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PUBLIC PERCEPTIONS David M. Berube Professor of Science Communication, STS, and CRDM (Communication, Rhetoric and Digital Media), North Carolina State.

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Presentation on theme: "PUBLIC PERCEPTIONS David M. Berube Professor of Science Communication, STS, and CRDM (Communication, Rhetoric and Digital Media), North Carolina State."— Presentation transcript:

1 PUBLIC PERCEPTIONS David M. Berube Professor of Science Communication, STS, and CRDM (Communication, Rhetoric and Digital Media), North Carolina State University Director: NCSU Public Communication of Science and Technology (PCOST) Project. CEO, Center for Emerging Technologies, LLC – social media consultancy (trade assns and food industry). PI: NSF NIRT #0809470 – Intuitive Toxicology and Public Engagement, 2007-2011. http://pcost.org RTPSRA 2010© Berube January 19, 2010 – Raleigh, NC

2 1. 1. Cultural worldview theories, see Kahan et al. Ideological associations between perceptions on safety and who and how to regulate (new data). 2. 2. Religiosity theories, see Scheufele et al. Beliefs linked to perceptions (new data). 3. 3. Familiarity hypothesis – linking perception to familiarity; deficit theory revisited. 4. 4. Flattened interest, see Kahan, Scheufele, Satterfield, and Berube. REVIEW

3 PERCEIVED - RISKS OF NANO: AWARE VS. UNAWARE RESPONDENTS HOW IMPORTANT IS AWARENESS? Hart 2007

4 1. 1. Effect tends to be minor and may be a reporting anomaly. Overclaims abound. Opinion surveys are weak instruments to validate hypothesis (Kahan). 2. 2. Familiarity is highly dependent on framing (self- reported awareness). Sources (incl. opinion leaders) and trust are changing (new data). 3. 3. Familiarity hypothesis is generally false (Brossard & Nisbet, 2007). Interest leads to information seeking behavior more than reverse. 4. 4. Link between knowledge/familiarity/ awareness and attitudes seems to be false (Nisbet, Brossard & Kroepsch, 2003) and (Cacciatore, Scheufele & Corley, forthcoming). FAMILIARITY HYPOTHESIS

5 PUBLIC KNOWLEDGE (DYNAMICS) ON NANOTECHNOLOGIES USA (3 yr span) 2004: Cobb/ Macoubrie 2005a: Einsiedel 2005b: Macoubrie 2006: Hart 2007: Kahan IRGC, 2009

6 1. 1. Bad data. Asking the wrong questions. 2. 2. Time frame meaningless. Ex: getting information from two points on the same curve. 3. 3. Public interest maxed out. 4. 4. Wrong sampling (7% solution). 5. 5. Wrong methodologies (experimental design vs. opinion sampling). SPECULATION

7   Public interest in science/tech policy.   Traditionally low (7-10%). Likely to be case/region specific.   Competing interests (unemployment, economy, wars….)   Critical case studies- hold strategic importance to issues.   Experimental design (Kahan). MOVE TO CRITICAL CASE STUDIES

8 Satterfield et al, 2009 (Nature Nano)  How can we tag perception levels when studies have such high variances? (Satterfield, 2009)  Should we tighten the samples? Should we stop priming the samples? Do engagement exercises involving artificial settings provide useful data sets?  Should we privilege the longitudinal data sets (Hart, 2006-08)?

9 Unaided/Unprimed Evaluation - General PUBLIC KNOWLEDGE ON NANOTECHNOLOGIES (HART 06-08)

10 BERUBE et al. NEW DATA (2009) Dillman National Public Survey (w U South Carolina, N=307)   Impressions of nano and synthetic bio (non- framed),   General risk levels (Slovic),   Concerns of nanoparticle risks,   Perceptions of expert ratings of risk,   Sources and use of various media for risk info   Trust   Social media sources,   Demographics   Religion   Ideology. Expert Delphi Study (NCSU)  Nanoparticle toxicity,  Potentially problematic uses,  Potentially problematic applications,  Estimations of public perceptions of risk.

