# Methods for assessing social impacts of policies in relation to absolute boundaries

Nicolas Desmoitier, Mathilde Kolenda, Karen Holm Olsen, Morten Walbech Ryberg

► To cite this version:

Nicolas Desmoitier, Mathilde Kolenda, Karen Holm Olsen, Morten Walbech Ryberg. Methods for assessing social impacts of policies in relation to absolute boundaries. Environmental Impact Assessment Review, 2023, 101, pp.107098. 10.1016/j.eiar.2023.107098. hal-05093442

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# Methods for assessing social impacts of policies in relation to absolute boundaries☆

Nicolas Desmoitier<sup>a, b, *</sup>, Mathilde Kolenda<sup>a</sup>, Karen Holm Olsen<sup>c</sup>, Morten Walbech Ryberg<sup>a</sup>

## ARTICLE INFO

**Keywords:**

- Social impact assessment
- Absolute sustainability
- Safe and just operating space
- Social foundation
- Sustainability assessment framework

## ABSTRACT

There is an urgent need for designing truly sustainable policies supporting transformational change, and consequently for integrated tools to avoid burden shifting from different dimensions of sustainability. The Safe and Just Operating Space concept holds potential to support sustainable design of policies and decision making, using both the planetary boundaries framework and key social dimensions on an absolute perspective. Yet there is a lack of associated quantitative social assessment approaches. A new methodology is developed to evaluate the social sustainability of a policy against absolute boundaries. First, the methodology quantifies the state of a system, in 15 social dimensions defined systematically. Second, it estimates the social impacts of a new policy and observes if it will contribute to reduce the social shortfall. A geothermal energy development policy in Uganda is taken as an illustrative example for proof-of-concept. In the metrics of the Social Foundation of the Just Operating Space, the implementation of the policy would substantially improve the social performance of Energy and Health. Conclusively, this methodology holds potential to help early-phase policy design that do not unintentionally shift burdens between social dimensions, albeit further work remains to test the methodology and apply it in absolute integrated assessments.

## 1. Introduction

Anthropogenic pressures on the Earth System (ES) are starting to jeopardize the stability of the Holocene state that has been so important for humans to prosper (Rockström et al., 2009). These pressures risk pushing the ES into a new state that is less suited for sustaining current human societies and economies (Steffen et al., 2018). Thus, drastic systemic actions are needed within the next decade to avoid a potential destabilization of the ES and safeguard human and planetary health (Masson-Delmotte et al., 2018). Future business-as-usual trends fail to eliminate social shortfalls, while worsening the ecological crisis (Fanning et al., 2021). Thus, policymaking has a key-role to play in designing transformational policies that enable a disruptive shift from unsustainable practices to zero carbon and sustainable societies in line with the

objectives of the Paris Agreement and the United Nation's global Sustainable Development Goals (SDGs) (Olsen and Singh, 2020).

Furthermore, transformational policies need to address the interdependence of environmental, economic and social issues. It is important to develop policy- and decision-support methods and tools that cover all three sustainability dimensions to promote synergies and avoid simply shifting the burden from one dimension to another (Sala et al., 2015). Acknowledging the interdependence of the socioeconomic and environmental issues, Raworth coined the concept of the Safe and Just Operating Space (SJOS) for humanity to maneuver within, ensuring that humans' rights are respected while safeguarding environmental limits (Raworth, 2012, 2017). On the one hand, the environmental limits are expressed by the Planetary Boundaries (PBs) framework (Rockström et al., 2009; Steffen et al., 2015), which identifies and defines

<footnote><sup>a</sup> Quantitative Sustainability Assessment group, DTU Management Department of Technology, Management and Economics, Technical University of Denmark, Building 424, Kgs, Lyngby 2800, Denmark</footnote>

<footnote><sup>b</sup> GeM - Institut de Recherche en Génie Civil et Mécanique - UMR 6183, Nantes Université - École Centrale de Nantes - CNRS. 1, rue de la Noë - BP 9210144321
NANTES cedex 3, France</footnote>

<footnote><sup>c</sup> UNEP Copenhagen Climate Center, Marmorvej 51, Copenhagen Ø 2100, Denmark</footnote>

