. The unidirectional deficit model of simply educating the public on theses issues is insufficient to address these complex questions, and some scholars have proposed scientists adopt a culture of civic science: "broad public engagement with issues that arise at the many intersections between science and society."[13] An emphasis is placed on developing an iterative engagement model that actively seeks to incorporate groups who stand to be adversely effected by a new technology[14] and conducting this engagement away from universities so that it can be done on the public's terms with the public's terms.[16] Other scholars have emphasized that this model of public engagement requires that the public be able to influence science, not merely be engaged by it, up to the point of being able to say "no" to research that does not align with the broader public's values.[17] Under the civic science model, there are five key lessons for scientists committed to public engagement:[14][18][19][20]

  1. Establish why you want to engage with the public and clearly identify your goals.
  2. Seek out and engage with a broad, diverse range of groups and perspectives and center engagement on listening to these groups.
  3. Work cooperatively with groups to establish common definitions to avoid the perception that researchers are being disingenuous by relying on semantic differences between expert and lay interpretations of vocabulary to ensure the public "supports" their position.
  4. Working to tilt public debates in favor of the priorities and values of researchers will not lead to consistent "best" decisions because wicked science and technology problems will have different considerations and perspectives depending on the application and cultural context.
  5. Meaningfully engage as early as possible; engagement must begin early enough in the research process that the public's views can shape both the research and implementation of findings

Public understanding of science

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Social scientists use various metrics to measure public understanding of science, including:

Factual knowledge

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The key assumptions is that the more individual pieces of information a person is able to retrieve, the more that person is considered to have learned.[21]

Examples of measurement:

  • Recognition: Answering a specific question by selecting the correct answer out a list[21]
  • Cued recall: Answering a specific question without a list of choices[21]
  • Free recall: After exposure to information, the study participant produces a list of as much of the information as they can remember[21]

Self-reported knowledge, perceived knowledge, or perceived familiarity

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The key assumption is that emphasizes the value of knowledge of one's knowledge.[22]

Examples of measurement:

  • Scaled survey responses to questions such as, "How well informed you would say you are about this topic?",[22] this can be also used to assess perceived knowledge before and after events[23]

Structural knowledge

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The nature of connections among different pieces of information in memory.[21] The key assumption is that the use of elaboration increases the likelihood of remembering information.[21]

Examples of measurement:

  • Asking study participants to assess relationships among concepts. For example, participants free recall concepts onto the first row and column of a matrix, then indicate whether the concepts are related to each other by placing an "X" in the cell if they are not. Participants then rank the remaining open cells by their relatedness from 1 (only very weakly) to 7 (very strongly related).[21]
  • Study participants answer questions designed to measure elaboration involved in a task, such as, "I tried to relate the ideas I read about to my own past experiences."[21]

Trust and credibility

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People may trust science or scientists to different degrees, or may find specific scientists or specific research to be more or less credible. These factors can be related to how science can be used to advance knowledge, and may also be related to how science is communicated.[24]

Examples of measurement:

  • The 21-item Trust in Science and Scientists Inventory, which measures agreement/disagreement with statements like, "We can trust scientists to share their discoveries even if we don't like their findings."[25]
  • Scientist-specific measures of agreement, such as "I would trust scientific information if I knew it came from this author."[26]

Mixed use of measures

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  • While some studies purport that factual and perceived knowledge can be viewed as the same construct, a 2012 study investigating public knowledge of nanotechnology supports separating their use in communications research, as they "do not reflect the same underlying knowledge structures".[22] Correlations between them were found to be low and they were not predicted by the same factors. For example different types of science media use, television versus online, predicted different constructs.[22]
  • Factual knowledge has been shown to be empirically distinct from structural knowledge.[21]

Project example

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Government and private-led campaigns and events, such as Dana Foundation's "Brain Awareness Week", are becoming a strong focus of programmes which try to promote public awareness of science.

The UK PAWS Foundation dramatically went as far as establishing a Drama Fund with the BBC in 1994. The purpose was to encourage and support the creation of new drama for television, drawing on the world of science and technology.[27]

The Vega Science Trust[28] was set up in 1994 to promote science through the media of television and the internet with the aim of giving scientists a platform from which to communicate to the general public.