11   Priming: prompting of a cognitive stimulus which may create or influence reactions to future stimuli.   For example: “How much did you know about nanotechnology before participating?” 1 = 1 = Almost nothing 2 = A little 3 = Quite a bit 4 = A great deal (XXX, 2006) PRIMING

12 UNPRIMED PUBLIC KNOWLEDGE/INTEREST DATA “What comes to mind when you hear the word “nanotechnology”? “Very very small subject matter- beyond microscopic.” “Cutting edge research and technology that has made products smaller, faster, lighter, and stronger.” “I actually don’t have the slightest idea, but I’m going to take a guess and say that it would be the smallest pieces of technological machines that can be made.”

13 KNOWLEDGE/INTEREST DATA EXPERT – HYPOTHETICAL EXPERT VIEW OF PUBLIC EXPERTS: Which current and predictably future products involving the applications of nanoparticles are potentially or actually problematic to EHS? RankExperts: Top 5 applications 1Cosmetics 2Fuel additives 3Anti-microbial clothing 4Toys and baby products 5Pesticides PUBLIC: If experts were asked which potential or actual uses of nanoparticles most concerned the public, how do you think they would rate the public’s concerns? RankPublic: Top 5 Applications 1Medicine 2Pesticides 3Food Additives 4Anti-microbial treatments 5Food Packaging

14 EXPERTS: What applications or products do you assume the public believes is potentially or actually problematic (using ordinal rankings)? KNOWLEDGE/INTEREST DATA EXPERT HYPOTHETICAL PUBLIC - ACTUAL PUBLIC RankTop 5 Applications 1Cosmetics 2Food additives 3Sunscreens 4 All CNTs 5Nanobots RankTop 5 Applications 1Food additives 2Pesticides 3Drugs 4Food packaging 5Water treatment PUBLIC: how concerned are you about risk to health and safety of the following potential or actual uses of nanoparticles as a component of each of the following (on a 7-item scale). FOOD

15 HEALTH AND SAFETY PUBLIC INFORMATION SOURCES AND TRUST PUBLIC: Which sources are you most likely to turn to FOR INFO about risks to health and safety (reported as probably would or more)? RankTop 5 EHS sources for info about risks 1 Doctors and health professionals (73%) 2 University researchers (41%) 3Family members 4Friends and acquaintances 5 Industrial researchers 1.“Religious leaders” 2 nd to last ahead of “Elected representatives”. 2.“Industrial scientists” were deemed more trustworthy than “NGOs”.

16 1 2 TV viewing 2008 WWW 2008

17 How often do you use the following media sources FOR INFO about risks to health and safety (reported as once a day or more)? RankMedia sources 1Television (59%) 2Internet (44%) 3Radio 4Newspapers RankTop Web 2.0 internet sources 1News accumulators (27%) 2Personal accumulators (21%) 3Health Blogs 4Social networking sites 5Wikis Which internet sources do you use FOR INFO about risks to health and safety (reported as one a week or more)? HEALTH AND SAFETY SOURCES INTERNET AND SOCIAL MEDIA (Web 2.0)

18   52.8% - SLIGHT to NO risk.   74.6% - MODERATE to NO risk.   Only 13.0% - HIGH health risk (only higher than X-Rays cell phones, transfusions, and air travel) and less risky than storms and floods.   Top 3 – street drugs, cigarette smoking, and AIDS.   Weighted Ranking - 18/24 risks.   Behind: stress, motor vehicle accidents, cloning, sun tanning, pesticide residues on foods, coal and oil burning plants, radon… HEALTH AND SAFETY COMPARATIVE RANKINGS OF RISKS Flynn, Slovic & Mertz 1994/Berube 2009

19 RTPSRA 20010© Berube January 19, 2010 – Raleigh, NC COMMUNICATING RISK TO THE PUBLIC AND THE MEDIA This work was supported in part by grants from the National Science Foundation, NSF 0809470, Nanotechnology Interdisciplinary Research Team (NIRT): Intuitive Toxicology and Public Engagement. NCSU, U Wisconsin, U Minnesota, U South Carolina, & Rice U. (6 grad. students). THANKS dmberube@ncsu.edu


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