<footnote>* The authors are thankful for the support from the Supporting Preparedness for Article 6 Cooperation (SPAR6C) program funded by the German government's International Climate Initiative (IKI).</footnote>

<footnote>* Corresponding author at: Institut de Recherche en Génie Civil et Mécanique - UMR 6183, Nantes Université - École Centrale de Nantes - CNRS, 1, rue de la Noë - BP 9210144321 NANTES cedex 3, France.</footnote>

<footnote>E-mail address: nicolas.desmoitier@ec-nantes.fr (N. Desmoitier).</footnote>
boundaries for nine key ES processes, considered essential for maintaining the ES in a Holocene-like state. Hereby, the PBs delimit a 'safe operating space' for humanity. On the other hand, the social dimensions in the SJOS are covered by a set of social categories, which altogether form a 'Social Foundation' (SF), below which exists unacceptable human deprivation (Raworth, 2012). The SJOS defines a space for humanity to act within to be both environmentally and socially sustainable.

To operationalize the underlying concepts of the SJOS framework, methods assessing if a product or system is environmentally sustainable across its life cycle in absolute terms relative to the PBs, have recently been developed (e.g. Algunaibet et al., 2019; Li et al., 2019; Ryberg et al., 2018).

As for the SF of the SJOS, studies have sought to assess social sustainability in relation to absolute boundaries, with no consensus in the literature on operational frameworks (e.g. Acosta, 2022; Fanning et al., 2021; Hickel, 2018; Luukkanen et al., 2021; D. W. O'Neill et al., 2018; Randers et al., 2018). These studies have tried to operationalize the global SJOS for humanity to sub-levels (national or regional scales) to support and influence the decision-making process. It can serve as a communication tool (Dearing et al., 2014), as a tool to define the 'national safe and just spaces' (Cole et al., 2014) or as a comparative tool to quantify the resource use associated with meeting basic human needs across countries (Fanning et al., 2021; D. W. O'Neill et al., 2018). The definition of the social foundation can be challenged: are the sets of dimensions, indicators and thresholds used so far relevant? So far, methodologies were based on practical considerations rather than theoretical ones and consequently showed little consistency (Häyhä et al., 2016). Besides, when trying to set social thresholds, arbitrary and disputable decisions were made (D. W. O'Neill et al., 2018; Raworth, 2017). Rather, a more systematic approach is needed for identification and definition of indicators and boundaries.

This study aims at reviewing the social framework and implementing a more systematic approach to frame the social foundation. The purpose is to develop a method for defining social boundaries and setting minimum targets with regards to social sustainability. The method is intended for application as part of policy assessment to provide an indication of the social impacts of a policy on a system in relation to the social dimensions of the SJOS. Therefore, to illustrate the applicability of the method, it is applied to a simple illustrative case of a draft policy in Uganda. This is used to assess the social impacts of a policy on the construction of a geothermal plan that provides 1500 MW additional energy to Uganda by 2040, as described in a real Ugandan policy case study (Kolenda and Desmoitier, 2019).

## 2. Methods

### 2.1. Defining the social foundation

To assess impacts of policies relative to absolute boundaries, it is first required to investigate the current system's social performance in relation to the defined absolute boundaries, i.e. the 'baseline scenario'. The sustainability performance refers to the capacity of a system to maneuver within the SF of the SJOS. Then, the methodology deals with assessing impacts assigned to a specific policy with a forward-looking vision and in relation to the baseline results (referred to as the 'policy scenario'). The SF of the SJOS relies on the concept of 'deprivation' (Raworth, 2012; Townsend, 1987). Deprivation is defined in relation to the multiple facets of poverty: "Individuals, families and groups in the population can be said to be in poverty when they lack the resources to obtain the types of diet, participate in the activities, and have the living conditions and amenities which are customary, or at least widely encouraged or approved, in the societies to which they belong" (Townsend, 1987). In that respect, this study takes an individual perspective and has a focus on individual well-being. Ensuring that basic humans' needs (represented by the dimensions of the SF) are met is embodied in the definition of the 'just space' of the SJOS. To consistently

define the SF-framework, we propose three main steps, sequentially aiming at i) defining the SF dimensions, ii) selecting the indicators to represent the SF dimensions, and iii) setting absolute boundaries for the selected indicators.

