D Duckett, J S Busby, S Onggo
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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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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

    • 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


  • 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


  • 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


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


  • 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


  • 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


  • 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


  • 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


  • 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)


  • 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


Risk level 10-2

10-3

10-4

10-5

Public

Industry

Independent

Time


  • 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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