The Simonyi Professorship for the Public Understanding of Science chair at The University of Oxford was established in 1995 for the ethologist Richard Dawkins[29] by an endowment from Charles Simonyi. Mathematician Marcus du Sautoy has held the chair since Dawkins' retirement in 2008.[30] Similar professorships have since been created at other British universities. Professorships in the field have been held by well-known academics including Richard Fortey and Kathy Sykes at the University of Bristol, Brian Cox at Manchester University, Tanya Byron at Edge Hill University, Jim Al-Khalili at the University of Surrey, and Alice Roberts at the University of Birmingham.

See also

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References

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  1. ^ Savaget, Paulo; Acero, Liliana (2017). "Plurality in understandings of innovation, sociotechnical progress and sustainable development: An analysis of OECD expert narratives" (PDF). Public Understanding of Science. 27 (5): 611–628. doi:10.1177/0963662517695056. PMID 29298581. S2CID 3179006.
  2. ^ Cowan, Louise. "LibGuides: Science Communication: Models of science communication". Newcastle University. Retrieved 10 January 2022.
  3. ^ Nisbet, Matthew (2018). "Divided Expectations: Why We Need a New Dialogue about Science, Inequality, and Society". Skeptical Inquirer. 42 (1): 18–19. Archived from the original on 19 June 2018. Retrieved 19 June 2018.
  4. ^ Branch, Glenn (January–February 2021). "In Science We Trust? Twenty-Country Pew Survey Shows Trust in Scientists – with Major Caveats". Skeptical Inquirer. Amherst, New York: Center for Inquiry. Archived from the original on 11 October 2021. Retrieved 11 October 2021.
  5. ^ The Royal Society. "The Public Understanding of Science". The Royal Society. Retrieved 11 October 2015.
  6. ^ "Going public: Public attitudes to science and research". www.wellcome.ac.uk. Archived from the original on 11 August 2007. Retrieved 6 June 2022.
  7. ^ "House of Lords – Science and Technology – Third Report". Parliament of the United Kingdom.
  8. ^ Wynne, Brian (1996). "Misunderstood Misunderstandings: Social Identities and the Public Uptake of Science". In Alan Irwin; Brian Wynne (eds.). Misunderstanding Science? The Public Reconstruction of Science and Technology. Cambridge: Cambridge University Press. pp. 19–46.
  9. ^ Jasanoff, Sheila (2003). "Breaking the Waves in Science Studies: Comment on H.M. Collins and Robert Evans, 'The Third Wave of Science Studies'". Social Studies of Science. 33 (3): 389–400. doi:10.1177/03063127030333004. S2CID 143457704.
  10. ^ Lövbrand, Eva, Roger Pielke, Jr. and Silke Beck (2011). "A Democracy Paradox in Studies of Science and Technology". Science, Technology, & Human Values. 36 (4): 474–496. doi:10.1177/0162243910366154. S2CID 2005295.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  11. ^ Funtowicz, Silvio O.; Ravetz, Jerome R. (September 1993). "Science for the post-normal age". Futures. 25 (7): 739–755. doi:10.1016/0016-3287(93)90022-L. S2CID 204321566.
  12. ^ Funtowicz, Silvio O.; Ravetz, Jerome R. (14 May 2020). "Science for the Post-Normal Age". Commonplace. doi:10.21428/6ffd8432.8a99dd09.
  13. ^ a b "The Civic Science Imperative (SSIR)". ssir.org. Retrieved 5 April 2021.
  14. ^ a b c Wirz, Christopher D.; Scheufele, Dietram A.; Brossard, Dominique (29 September 2020). "Societal Debates About Emerging Genetic Technologies: Toward a Science of Public Engagement". Environmental Communication. 14 (7): 859–864. Bibcode:2020Ecomm..14..859W. doi:10.1080/17524032.2020.1811478. ISSN 1752-4032.