#### 2.1.1. Definition of the social foundation dimensions

The dimensions of the SF were defined based on a literature review of studies operationalizing the SJOS framework, the SDG framework (United Nations, 2018), the original SJOS concept (Raworth, 2012, 2017) and the underlying reports, namely the theory of basic needs (Doyal and Gough, 1991), and the RIO + 20 countries priorities (Raworth, 2012).

As for the literature review, the following search strategy (TS = ("donut economic*" OR "doughnut economic*" OR "social foundation" OR "just operating space" OR ("safe and just" NEAR/2 space))) AND TS = (thresholds OR indicators OR operational* OR metric* OR measure OR downscal* OR dimensions), with restrictions to research articles written in English between 2009/01/01 and 2022/30/11, generated 49 results on the search engine 'Web of Science'. The search criteria did not explicitly encompass the term SDGs, as research studies utilizing the Donut economics are themselves based upon the SDG framework. Eventually, screening and assessment of the results left 11 studies for comparison and definition of the SF dimensions (Acosta, 2022; Capmourteres et al., 2019; Cole et al., 2014; Dearing et al., 2014; Fanning et al., 2021; Hickel, 2018; Luukkanen et al., 2021; D. W. O'Neill et al., 2018; Randers et al., 2018; Roy et al., 2021; Zhang et al., 2022) (see Supplementary Material (SM) fig. S1 for details). Defining the dimensions has comprehensively been based on the existing dimensions of the literature (see SM sections S2.1. and S2.2 for more details). As a result, 15 dimensions were found to be constitutive of the SF (see Table 1).

<caption>**Table 1**</caption>

Overview of the 15 social foundation dimensions, their associated top-ranked indicator and absolute boundary.

<table><thead><tr><th>Tier</th><th>Dimension</th><th>Indicator</th><th>Absolute boundary</th></tr></thead><tbody><tr><td>Tier 1</td><td>Food</td><td>Fraction of population undernourished (%)</td><td>0%</td></tr><tr><td>Tier 1</td><td>Water</td><td>Fraction of population using safely managed drinking water services (%)</td><td>100%</td></tr><tr><td>Tier 1</td><td>Sanitation</td><td>Fraction of population with access to improved sanitation (%)</td><td>100%</td></tr><tr><td>Tier 1</td><td>Housing</td><td>Fraction of urban population living in slums, informal settlements or inadequate housing (%)</td><td>0%</td></tr><tr><td>Tier 1</td><td>Income</td><td>Fraction of population living below the national poverty line (%)</td><td>0%</td></tr><tr><td>Tier 1</td><td>Education</td><td>Children aged 12–15 out of school (%)</td><td>0%</td></tr><tr><td>Tier 1</td><td>Energy</td><td>Fraction of population with access to electricity (%)</td><td>100%</td></tr><tr><td>Tier 1</td><td>Safety and Justice</td><td>Number of victims of intentional homicide per 100,000 people</td><td>0</td></tr><tr><td>Tier 1</td><td>Networks</td><td>National average of binary responses to the question "If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?"</td><td>100% of 'yes'</td></tr><tr><td>Tier 2</td><td>Work</td><td>Unemployment rate by sex, age and persons with disabilities (%)</td><td>5%</td></tr><tr><td>Tier 2</td><td>Gender Equality</td><td>Share of women in national parliaments (%)</td><td>50%</td></tr><tr><td>Tier 2</td><td>Life Satisfaction</td><td>Cantril life ladder (from 0 to 10)</td><td>6.5</td></tr><tr><td>Tier 3</td><td>Health</td><td>Life expectancy at birth (years)</td><td>75</td></tr><tr><td>Tier 3</td><td>Social equity</td><td>Palma ratio</td><td>1.2</td></tr><tr><td>Tier 3</td><td>Democratic rights</td><td>Voice and Accountability index</td><td>1.0</td></tr></tbody></table>
### 2.1.2. Selection of the indicators

Based on the 225 indicators identified in the literature review of dimensions of the SF, a selection process was developed to systematically select and assign one indicator per social dimension. All indicators retrieved from the reviewed literature were classified according to the social dimensions they relate to (gathered in Supplementary Data, by social dimension). Hereafter, each indicator was ranked based on its relevance to the social dimensions. The ranking was based on four criteria of different importance, presented here from most to least important: 1) Relevance, 2) Classification of the indicator in the UN Tiers, 3) Frequency, 4) Alignment with the SDGs (see Section S2.3 for more details on the definition of the four criteria). First-ranked indicators for each dimension were selected as SF indicators as depicted in Table 1.

