D Duckett, J S Busby, S Onggo
Lancaster University
Department of Management Science, Lancaster University

• 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

• 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
Risk input to
Social processes produces
Amplified risk
Social actors attribute
Amplification of risk to
Other social actors

• 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

• Several forms of amplification attribution are evident in the data
Actors constructing amplification labels
Consequence
Retrospective
Corrective
Ancillary
Gap
Anticipatory
Media
Transboundary
Maverick-led
Plot
Other actors as objects of amplification labels and as authors of counterclaims

• 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

• 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 attributed to public amplification Communicated
+ risk level
+
–
Independent risk level
–
+
+
Espoused risk level
+
Corrected
+ risk level
–
Memory of industry amplification
+
Amplification attributed to industry
Industry
Public

• 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
Time
Public
Industry
Independent

• 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

• 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)

• 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)
Industry
+ –
Amenity demand subsystem
Amplification
• Assumed to be corrective
+
Communicated
+
–
Independent risk level
–
+
Espoused risk level
+
Amplification attributed to
+
Corrected
+ risk level
–
Memory of industry amplification
+ industry
Distrust & confusion subsystem
Public

• Now distrust and confusion limit & even overcome polarisation
Risk level 10 -2
10 -3
10 -4
10 -5
Public
Industry
Independent
Time

• 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