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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Science communication | 3/7 | https://en.wikipedia.org/wiki/Science_communication | reference | science, encyclopedia | 2026-05-05T06:57:07.866073+00:00 | kb-cron |
However, Einsiedel goes on to suggest both views of the public are "monolithic" in their own way; they both choose to declare what something called the public is. Some promoters of public understanding of science might have ridiculed publics for their ignorance, but an alternative "public engagement with science and technology" romanticizes its publics for their participatory instincts, intrinsic morality or simple collective wisdom. As Susanna Hornig Priest concluded in her 2009 introduction essay on science's contemporary audiences, the job of science communication might be to help non-scientists feel they are not excluded as opposed to always included; that they can join in if they want, rather than that there is a necessity to spend their lives engaging. The process of quantifiably surveying public opinion of science is now largely associated with the public understanding of science movement (some would say unfairly). In the US, Jon Miller is the name most associated with such work and well known for differentiating between identifiable "attentive" or "interested" publics (that is to say science fans) and those who do not care much about science and technology. Miller's work questioned whether the American public had the following four attributes of scientific literacy:
knowledge of basic textbook scientific factual knowledge an understanding of scientific method appreciated the positive outcomes of science and technology rejected superstitious beliefs, such as astrology or numerology In some respects, John Durant's work surveying British public applied similar ideas to Miller. However, they were slightly more concerned with attitudes to science and technology, rather than just how much knowledge people had. They also looked at public confidence in their knowledge, considering issues such as the gender of those ticking "don't know" boxes. We can see aspects of this approach, as well as a more "public engagement with science and technology" influenced one, reflected within the Eurobarometer studies of public opinion. These have been running since 1973 to monitor public opinion in the member states, with the aim of helping the preparation of policy (and evaluation of policy). They look at a host of topics, not just science and technology but also defense, the euro, enlargement of the European Union, and culture. Eurobarometer's 2008 study of Europeans' Attitudes to Climate Change is a good example. It focuses on respondents' "subjective level of information"; asking "personally, do you think that you are well informed or not about...?" rather than checking what people knew.
=== Frame analysis === Science communication can be analyzed through frame analysis, a research method used to analyze how people understand situations and activities. Some features of this analysis are listed below.
Public accountability: placing a blame on public actions for value, e.g. political gain in the climate change debate Runaway technology: creating a certain view of technological advancements, e.g. photos of an exploded nuclear power plant Scientific uncertainty: questioning the reliability of a scientific theory, e.g. arguing how bad global climate change can be if humans are still alive
=== Heuristics === People make an enormous number of decisions every day, and to approach all of them in a careful, methodical manner is impractical. They therefore often use mental shortcuts known as "heuristics" to quickly arrive at acceptable inferences. Tversky and Kahneman originally proposed three heuristics, listed below, although there are many others that have been discussed in later research.
Representativeness: used to make assumptions about probability based on relevancy, e.g. how likely item A is to be a member of category B (is Kim a chef?), or that event C resulted from process D (could the sequence of coin tosses H-H-T-T have occurred randomly?). Availability: used to estimate how frequent or likely an event is based on how quickly one can conjure examples of the event. For example, if one were asked to approximate the number of people in your age group that are currently in college, your judgment would be affected by how many of your own acquaintances are in college. Anchoring and adjustment: used when making judgments with uncertainties. One will start with an anchoring point, then adjust it to reach an assumption. For example, if you are asked to estimate how many people will take Dr. Smith's biology class this spring, you may recall that 38 students took the class in the fall, and adjust your estimation based on whether the class is more popular in the spring or in the fall. The most effective science communication efforts take into account the role that heuristics play in everyday decision-making. Many outreach initiatives focus solely on increasing the public's knowledge, but studies have found little, if any, correlation between knowledge levels and attitudes towards scientific issues.