  15. ^ "The COVID-19 Communication War". Issues in Science and Technology. 17 April 2020. Retrieved 5 April 2021.
  16. ^ Leshner, Alan I. (13 October 2006). "Science and Public Engagement". chronicle.com. Retrieved 5 April 2021.
  17. ^ Evans, John H. (3 September 2020). "Can the Public Express Their Views or Say No Through Public Engagement?". Environmental Communication. 14 (7): 881–885. Bibcode:2020Ecomm..14..881E. doi:10.1080/17524032.2020.1811459. ISSN 1752-4032. S2CID 222074307.
  18. ^ Brossard, Dominique; Belluck, Pam; Gould, Fred; Wirz, Christopher D. (14 January 2019). "Promises and perils of gene drives: Navigating the communication of complex, post-normal science". Proceedings of the National Academy of Sciences. 116 (16): 7692–7697. Bibcode:2019PNAS..116.7692B. doi:10.1073/pnas.1805874115. ISSN 0027-8424. PMC 6475393. PMID 30642954.
  19. ^ Scheufele, D. A. (20 August 2013). "Communicating science in social settings". Proceedings of the National Academy of Sciences. 110 (Supplement_3): 14040–14047. doi:10.1073/pnas.1213275110. ISSN 0027-8424. PMC 3752169. PMID 23940341.
  20. ^ Rowe, Gene; Watermeyer, Richard Patrick (4 March 2018). "Dilemmas of public participation in science policy". Policy Studies. 39 (2): 204–221. doi:10.1080/01442872.2018.1451502. ISSN 0144-2872. S2CID 158913099.
  21. ^ a b c d e f g h i Eveland, William (2004). "How Web Site Organization Influences Free Recall, Factual Knowledge, and Knowledge Structure Density". Human Communication Research. 30 (2): 208–233. doi:10.1111/j.1468-2958.2004.tb00731.x.
  22. ^ a b c d Ladwig, Peter (2012). "Perceived familiarity or factual knowledge? Comparing operationalizations of scientific understanding". Science and Public Policy. 39 (6): 761–774. doi:10.1093/scipol/scs048.
  23. ^ Duckett, Catherine J.; Hargreaves, Kate E.; Rawson, Kirstie M.; Allen, K. Elizabeth; Forbes, Sarah; Rawlinson, Katherine E.; Shaw, Hollie; Lacey, Melissa (2021). "Nights at the museum: Integrated arts and microbiology public engagement events enhance understanding of science whilst increasing community diversity and inclusion". Access Microbiology. 3 (5): 000231. doi:10.1099/acmi.0.000231. PMC 8209632. PMID 34151182.
  24. ^ Agley, Jon; Xiao, Yunyu; Thompson, Esi E; Golzarri-Arroyo, Lilian (30 March 2023). "Using Normative Language When Describing Scientific Findings: Randomized Controlled Trial of Effects on Trust and Credibility". Journal of Medical Internet Research. 25: e45482. doi:10.2196/45482. ISSN 1438-8871. PMC 10131812. PMID 36995753.
  25. ^ Nadelson, Louis; Jorcyk, Cheryl; Yang, Dazhi; Jarratt Smith, Mary; Matson, Sam; Cornell, Ken; Husting, Virginia (19 January 2014). "I Just Don't Trust Them: The Development and Validation of an Assessment Instrument to Measure Trust in Science and Scientists". School Science and Mathematics. 114 (2): 76–86. doi:10.1111/ssm.12051. ISSN 0036-6803.
  26. ^ Song, Hyunjin; Markowitz, David; Taylor, Samuel (30 June 2022). "Trusting on the shoulders of open giants? Open science increases trust in science for the public and academics". Journal of Communication. 72 (4): 497–510. doi:10.1093/joc/jqac017.
  27. ^ "PAWS off science?". Physics Education. 33 (1). January 1998. doi:10.1088/0031-9120/33/1/011. S2CID 250835641.
  28. ^ "The Vega Science Trust - Science Video - Homepage". vega.org.uk.
  29. ^ "Professor Richard Dawkins – The Simonyi Professorship". University of Oxford. Archived from the original on 14 May 2011.
  30. ^ "Professor Marcus du Sautoy – The Simonyi Professorship". University of Oxford. Archived from the original on 31 May 2010.

