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D Duckett, J S Busby, S Onggo Lancaster University. The social amplification of risk & zoonotic disease outbreaks. Department of Management Science, Lancaster University. Social amplification of risk Laypeople not going along with expert assessment A source of disproportionate response

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slide1

D Duckett, J S Busby, S Onggo

Lancaster University

The social amplification of risk & zoonotic disease outbreaks

Department of Management Science, Lancaster University

slide2

Social amplification of risk

  • Laypeople not going along with expert assessment
    • A source of disproportionate response
    • An obstacle to progress
    • The need to manage the ‘issue’ (Leiss 2001) as well as substance
  • The Social Amplification of Risk Framework (Kasperson et al 1988)
    • Signals that get magnified or diminished
    • Secondary or ripple effects that are generated
    • Applied with apparent success to BSE, WJD, SARS...
  • The trouble with SARF
    • The idea of a real, ‘accurate’ risk that’s amplified (Rayner 1988)
    • The implication that amplification should be overcome (Rip 1988)
    • The response (Kasperson et al 2003) as a motte-&-bailey defence
slide3

Social amplification of risk

  • Keeping amplification but only as an attribution (Busby et al, 2009)
    • Can produce objective outcomes: polarised risk perceptions
    • Helps explain how people resist systematically different views
    • Encourages reflexive understanding
      • Not ‘X is amplifying’ but ‘why is X attributing attenuation to us?’
      • Important when people understand risks socially
  • A project applying this idea to zoonotic disease outbreaks
    • Fieldwork looking at how people explain their responses to risk
    • Simulation modelling exploring the consequences of amplification
    • Funded by EPSRC jointly with NCZR

Social actors

Risk

input to

attribute

Amplification of risk

Social processes

produces

to

Amplified risk

Other social actors

slide4

Fieldwork: how people talk about risk & amplification

  • A natural starting point to look at attributions in discourse surrounding risk
  • Qualitative analysis of rich textual data in which people make sense of
  • zoonotic cases
    • Lay Focus Groups
      • PhD students from management related disciplines
      • Veterinarian PhD students
      • Retired lay people
      • Mothers of young children
    • Expert individual & group interviews
      • Regulators
      • Farming interests
      • Epidemiologists
      • Virologists
      • Veterinarians
      • Science journalists
slide5

Fieldwork: categories of attribution

  • Several forms of amplification attribution are evident in the data

Consequence

Retrospective

Corrective

Ancillary

Gap

Anticipatory

Media

Transboundary

Maverick-led

Plot

Actors constructing amplification labels

Other actors as objects of amplification labels and as authors of counter-claims

slide6

Fieldwork: important points

  • Amplification is relational
    • Social relationships determine how risk responses are viewed as
    • amplified or attenuated & are often contested
  • Amplification often then attributed as an instrumental strategy
    • Eg informercial campaigns, import/export policies, media headlines
  • Authoritative and lay assessments are by no means equal
    • But authorities may benefit from understanding attributions to them
slide7

Modelling social risk amplification as an attribution

  • A 2-actor system dealing with a single event
    • Both actors form risk judgments based on same datum
    • But also taking account of the other’s expressed risk beliefs
    • And correcting for remembered, perceived amplifications

Memory of public amplification

Industry

+

Amplification

attributed to public

Communicated risk level

+

+

Independent risk level

+

Espoused risk level

Amplification attributed to industry

+

+

+

Corrected risk level

Memory of industry amplification

+

Public

slide8

Modelling social risk amplification as an attribution

  • This is unstable
    • The 2 actors’ risk levels diverge strongly over time
    • Following eg changes in datum and anticipations
    • Although memory limits lead to saturation of polarisation
    • Simple refinements preserve instability
      • Delays & imperfections in observation and remembering
      • Other actors assumed to distort in opposite sense

Risk level 10-0

10-1

10-2

10-3

10-4

10-5

10-6

Public

Industry

Independent

Time

slide9

Modelling social risk amplification as an attribution

  • Stability only when actors accept other views uncritically
    • Despite shared datum
    • And memory reset at the start of the event
  • No attempt at calibration so timescales uninformative
    • Sensitivity of critical time for polarisation to reach threshold
    • Exogenous factors (discounting, anticipation) have little effect
slide10

Modelling social risk amplification as an attribution

  • Adding features
    • Endogenising the weighting given to others’ beliefs
      • Reflecting the role of distrust (eg Frewer 2003)
        • Determined by perceived distortion, bias, wrongness
      • And perception of confusion (eg Bergeron and Sanchez, 2005)
        • Determined by rate of change of risk belief
    • Capturing the link to and effect of behaviour
      • Perception affects demand, exposure & assessment
      • Assumed to be corrective
      • Action may be easy yet seem disproportionate (Rip 2006)
slide11

Modelling social risk amplification as an attribution

  • Adding features
    • Endogenising the weighting given to others’ beliefs
      • Reflecting the role of distrust (eg Frewer 2003)
        • Determined by perceived distortion, bias, wrongness
      • And perception of confusion (eg Bergeron and Sanchez, 2005)
        • Determined by rate of change of risk belief
    • Capturing the link to and effect of behaviour
      • Perception affects demand, exposure & assessment
      • Assumed to be corrective
      • Action may be easy yet seem disproportionate (Rip 2006)

Memory of public amplification

Industry

+

Amplification

attributed to public

Communicated risk level

+

Amenity demand subsystem

+

Independent risk level

+

Espoused risk level

Amplification attributed to industry

+

+

+

Corrected risk level

Distrust & confusion subsystem

Memory of industry amplification

+

Public

slide12

Modelling social risk amplification as an attribution

  • Now distrust and confusion limit & even overcome polarisation

Risk level 10-2

10-3

10-4

10-5

Public

Industry

Independent

Time

slide13

Conclusion

  • Social risk amplification looks important for managing outbreaks
    • Supporting idea that risk beliefs can be systematically mistaken
  • But it’s hard to accept it as an objective description
    • Based on the distortion of a true level of risk
  • Moving to the idea of amplification as a subjective attribution...
    • Shows structure: different categories & significance
    • Has consequences: likely polarisation with saturation
  • And suggests for policy makers...
    • The need to be careful in anticipating distortion among publics
    • The value of asking why others attribution amplification to you
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