Does Distributive Justice Improve Welfare Outcomes in Climate Adaptation? An Exploration Using an Agent-Based Model of a Stylized Social–Environmental System
2. Theoretical background
2.2. Role of Distributive Justice
2.3. The Capability Approach to Operationalize Distributive Justice
2.4. Potential of ABM
3. Model Description
3.1. Model Conceptualization
3.2. Theoretical Exploration as Modelling Purpose
3.3. Model Narrative
3.3.1. Overview and Assumptions
Social Entities and Their Interactions
Capability Attainment and Access Potential
System State and Resource System Damages
Recovery of Resource Systems
Accounting of Overall Changes and External Random Damage
3.3.2. Overview of the System Dynamics
3.3.3. Operationalizing Principles of Distribution
- Egalitarianism: A strict egalitarian principle prescribes that each individual ought to have an equal number of resources and opportunities. In our model we operationalize this principle as a rule according to which all individuals in the societal system contribute all of the access potential they possess to a community fund. The access potential amount that has been pooled together is divided equally among people so that each individual has the same access potential with which to call on resource systems, giving them the same likelihood of obtaining the capability. This means that under an egalitarian redistribution in our model, all individuals have the same likelihood of obtaining the capability. This is a simplification we make, as realizing a capability in the real world depends not just on resource access but oftentimes on a multitude of social, political, and environmental conversion factors . With this approach we are able to evaluate the effects of an egalitarian principle under (idealized) circumstances where conversion factors other than resource access potential are equal for everyone.
- Sufficientarianism: A sufficientarian principle requires that each individual be brought up to a minimum acceptable level of well-being before resources may be directed to other actions. Under this distributive principle in our agent-based model, individuals with at least an acceptable capability attainment will prioritize expending their means or effort to help others in their network with unacceptably low attainments by obtaining the capability from a resource system unit on their behalf. They will then devote the remainder of their means or efforts to repairing resource system damages.
- Difference-proportionate sharing: Under this distributive rule in the model, an individual who has been able to maintain their capability attainment above an acceptable threshold will transfer an amount of access potential to the person with the lowest average capability attainment in their network. The amount is set to be up to half the difference between the access potential amounts of the two individuals. The intent behind this rule is for individuals with satisfactory capability attainment levels to locally redistribute an amount of their access potential in proportion to the advantage they have over more vulnerable individuals.
4. Experiment and Results
4.1. Redistribution of Access Potential
4.2. Outcome Indicators
4.3. Outcome Patterns
- The steep descent to zero of all four satisfactory capability attainment curves in Figure 3A shows that none of the four different modes of allocating the access potential is able to ensure system stability beyond a certain threshold value of the random damage limit parameter. This value differs across the modes, with the egalitarian one able to tolerate higher damage limits best, and (our implementation of) the sufficientarian one worst. These patterns emerge due to the extent of resource system damage repair that each distributive principle facilitates, which Figure 4D highlights.
- The egalitarian principle achieves the best results overall, generally increasing the fraction of people with a desirable capability attainment and decreasing the unacceptable attainment fraction. It is a clear improvement on the baseline scenario in which there is no redistribution of the access potential.
- The sufficientarian principle improves capability attainment at lower random damage values but performs significantly worse as the random damage value increases. It also results in the highest fraction of runs that end in collapse.
- The difference-proportionate rule improves capability attainment and run stability over the baseline no-redistribution scenario, but not to the extent that an egalitarian redistribution would allow.
- In Figure 4C, we see these patterns reflected also in the relative values for the minimum global mean capability attainment. The egalitarian redistribution, and to a lesser extent the difference-proportionate one, tend to raise it over values reached in the baseline case. The sufficientarian principle is only able to improve this at lower random damage values.
4.4. Baseline Scenario: No Redistribution
4.5. Egalitarian Principle
4.6. Sufficientarian Principle
4.7. Difference-Proportionate Rule
5.1. Model Analogies with Real World Situations
5.2. Contributions and Implications
- It adds a novel perspective to the nascent challenge of how to evaluate justice outcomes in model-based approaches to climate adaptation planning and policymaking. Our model presents a basic social–environmental system structure on which to operationalize distributive principles from justice theory as interaction rules. It provides a quantitative and stochastic testing ground to explore the consequences of certain normative ethical principles on general well-being outcomes. In doing so, our work contributes to extending the potential of ABM to account for ethical concerns in a climate adaptation context. It is also a small step towards bridging the gap between the realms of social systems modelling and applied ethics.
- Model-based representations of social–environmental systems must account for inherent systemic uncertainties to the extent appropriate for their purpose. For our model we opt for a simplified, generic representation that eschews context-specific details in favour of capturing the fundamental process that underlies society–environmental interactions: resource consumption leading to environmental impact. In whittling down societal entities and interactions to such basic forms, we essentially construct an idealized system in which the effects of a distributive principle manifest without being amplified or diminished by various sources of uncertainties. While our model is idealized and abstracts from some arbitrary contingencies, it does recognize the finiteness of ecosystems and is thereby more consistent with approaches that are built on the idea of planetary boundaries . We present this as a useful approach for performing a broad quantitative exploration of the relative merit of different distributive principles in a climate adaptation context.
- It contributes to the discussion on distributive justice as a societal precondition to ensure equitable and successful adaptation outcomes among differentially vulnerable people and groups. The generic social–environmental system of the model facilitates a comparative assessment of the impact of different principles of distribution on well-being outcomes in a finite-resource system. It gives insight into the types of distributive policies that are most likely to foster effective and fair climate adaptations, and how best to reallocate access to essential resources in society to that end.
