Public Trust in the U.S. Food System

1. Public Trust in the U.S. Food System When Good Communication Isn’t Good Enough Steve Sapp Department of Sociology Iowa State University

2. The Issue: Risk Communication • The development and implementation of new technologies sometimes engenders uncertainty, anxiety, fear, concern, and organized resistance. • The extent to which these feelings and actions are justified is not the subject of this presentation. • Rather, we ask, “What procedures are most effective at alleviating these feelings—under the presumption that, overall, the technology is good for society.”

3. The Issue: Risk Communication • This presumption is fraught with limitations. • We make it to allow us to address just one facet of a complex decision-making process regarding the development and implementation of new technologies. We ask, “How does one gain the trust of others?” • This, essentially, is the task of risk communication: To convince others either to “look out” or “stop worrying.”

4. Risk Communication: Approaches • To convince others to stop worrying, scientists might choose to provide no communication. That is, they might take the perspective that nothing needs to be said because they and risk managers are the ones who are well educated and know what they are doing. • To some extent, this is a very good argument! • Unfortunately, scientists and risk managers err sufficiently that, within democratic societies, the public demands to become involved in the decision-making process.

5. Risk Communication: Approaches • When scientists attempt to explain the facts, however, they face other problems because explanations involve subjective evaluations. • Scientists and representatives of groups concerned about the technology then argue about whose interpretation is the most correct. • These arguments come to the attention of the media, who understandably report them.

6. Risk Communication: The Media • When the media report on a controversy, it becomes amplified. We notice a “hoopla” effect. • Proponents of the technology then blame the media for arousing unnecessary anxiety about the technology. • Assuming the media are responsible in their actions, this critique is unjustified. • It is more correct to note that negative information carries disproportionate weight, for many good reasons.

7. Risk Communication: Trust • Some scholars argue that this amplification of risk and reporting of negative information destroys trust, which is fragile. • Others argue that this downturn in trust is temporary and can be overcome with risk communication techniques aimed at restoring trust. • To make a long story short: Convincing others to “stop worrying” equates to gaining their trust because trust explains most of the variance in adoption of new technologies.

8. Risk Communication: Trust • Informing scientists and business organizations about how to gain trust, therefore, is the key to teaching them how to inform the public about new technologies. • So, we ask the question, “What influences public trust in institutions?” • If we know what drives trust, then we can inform scientists and business organizations about how to convince the public to stop worrying (again, under the presumption that the technology mainly is a good one).

9. Risk Communication: Trust • Explaining public trust and training scientists and business leaders to communicate adequately with the public is easy!  • We simply develop a theoretical model with the variables shown on the next slide. Then, we estimate the model, determine which variables are most effective at explaining trust, define these variables for scientists and business leaders, and convince them to listen to our advice.

10. Risk Communication: Trust • Here are just some of the variables we will need to explain public trust in societal institutions: perceived risks stigma complexity alienation age perceived benefits familiarity relative advantage value similarity sex anomie compatibility source credibility trialability observability race income prior exposure media attention education…..

11. Risk Communication: Recreancy • Of course, a simpler model would be preferable! • We seek a model that: • explains much of the variance in trust • with just a few variables • that are easily defined to others • and appeal to them as actionable.

12. Risk Communication: Recreancy • The solution might lie in the recreancy theorem, which asserts that public trust in societal institutions reflects assessments of the competence and fiduciary responsibilities of institutional actors. • Where Competence refers to perceptions of expertise and skill, and Fiduciary Responsibility refers to perceptions that the source will behave with in the “right” way (ethically). • Fiduciary Responsibility can also be called Confidence.

13. Competence Trust Compliance Confidence Risk Communication: Recreancy • Our theoretical model can be diagrammed like this: • Where Compliance refers to willingness to heed the recommendations of others. This variable is used to evaluate the external validity of the measure of trust, as an indicator of commitment to a source of information.

14. Risk Communication: Recreancy • Note that, for the most part, scientists, business leaders, and proponents of new technologies prefer risk communication strategies that focus upon establishing competence. • Proponents want the public to believe that proponents know what they are doing, that the scientific findings are accurate and unbiased. • We will therefore be interested in discovering the relative effects of competence and confidence in explaining trust.

15. Recreancy: Empirical Analysis • Examination of trust in the U.S. food system. • Nationwide survey of primary food preparers at home. • Final sample of 2,008 adults living in 50 states. • Measurements on competence, confidence, trust, compliance, and some social-demographic controls (i.e., age, sex, education). • Five areas of the U.S. food system: food safety, nutrition, worker care, environmental protection, animal welfare. • 7-9 pertinent actors within each area (e.g., producers, processors, grocers, regulators, restaurants, advocacy groups).

16. Recreancy: Empirical Analysis • This research design yields 41 tests of our theoretical model. These are the results: Std. Estimates PathAvg.LowHigh Trust  Compliance .676 .520 .792 Competence  Trust .216 .154 .311 Confidence  Trust .668 .579 .768 R-SquareAvg.LowHigh Trust .745 .590 .837 Compliance .495 .299 .713

17. Recreancy: Empirical Analysis • The results indicate that the model: • explains much of the variance in trust • with just a few variables • that are easily defined to others. • Also, the results indicate overwhelmingly that confidence, not competence, is the key driver of public trust in societal institutions responsible for the U.S. food system!

18. Recreancy: Prospects • The question remains, “Do representatives of the U.S. food system understand the implications of these results and consider them to be actionable? • The interest shown in the results, which were presented at the Food Summit, held in Indianapolis in October, 2007, indicates that the model does have potential to affect the risk communication strategies of organizations and companies involved in the U.S. food system.

19. Recreancy: Prospects • Presenting messages aimed at instilling confidence in the source have been an important part of advertising and other promotional activities for many years. • But this approach is relatively new to proponents of the complex and sometimes controversial technologies used in the U.S. food system. • Future research needs to further explore the meanings of competence and confidence.

20. Public Trust in the U.S. Food System When Good Communication Isn’t Good Enough Thank You!