### 2.1.3. Absolute boundaries definition

In this study, a socially sustainable state is defined when ‘no deprivation to humans’ is observed. There is no consensus for defining a boundary for expressing an absolute social sustainable state and such boundary is potentially normative. Thus, the dimensions were divided into three tiers, depending on the degree of certainty, credibility or scientific support with which the boundary for each SF indicator can be defined. Tier 1 includes dimensions, whose indicator directly measures deprivation or needs fulfillment (i.e. anti-deprivation) and the absolute boundary is, accordingly set to 100% or 0%, respectively. Tier 2 relies on existing research studies in which there is sufficient evidence to define a boundary. Tier 3 refers to dimensions, where there are few previously published studies and where the definition of absolute boundaries involves ethical, social or cultural perspectives. Thus, absolute boundary definitions for Tier 3 were based on empirical data and the Human Development Index (HDI), particularly with countries classified under the group ‘very high’ human development (see Section S2.4 for details). Absolute boundaries for all 15 dimensions are presented in Table 1.

The 15 social dimensions and their respective associated indicators define the social state of the system before the implementation of the assessed policy. By comparing this state with the absolute thresholds defined in this study, the absolute social performance of the system in the reference scenario is obtained. Then, social impacts of the assessed policy need to be quantified in the metrics of the indicators defined in this section and compared to the baseline scenario.

## 2.2. Ex-ante social impact assessment of a policy

The policy scenario consists of assessing the impacts associated with the implementation of a policy and of adding the impacts of the policy results to baseline scenario impact scores. Only impacts associated with the policy are considered in the comparison between the baseline and the policy scenario. All other conditions that might affect the scores of SF dimensions are kept constant, except for population growth, which is accounted for via population projections.

As opposed to environmental impacts which are governed by laws of physics well studied cause-effect mechanisms, social impacts are affected by human behavior, which can be unpredictable and irrational (Sircova et al., 2015), and quantitative social impact assessment models are less developed as they highly depend on cultural and regional context. The novelty of this study is to contribute to the development of a methodology for ex-ante social impact assessment of policies, as standardized methods for assessing social impacts in the context of the SJOS framework are lacking (Raworth, 2012). Several disciplines have developed to answer specific needs, such as Social Life Cycle Assessment (SLCA) with a focus on assessing social impacts from products and services (UNEP/SETAC Life Cycle Initiative, 2009) or Social Impact Assessment (SIA) to analyze, monitor and manage the intended and unintended social consequences of planned interventions (Esteves et al., 2012) (see SM Section S1 for more details). Drawing on these disciplines, a method for quantitatively assessing the social impacts of policies in

relation to the SFs was developed. The method consists of three main steps, which are detailed in the next sections:

1. impacts identification

2. significance assessment

3. impact quantification

### 2.2.1. Impact identification

The impacts identification (Step 1) relates to the identification of the potential positive and negative impacts that might arise from implementing the policy. This method draws on the method developed by Terrapon-Pfaff et al., 2017, which applies a participatory approach for identifying impacts. The process includes the following steps: (i) Identify relevant stakeholder groups impacted by the policy; (ii) build a diverse and comprehensive panel of people representing different groups affected by the policy; (iii) conduct surveys among this panel to list potential impacts. If i), ii), iii) cannot be performed, an alternative is to (iv) scan existing literature on similar implemented projects in similar conditions to list potential impacts. Lastly, it is needed to (v) classify all identified impacts within the dimensions of the SF.