5.3. Limitations and Future Work
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A. Overview of Experiment Results
Appendix B. ODD Model Description
|Purpose||To perform a comparative evaluation of the effects of different principles of distribution on the ability to attain an essential need in a stylized social–environmental system.|
|State variables and scales||There are two agent (turtle) types: individuals and (social–environmental) resource systems. Individuals possess an attribute called ‘access potential’ which differentiates them from one another. In the language of the capability approach, the access potential may be thought of as a personal conversion factor that determines one’s ability to attain an essential need. In the model we also consider another attribute called ‘social capital’ as being completely correlated with an individual’s access potential attribute. An individual’s social capital determines the number of resource systems and other individuals that they may interact with.|
Resource systems are characterized by their ‘system state’, an indicator of their health and capacity to provide the essential need. This attribute variable may be thought of as a socio-environmental conversion factor. The values of the access potential of individuals and the system state of resource systems both range from 0 to 1.
Access potential values do not change over time except when a distributive principle is implemented. The system state attribute of resource systems evolves as they provide the essential need to people and in the process accrue damages that need maintenance and repair.
|Process overview and scheduling||Setup:|
|Theoretical and empirical background||Actor heterogeneity in society entails unequal vulnerability to climate change impacts, and means that some people and groups will be better able to adapt than others. Justice requires a fair and equitable distribution of risks and benefits of adaptation actions across society (including as a means to foster resilience). Different principles of distribution are operationalized and evaluated against one another in terms of their effect on peoples’ ability to fulfil their essential needs, or capabilities in the language of the capability approach.|
|Individual decision making||For each tick, individuals evaluate their state of well-being. If their capability attainment running average is below a certain threshold, they will call on a resource system unit in their network to try to obtain the capability (or essential need). If it is above the threshold, the person will contribute to repairing damages incurred by resource systems, or to help ensure that people with inadequate access potential are also able to attain the capability (essential need), depending on the principle of distribution followed.|
|Individual sensing||Individual agents are aware of the states of other individuals as well as resource systems in their network. This allows them, for example, to select the most needy individuals in their network to help, or to perform repairs on the most damaged resource system unit(s).|
|Interaction||Individuals interact with the resource system units and other individuals in their own network. They call on resource systems to obtain the essential need (capability) and to repair the damages they have accumulated. Under certain principles of distribution, they seek out individuals to help and do so by sharing some of their access potential or by obtaining the capability on their behalf.|
|Collectives||Individuals and resource systems are linked in networks. However, each individual has their own network, and a person in that network is unlikely to have the same network for themselves as well.|
|Heterogeneity||Individuals possess different amounts of the access potential attribute, which sets up unequal capacities to obtain the essential need from resource systems.|
|Stochasticity||The following elements are stochastic in the model:|
|Observation||The model provides the following output:|
|Implementation details||The model is implemented in NetLogo 6.1.1.|
The following functions are used:
system recovery with maintenance effort = maintenance-effort * (system-state) ^ (1/2)
repair-impact = 1/(1 + exp (− (total-system-repairs − (minimum-system-damage-this-run + system-damage-range-this-run/2))))
net-system-state-change = (− damage-impact + repair-impact − random-damage)
If net-system-state-change >= 0:
system-state = system-state-old + (1 − system-state-old) *
net-system-state-changeIf net-system-state-change < 0:
system-state = system-state-old * (1 − (− net-system-state-change/100))
There are three different rules according to which the access potential may be (re-)distributed in the model, besides the ‘baseline’ scenario in which there is no re-distribution of access potential among individuals.
|Initialization||Individuals and resource systems are set up and linked; the number each individual is linked with is based on their social capital attribute value. Each individuals is assigned an access potential value from 0 to 1.|
|Input||Number of individuals and resource system units; desirable, acceptable, and unacceptable capability attainment thresholds; distribution principles for the access potential attribute; extent of random damage (as a representation of external stresses such as a climate change impact) suffered by resource systems.|
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|Model Parameter||Description||Value or Range in Experiment|
|Number of people||The population size of the stylized social system.||200|
|Number of resource systems||The number of resource system units that provide the essential need or capability.||12|
|Access potential||The attribute that determines an individual’s chances of attaining the capability, and the object of redistribution.||[0.00–1.00]|
|Random damage limit||The maximum amount of periodic damage not induced by resource consumption that resource systems may suffer.||[0.1–33.34%] of system state|
|Resource system operation threshold||The value of a resource system unit’s system state below which it ceases to function.||0.20|
|Principles of distribution||Principles we formalize as rules according to which the access potential is allocated or shared.||no redistribution; egalitarian; difference-proportionate; sufficientarian|
|Time limit for each run||The maximum number of time steps that each run is allowed to last.||3000 ticks|
|Capability attainment (moving average) levels:||These ranges for capability attainment values are used to categorize and assess the well-being of individuals.|| |
|Capability unit||The amount of capability that can be obtained from a resource system at each call (attempt).||0.75|
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Joshi, A.; Chappin, E.; Doorn, N. Does Distributive Justice Improve Welfare Outcomes in Climate Adaptation? An Exploration Using an Agent-Based Model of a Stylized Social–Environmental System. Sustainability 2021, 13, 12648. https://doi.org/10.3390/su132212648
Joshi A, Chappin E, Doorn N. Does Distributive Justice Improve Welfare Outcomes in Climate Adaptation? An Exploration Using an Agent-Based Model of a Stylized Social–Environmental System. Sustainability. 2021; 13(22):12648. https://doi.org/10.3390/su132212648Chicago/Turabian Style
Joshi, Aashis, Emile Chappin, and Neelke Doorn. 2021. "Does Distributive Justice Improve Welfare Outcomes in Climate Adaptation? An Exploration Using an Agent-Based Model of a Stylized Social–Environmental System" Sustainability 13, no. 22: 12648. https://doi.org/10.3390/su132212648