Communicating Science in Times of Crisis. Группа авторов

Communicating Science in Times of Crisis - Группа авторов


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conspiracy behind the catastrophe. The enemy inheres as an essential figure within the very concept of conspiracy.

       (Madisson, 2014, pp. 282–283)

      The invisibility underlying conspiracies is also one of the features that makes them resistant to opposing accounts, much less falsification—counterarguments and counterevidence not only do not take into account what is hidden but are misleading products of the cabal that seeks to remain hidden. Of course, Big Pharma has a profit motive to sustain science that supports vaccines, and, of course, China wants everyone to believe the science that 5G will bring only convenience and efficiency to our communications, rather than activating population control through its bioengineered virus. People who only pay attention to “the evidence” are simply not woke to what is happening in secret.

      Narrative Theory and Health Communication

      The narrative immersion model (Shaffer & Zikmund-Fisher, 2013) extends narrative theory into health communication specifically. It proposes five broad purposes served by narratives: to persuade (e.g., alter behavioral intentions), to influence (alter behaviors), to inform (increase knowledge or decrease uncertainty), to comfort (reduce anxiety) or to engage (transport, immerse, entertain, etc.). These purposes are sought by three types of health-related narrative types: outcome narratives (i.e., the mental or physical health outcomes or effects associated with a health-related factor such as a disease or a treatment), experiential narratives (i.e., the phenomenological symptoms, progression, and senses resulting from a disease or treatment), and process narratives that explain how a person makes decisions relevant to the disease or treatment (Shaffer & Zikmund-Fisher, 2013). The model predicts different effects with different narratives, which would also suggest ways in which narratives could be manipulated to be most relevant at various stages of a disease progression or pandemic history. The model proposes that narrative realism, source credibility (ethos), and entertainment value will influence the extent of a person’s immersion in a given narrative (Shaffer et al., 2018).

      Diffusion Theories

      Other theories may provide complementary insight into diffusion dynamics of dismisinformation. The multilevel model of meme diffusion (M3D) proposes that in information-dense ecosystems, any given message or message stream competes in an attention economy at both individual and collective levels (Magarey & Trexler, 2020; Ryan et al., 2020; Spitzberg, 2014, in press ; Stano, 2020; Zollo, 2019). In essence, humans are limited information processors facing an information ecology containing an almost infinite amount of information. In contrast to human selection, which by its nature is miserly, media contents, like nature, are profligate. Evidence suggests that people’s attention spans are decreasing as their media consumption continues to use more minutes per day of almost everyone’s quotidian activities (Spitzberg, 2019; Twenge, Martin et al., 2019; Twenge, Spitzberg et al., 2019). As Simon (1971) proposed axiomatically:

      In an information-rich world, the wealth of information means a dearth of something else: A scarcity of whatever it is that information consumes. What information consumes is rather obvious: It consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.

       (pp. 40–41)

      In such contexts, bright and shiny memes that become viral tend to attract attention and divert attention away from other potentially more important or legitimate sources of information. Indeed, a distinguishing feature of fake news as a rhetorical trope is their imitation and capture “of the time-sensitive media cycle—a daily routine of mass media consumption” (Avramov et al., 2020, p. 517), suggesting there may be prototypical lifecycles


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