### 2.2.2. Significance assessment

Step 2 aims at increasing the efficiency of the assessment and only focusing on important social impacts. Accordingly, a significance assessment is carried out to identify significant impacts. The significance assessment is based on four criteria on a five-point scale: Likelihood, Intensity, Geographic extent and Duration (Terrapon-Pfaff et al., 2017), and is used to estimate a final significance score for each identified impact (see SM Section 3.1 for more details). The final significance scores are, hereafter, ranked and classified as being either ‘very low’, ‘low’, ‘moderate’, ‘high’ or ‘very high’. Impacts classified as having a ‘moderate’, ‘high’ or ‘very high’ level of significance are selected and must be quantified. There may be cases where numerous impacts with ‘very low’ or ‘low’ significance all affect one specific SF dimension and, thereby, altogether have a significant impact. To avoid overlooking such cases, significance scores are summed per SF dimension and converted into an aggregated significance level per dimension. Here, dimensions with a ‘moderate’ or higher level of aggregated significance are included as part of the impact quantification step (referred to as ‘relevant dimensions’) (see SM section S3.1 for specific details).

### 2.2.3. Impact quantification

In Step 3, the impacts identified in Step 1 and Step 2 are quantified to facilitate a comparison between a policy scenario and a baseline scenario. Hence, the objective of Step 3 is to draw ‘social impact pathways’, that represent a range of causal relationships between indicators in an area of protection (Jørgensen et al., 2009) to quantify both significant impacts and overall impacts on relevant dimensions. Quantifying social impact pathways requires establishment and quantification of causal links between the policy outcomes, the significant impact(s) of the dimension and the associated social foundation indicator. However, in case mechanistic models could not be developed due to the complexity and non-linear characteristics of social behavior, it is recommended to use statistical correlations to express the relationship between different indicators on the social impact pathway and between different SF dimensions. A set of validation conditions were defined to judge if the correlation between e.g. two indicators is sufficiently strong, including a coefficient of determination ($r^2$ > 0.5) and a statistically significant correlation coefficient ($p$-value <0.05) (see SM section S3.2 for specific details).

## 2.3. Illustrative case: assessment of the geothermal energy development policy in Uganda

The methodology presented in Section 2.1 and 2.2 is applied in a
simple case study as a proof of concept to show the applicability of the methodology in practice and indicate the added value in terms of supporting policymaking. The case study is on the Geothermal Energy Development Policy in Uganda aiming at developing additional 1500 MW generated from geothermal energy by 2040.

### 2.3.1. *Baseline scenario*

Data for expressing the social status of Uganda was collected and compiled to construct the ‘baseline scenario’, where 2018 was selected as reference year. Thus, data for 2018 was prioritized and latest available data was used as a proxy if data from 2018 was not available (see Table A.1 for the overview of data sources used to construct the baseline scenario for social impacts). All dimensions were assessed except for *Sanitation*, due to lack of data, but this does not hinder the demonstration of the proof of concept as energy policy is not likely to have substantial effects on sanitation.

### 2.3.2. *Policy scenario*

The identification Steps i, ii and iii (see Section 2.2.1) involving stakeholder participation has not been performed for this illustrative case. To support decision-making in policy design, taking a participatory approach with the application of these steps would be necessary. In this study, as the policy only aims at being a proof of concept, the alternative option of performing a scan of existing literature on similar implemented projects was conducted, based on reports from the African Geothermal Inventory Database (UNEP AGID, 2014) in Uganda and neighboring countries (Bw'obuya, 2002; Mwangi-Gachau, 2011; Namugize, 2011; Oduor, 2010; Shortall et al., 2015; Zakkour and Cook, 2016). As a result, 51 potential impacts were identified (see Table S8). Similarly, the significance assessment and impact quantification were carried out by the authors of this study to illustrate the applicability of the methodology. Six impacts were found to be significant: four in the *Energy* dimension (*Decreased levelized cost of energy and electricity*; *Increased energy security*, *national independence and stabilization*; *Increased access to energy in households, public infrastructures*, etc.; *Increased share of clean energy*), one in *Income* (*Increased salaries for directly or indirectly involved employees*), one in *Health* (*Decentralization of energy systems and health centers*), plus one other relevant dimension, *Work*, for which the aggregation of numerous impacts with ‘Low’ or ‘Very low’ significance was found significant (see Table S8).

