This document discusses contested modelling approaches for sustainability interventions. It begins by noting that over-reliance on mathematical models has led to a loss of narrative and limited debate. It then examines different ontologies for understanding social-technical transitions, and questions whether modelling projects make their underlying ontologies explicit. The document also considers the purpose and enactment of modelling, and whether projects support reflexivity and stakeholder engagement. It analyzes several case studies along these dimensions and concludes by discussing challenges around validation and the need for wider stakeholder engagement in modelling to better support sustainability action.

1. Contested Modelling
Dr Mike Yearworth1, Dr Sarah Cornell2
[1] Reader in Engineering Systems, Faculty of Engineering
University of Bristol, UK
[2] Coordinator – Planetary Boundaries Collaboratory, Stockholm
Resilience Centre, Stockholm University, Sweden
17th July 2012

2. ! Starting points
• Over-mathematisation of models and reliance on
simulation has led to a loss of narrative and
representations  essentially black-box approaches
• Ownership and control of models is in conflict with
processes that might make them debatable with
publics
• Need for specialised techniques also limits debate to
between experts and narrow falsifiability as a
validation technique
• Focus on nomothetic approaches – universal models
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3. ! Method
• Can we get better at sustainability interventions
given our starting point in expert modelling?
• RQ: Do we (the authors) understand the relationship
between expert modelling and its publics?
• SRQ: Do we understand each other?
• Data sources – project experience (Sympact,
HalSTAR, CONVERGE, IHOPE)
• Theoretical lens – ontology, praxis and reflexivity
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4. ! Ontologies
• Geels§ identifies seven ontologies in analysing
social-technical transitions towards sustainability
• Rational choice, evolutionary theory, structuralism,
functionalism, interpretivism, conflict and power
structure, relationism
• cf Burrel & Morgan (Sociological Paradigms and
Organisational Analysis: Elements of the Sociology of
Corporate Life)
• Questions: Is there an underpinning project
ontology? Is there diversity? Made explicit?
§Geels,F. W. (2010) Ontologies, socio-technical transitions (to sustainability), and the multi-level
perspective. Research Policy, 39(4), pp. 495-510.
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5. ! Ontologies
Ontology Causal Agent Causal Mechanism
Rational Choice Self interested individuals Decentralised choice
Co-Evolution Populations Search, selection
Structuralism Belief systems ‘Deep structures’
Interpretivism Individuals, interpretations Shared meaning, sense-
making, debate
Functionalism Elements of a social system Enacting roles, feedback
Conflict and Power Groups with conflicting Struggle between groups
interests
Relationism Networks Interaction
Adapted from Geels, F. W. (2010) Ontologies, socio-technical transitions (to sustainability), and the
multi-level perspective. Research Policy, 39(4), pp. 495-510.
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6. ! Praxis & Purpose of Modelling
• Way in which theoretical knowledge of the expert
modeller(s) is enacted through intervention
• Modelling purpose is bound to the question of
enactment of intervention
• Questions: Is there a stated purpose to
modelling? Best mode of expressing the
models? Prediction (action outside scope) or
guide to action? If action, then is action research
explicit?
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7. ! Reflexivity
• Translating ideas of reflexivity into context of
environmental governance
• Sensitivity to inputs from diverse perspectives
• Recognising alternative ways of seeing issues of
concerns
• Questions: How does modelling support
reflexivity? Support stakeholder engagement?
Longer term engagement?
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8. ! Projects
• Sympact
• Generate predictions/scenarios around GHG emissions in
the digital media industry to inform strategy. LCA and SD
models.
• Functionalism
• Future intent to support wider engagement
• HalSTAR
• Grounded, holistic approach to assessing sustainability
options of civil engineering projects
• Functionalism, initially, moving towards interpretivism
• Latter leads to better reflection on original modelling task
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9. ! Projects
• CONVERGE
• Global sustainability, conceptualising equity within the Earth’s
natural biophysical limits
• Functionalism and structuralism with some interpretivist, conflict/
power structures
• Models intended to guide action, explicit action research
• Long term relationships with communities. And not…
• IHOPE
• Linking social and environmental sciences to understand
human-environment interactions over multiple timescales
• Functionalism, but some debate
• Recognises need to link to wide social and environmental
sciences communities to improve current Earth systems models
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10. Engagement of model users in process for action
Direct
HalSTAR
Sustainability Action:
Indirect
Sympact
CONVERGE
None
IHOPE
None Indirect Direct
Knowledge Building:
Engagement of stakeholders in model construction
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11. ! Validation – after Barlas§
• White box vs. black box modelling
• black box  quality of the predictions: do they match observational
data? [data-driven, correlational , possible abductive fallacies]
• white box  structure of the model: does the model explain how
observed behaviour is obtained? [theory-like, causal descriptive ]
• How do we validate explanations (structural validity)
i.e. get right behaviour for the right reason ?
• Functionalist worldview  objective representation of real world
 model is either correct or incorrect. Possibly true of other
ontologies
• Praxis view  one possible representation  continuum of
usefulness
§Barlas,
Y. (1996) Formal aspects of model validity and validation in system dynamics. !
System Dynamics Review, 12(3), pp. 183-210.
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12. ! Towards wider stakeholder engagement?
 this is not about open data, or open access to
publications (both are necessary but not
sufficient), and not really open source either…
• Possible approaches
• Argumentation (Toulmin, De Liddo, 2010)
• Participatory Action Learning (Perkons and Brown,
2010)
• Issue Based Information Systems (IBIS) (Buckingham
Shum, 2006, Conklin, 2003)
• Social Learning (Senge, 2005)
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13. ! Discussion Points
• If ultimately praxis is about behaviour change then what is
more important: accuracy or method of coupling with change
processes?
• Difficult for non-scientific public to make distinctions between
ignorance, uncertainty and contingent findings expressed as
testable hypotheses
• Predominately functionalist worldview of expert modellers is
mismatched to intervention generally – who has the view of
the “real” world?
• Ironically, in the area of sustainability this disconnect is
ultimately untenable (obviously?)
• Paradoxically, over-attention to being scientific closes
avenues for scientifically informed but systemic solutions
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14. Questions?
mike.yearworth@bristol.ac.uk
sarah.cornell@stockholmresilience.su.se
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