Further reading

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  • Bensaude-vincent, Bernadette (2001). "A Genealogy of the Increasing Gap between Science and the Public". Public Understanding of Science. 10 (1): 99–113. doi:10.1088/0963-6625/10/1/307.
  • Bijker, Wiebe E., Bal, Roland and Hendriks, Ruud. 2009. The Paradox of Scientific Authority: The Role of Scientific Advice in Democracies. Cambridge and London: The MIT Press.
  • Bucchi, Massimiano (1996). "When Scientists Turn to the Public: Alternative Routes in Science Communication". Public Understanding of Science. 5 (4): 375–394. doi:10.1088/0963-6625/5/4/005. S2CID 143374883.
  • Dash, Biswanath (2014a). "Public Understanding of Cyclone Warning in India: Can Wind be Predicted?". Public Understanding of Science. 24 (8): 970–987. doi:10.1177/0963662514553203. PMID 25313142. S2CID 22226217.
  • Davenport, Sally and Leitch, Shirley. 2005. "Agoras, Ancient and Modern, and a Framework for Science-Society Debate", Science and Public Policy 32(2), April, pp. 137–153.
  • Dryzek, John S. 2000. Deliberative Democracy and Beyond: Liberals, Critics, Contestations. New York and Oxford: Oxford University Press.
  • Felt, Ulrike; Fochler, Maximilian (2010). "Machineries for Making Publics: Inscribing and De-scribing Publics in Public Engagement". Minerva. 48 (3): 219–239. doi:10.1007/s11024-010-9155-x. S2CID 144227502.
  • Fischer, Frank. 2005. Citizens, Experts, and the Environment. Durham: Duke University Press.
  • Gregory, Jane & Miller, Steve (1998); Science in Public: Communication, Culture & Credibility (Cambridge, Massachusetts USA: Perseus Publishing)
  • Hess, David J (2011). "To Tell the Truth: On Scientific Counter Publics". Public Understanding of Science. 20 (5): 627–641. doi:10.1177/0963662509359988. S2CID 145627603.
  • Hilgartner, Stephen (1990). "The Dominant View of Popularisation: Conceptual Problems, Political Uses". Social Studies of Science. 20 (3): 519–539. doi:10.1177/030631290020003006. S2CID 144068473.
  • Irwin, Alan and Wynne, Brian. (eds.) 1996. Misunderstanding Science? The Public Reconstruction of Science and Technology. Cambridge: Cambridge University Press.
  • Irwin, Alan. 1995. Citizen Science: A Study of People, Expertise and Sustainable Development. London and New York: Routledge.
  • Jasanoff, Sheila (2003c). "Technologies of Humility: Citizen Participation in Governing Science". Minerva. 41 (3): 223–244. doi:10.1023/A:1025557512320. S2CID 14370392.
  • Jasanoff, Sheila. 2005. Designs on Nature: Science and Democracy in Europe and the United States. Princeton and Oxford: Princeton University Press.
  • Leach, Melissa, Scoones, Ian and Wynne, Brian. (eds.) 2005. Science and Citizens: Globalisation and the Challenge of Engagement. London and New York: Zed Books.
  • Public Understanding of Science, specialist journal.
  • Shapin, Steven. 1990. 'Science and the Public' in R.C. Olby et al. (eds). Companion to the History of Modern Science. London and New York: Routledge. Pp. 990–1007.
  • The Royal Academy of Science's 2006 "Factors affecting science communication: a survey of scientists and engineers" report.
  • Southwell, Brian G. (2013). "Social Networks and Popular Understanding of Science and Health". Baltimore, MD: Johns Hopkins University Press.
  • Southwell, Brian G.; Torres, Alicia (2006). "Connecting interpersonal and mass communication: Science news exposure, perceived ability to understand science, and conversation". Communication Monographs. 73 (3): 334–350. doi:10.1080/03637750600889518. S2CID 143644528.
  • Varughese, Shiju Sam (2012). "Where are the missing masses? The Quasi-publics and Non-publics of Technoscience". Minerva. 50 (2): 239–254. doi:10.1007/s11024-012-9197-3. S2CID 144319733.
  • Varughese, Shiju Sam (2017). Contested Knowledge: Science, Media, and Democracy in Kerala. Oxford University Press. doi:10.1093/acprof:oso/9780199469123.001.0001. ISBN 9780199469123.
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