Based on the policy documentation and related literature (UNEP AGID, 2014), it was possible to construct and quantify impact pathways for the significant impacts pertaining to the *Energy* dimension and for the overall impact on the *Work* dimension. A correlation between the social foundation indicators of *Energy* and *Health* was built and validated to quantify the impact of the policy on the *Health* dimension. For the significant impact in the *Income* dimension, it was not possible to develop the impact pathway due to lack of data. Instead, a correlation between the social foundation indicators of *Energy* and *Income* was tested. Particularly, data points are scattered and no visible correlation can be observed when the 'Proportion of population living below the national poverty line' is plotted as a function of the 'Fraction of population with access to electricity'. Such correlation was found too weak, thus impacts on the *Income* dimension could not be quantified in this case (see SM Section S5 for details on the case-specific impact quantification and SM 1).

## 3. Results on an illustrative case

The results of the assessment are given in Fig. 1 in their normalized form (see Table A.1 for all social scores; see SM Section S4 for details on normalization method). Fig. 1 shows Uganda's current performance in the baseline scenario (colored areas) and the additional social impacts associated with implementation of the geothermal energy policy (grey areas). Notably, the theoretical fraction of the Ugandan population with access to electricity is estimated to significantly rise from 19% to 57%,

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Visualization of the current status of Uganda, i.e. the baseline and the social impact of the assessed policy. The results are plotted in their normalized form for each social dimension. Results for social foundation dimension *Sanitation* are not shown as relevant indicators and impact assessment model could not be derived.</figcaption></figure>

while life expectancy increases from 57.0 to 66.1 years. *Work* dimension did not show noteworthy changes, as unemployment rate decreased from 9.4% to 9.33%. Lastly, impacts on the *Income* dimension were not considered as they could not be quantified due to limited information to define the causal chain and a lack of correlation between the dimensions *Income* and *Energy* indicators.

## 4. Discussion

### 4.1. *Illustrative case in Uganda as a proof of concept*

#### 4.1.1. *Social impacts of the geothermal energy development policy in Uganda*

The methodology developed in this study, applied on the illustrative case of the Geothermal Energy Development Policy in Uganda, provides an assessment of the baseline scenario (Uganda country) in relation with the SF of the SJOS, and of the impacts on this policy on that system. The results show that Uganda is currently maneuvering in a high state of social deprivation (i.e. no absolute social boundary is met), particularly, within the *Energy* and *Water* dimensions. The introduced policy would improve the performance for four SF dimensions: *Energy*, *Health*, *Work*, *Income*, and significantly on *Energy* and *Health* dimensions. It appears logical that a net-increase in energy generation will have a positive impact on *Energy* in terms of the share of Ugandan population with access to electricity. However, the indirect increase in *Health* expressed as life expectancy is also an important benefit of the policy.

As a result, the policy is found to enhance social standards in Uganda and this benefit should be compared with potential further exceedance of the assigned share of the safe operating space in the metrics of the Planetary Boundaries. The impact assessment methodology presented in this study allows for evaluating social impacts of policies, or other large-scale changes in relation to absolute social boundaries. Here, results
allowed for identifying the potential social impacts of implementing the policy and how this would affect the current performance of the country. Indeed, being able to indicate the direct and indirect social effects of introducing a policy is an important contribution to better decision-making. Also, the qualitative assessment, i.e. impact identification and significance assessment, can already highlight what potential impacts would be significant in a policy scenario. This methodology and the visualization of the results could serve as a decision support tool to quickly assess the social impacts of a policy on a system in early-phase design and to prioritize subsequent in-depth studies.

### 4.1.2. Uncertainties

All types of impact assessments are subject to inherent uncertainties stemming from various sources, such as the selection of models and parameters used as input for the chosen models (Huijbregts, 1998). For example, parameter uncertainty is introduced for the social results from the significance levels defined by expert judgement. Uncertainty due to value choices is seen in the definition of the absolute social boundaries; and model uncertainty is introduced via the selection of models for quantifying social impacts. It is important to identify the various sources of uncertainty and quantify their contribution to the results. This is needed to provide results with confidence intervals and to take measures to reduce their overall uncertainty. It is common practice to provide policymakers with scientific results and their associated uncertainty for political decisions to be made accordingly (Masson-Delmotte et al., 2018). Considering the potentially high uncertainty of the results, it is recommended to use the developed methodology as an initial screening to make informed decisions and allocate resources in key areas, for which more specific assessments should be conducted. For instance, in the proof of concept, the Ugandan policy leads to substantial impacts on the *Health* dimension. However, quantitative results should be examined cautiously since no participatory approach was adopted and no quantification of the sensitivity nor uncertainty has been carried out in this study, and these areas should undergo further investigations. It is therefore recommended to complete the quantification with a participatory approach to corroborate the results including surveys, interviews or panel discussions for example.

