Participation and e-Participation: Involving Stakeholders in the Management of Food Chain Risks in the Rural Economy

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Participation and e-Participation Involving
Stakeholders in the Management of Food Chain
Risks in the Rural Economy

• Simon French, Gary Barker,Clare Bayley, Emma
  Carter, Andy Hart, John Maule, Christoph Mohr,
  Richard Shepherd

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Plan

• Introduction and background
• Type of issue considered
• TED project
• HCI issues ? taken very broadly
• RELU project
• Issues of selecting appropriate
  (e-participation) methods
• Conclusions and questions

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Background

• UK rural community
• General social and economic change
• Specific impacts
• BSE
• Salmonella
• Foot and Mouth
• Rural Economy and Land Use Programme (RELU)
• Funded by UK research councils

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Cynefin model of decision contexts
Knowable Cause and effect can be determined with
sufficient data The realm of scientific inquiry
Chaos Cause and effect not discernable
Known Cause and effect understood and
predictable The realm of scientific knowledge
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Cynefin model of decision contexts
Knowable Cause and effect can be determined with
sufficient data Assess, learn and respond
Chaos Cause and effect not discernable
Known Cause and effect understood and
predictable Categorise and respond
Act, reflect, act
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Context expected by Government in handling issues
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and then as data accumulates
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What can we learn from the past?
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BSE
GovernmentDont worry trust the scientists
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FM
GovernmentDont worry trust the scientists
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ESF TED Programme

• Towards Electronic Democracy
• Can we use web-enabled decision analytic tools to
  involve citizens in deliberative democracy?
• An electronic Athenian ideal

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The middle ground
Wheredecision analysiscan help bring
deliberative e-democracy?
Representativeselected to takedecisions(Parliam
entary Democracy)
Individualsparticipateand votein all
decisions(Athenian Ideal)
Individuals interact and participate but
authorities or parliamentdecide.(e-participatio
n)
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First steps e-participation in analysis
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Human Computer Interface (HCI)

• Multiple users
• often untrained/unfacilitated
• So the HCI needs to recognise each users
• culture
• knowledge and skills base
• behavioural biases
• philosophy (e.g. Bayesian vs fuzzy vs AHP vs )

TED Workshop on HCI and e-democracy. Manchester
Business School Nov 9 11, 2005
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RELU-RISK

• Project just beginning
• Not sure what we are doing
• Possible scenarios
• Choice between strategies for improving hygiene
  in the food chain
• An increase in the occurrence of toxoplasmosis in
  pigs
• Relative risks from two pesticide regimes
• Withdrawal of exemption licence on existing
  pesticides

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How do we select appropriate (e-)participation
methods?

• Literature has
• Lots of theory
• Lots of big ideas
• Lots of studies of particular participation
  instruments
• A few comparative studies
• Very little guidance on selection
• and no agreement on terminology

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Possible objectives in design of participatory
process

• If we take a democratic ideal perspective,
  principles matter most.
• If we take the perspective of a regulator, the
  choice is based upon more pragmatic attributes

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Separation of science and values
Issues
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Have begun to build comparative matrices
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Process of participation

• We are not going to select a best instrument
• We need to develop a process in which several
  instruments are blended into a hybrid process
• E.g. a mix of web-sites with information and
  decision analyses, plus stakeholder workshops,
  plus postal consultation, plus
• Will there be interaction effects?

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Questions

• Particularly, please answer ours!