## 4.2. Added value and potential of the developed methodology: holistic assessment of social impacts to support better policy making

### 4.2.1. Absolute perspective

The methodology presented in this study facilitates systemic assessment with the development of a framework for social impact assessment in the metrics of the SF of the SJOS. A novel aspect of the SJOS is to bring an absolute perspective when assessing systems' social performance, by defining boundaries for all social foundation indicators. The use of absolute boundaries allows for identifying if the evaluated policy is sufficient for increasing social dimensions to above the boundaries or if additional policies are required to reach a socially sustainable level. This is very relevant for policymakers as it allows for evaluating the efficiency of policies and, thus, designing policies or a suite of policies that are sufficient for making e.g. a country, sustainable in an absolute sense. Also, the consideration of all dimensions of social sustainability allows to highlight benefits and burdens across different social categories, i.e. potential trade-off. This study provides a first take on defining and operationalizing holistic assessments of social impacts relative to absolute boundaries and illustrate the potential of the approach to produce evidence-based and comparable assessment results. This type of approach can help reverse the logic by designing policies with the intention to be sustainable, i.e. use absolute boundaries as targets for policy definition.

### 4.2.2. Potential for early-stage policy development

This methodology holds potential to support decision-making in the design of policies seeking to raise social standards, with an effective

visualization and a holistic approach. The qualitative phase of impact identification allows for prioritization of specific impact quantifications, resulting in a relatively quick initial assessment of the policy which can be useful in early phases of policy design. In addition, this methodology could be used to compare the effects of several policies that are not necessarily related as well as to identify priorities: for example, the social impacts of a food policy could be compared with those of an energy policy. By extension, the combined effects of several policies and the degree they allow to stay within the Safe Operating Space could also be studied using this methodology.

### 4.2.3. Potential use in integrated absolute assessments

This methodology allows for contribution to design policies on an informed basis, where unintentional social burden-shifting can be avoided. It shows a great potential for supporting decision-making and early-stage policy development, especially if combined with an absolute environmental sustainability assessment. Indeed, there is a need for applying systemic approaches that cover both environmental and social aspects to address major challenges such as climate change, social (in) justice and economic growth (Daly et al., 2017). The ability to comprehensively evaluate a policy across a suite of social and environmental indicators is important to avoid unintentional burden-shifting of impacts among the social and environmental indicators. This is important to avoid cases, where policies that focus on improving a single, or a set of, environmental or social aspects have unintended negative impacts on other aspects and to evaluate trade-offs, where such negative impacts occur.

For instance, in Uganda, D. O'Neill, 2018 shows that “only” one of the seven PB covered in its study, namely *Land-system change*, is found to be transgressed in the baseline scenario. This is due mainly to Uganda's large agricultural sector where forest has been converted into arable land (Obua et al., 2010). For all other PB, Uganda operates within its assigned SoSOS. Thus, there is not a large need for introducing policies aiming at reducing environmental impacts because Uganda is generally acting within its assigned SoSOS. Instead, the focus of Ugandan policies should be to improve social conditions while not further exceeding the environmental ceiling.

## 4.3. Limitations and further work

The assessment methodology developed in this study shows a large potential for supporting policy-related decisions on the social aspect. Still, several challenges must be addressed and are subject to further work, to improve the applicability and robustness of the methodology. It is also recommended to test the methodology via application on different types of policies with stakeholders' engagement to detect potential dead-ends and other improvement needs.

### 4.3.1. Limitations in defining the social foundation

Defining boundaries for the SF comes with the underlying assumption that such universal standards exist. However, most choices, when defining boundaries, are normative and influenced by values, which are in turn context and time dependent. Therefore, it is essential to be transparent in the definition of boundaries. In this regard, the tiered classification of dimensions gives insights on which absolute boundaries are more consensual than others. Moreover, the definition of the SF's dimensions does not prevent potential overlaps between dimensions, which may result in over-representation of certain issues (e.g. *Housing* with *Water*, *Sanitation* or even *Energy*). Dimensions are also considered equally important, when it can be argued that some (e.g. *Food*, *Water*, *Health*) represent basic needs that are essential to fulfil, while others (e. g. *Democratic rights*, *Social equity*) are higher psychological needs, based on Maslow's hierarchy (Maslow, 1943). Further research could investigate if core social dimensions might be defined and might be given greater weight. It is important that the methodological limitations and the importance of value-based choices are further investigated, notably
through stakeholders' engagement and participatory approaches, to increase the robustness of the methodology. Further research could also examine the definition of the social foundation based on sufficiency, deprivation and human needs in different geographical and cultural contexts.

### 4.3.2. Further development of the SJOS impact assessment method

This methodology is developed with a focus on systems that have not reached the social foundation and probably nor overshoot the environmental ceiling, such as for low-income countries. This choice is reflected in the definition of indicators and the normalization of social scores, aiming at enhancing social standards. Practically, focusing on depicting the reduction of deprivations for all means overlooking what happens on the 'other side' of the social foundation. Therefore, it proves to be less adequate for systems that have high social standards (beyond the social foundation) at the expense of the PBs that might already be transgressed. Such trends are common patterns of 'high income countries' (D. O'Neill, 2018). Subsequently, other indicators would be required in order to reveal 'the social standards surplus' (what happens once the SF is met). For example, the indicator "% of population undernourished" of the Food dimensions could be changed to "Obesity rate". This approach would then serve a different purpose, aiming at granting a 'social budget', i.e. a maximum decrease or stagnation in social standards, for each reduction of environmental stress. It poses the following question: How to maintain good living standards, while drastically decreasing anthropogenic environmental pressures? To address this issue, the methodology could be adapted to not only look at minimum social foundations but also to account for excessive social conditions, and then compare with results of an absolute environmental sustainability assessment. This question is found to be highly normative though critical with the planetary state as expressed by the Planetary Boundaries framework. Further research could investigate the relation between the absolute social thresholds and their potential exceedance while maintaining our Earth System with Planetary Boundaries.

Even though the social assessment embraces socio-economic considerations through the Work or Income dimensions, it does not evaluate the performance of the economy at the system level. This simplification hides important parameters that could influence the sustainability performance of a system, as no sustainable state can be reached without levers to be pulled in the economic playing field (Biermann et al., 2012). While the end-goal of absolute social sustainability is people welfare, it is deemed interesting to take process-goals into consideration as levers to reach social sustainability, including large-scale economic variables, such as GDP or income distribution, to represent the response of the social states of a system to its economic evolution.

## 5. Conclusion

This study developed a novel methodology for evaluating the social impacts of policies in relation to absolute boundaries for social deprivation. The methodology allows for defining the social sustainability state of a system in 15 social dimensions and quantifying associated social impacts. It was tested on an illustrative example of a Geothermal Energy Development Policy in Uganda. The results identify the social impacts of implementing the policy for Uganda and to which extent the policy contributes to achieving social sustainability. Thus, we see that the methodology has the potential to express the effects of a policy on social conditions. This allows for gauging and evaluate the effect of future policies and designing policies or policy sets that allows for achieving social sustainability. This has the potential to be combined with assessments of environmental sustainability to evaluate to which extent policies contribute to staying within the Safe and Just Operating Space. Still, future work is needed on quantifying and indicating uncertainty of the results as well as further testing of the methodology in more case studies to detect potential needs for improvements. Nevertheless, transformational policies are required to address both environmental and social problems and it is imperative that environmental sustainability is not achieved at the expense of social sustainability. Thus, methods for assessing social sustainability of policies in an absolute perspective are needed to provide a holistic evaluation of policies to avoid potential burden shifting between environmental and social aspects. We see this method as an important aid for decision-makers as part of policy making and evaluation to ensure the development of policies that can provide the transformational changes needed for making humanity navigating within the Safe and Just Operating Space.

### Credit authorship contribution statement

Nicolas Desmoitier: Conceptualization, Methodology, Writing – original draft. Mathilde Kolenda: Conceptualization, Methodology, Writing – review & editing. Karen Holm Olsen: Validation, Resources, Writing – review & editing. Morten Walbech Ryberg: Validation, Supervision, Writing – review & editing.

### Declaration of Competing Interest

The authors declare that they have no conflict of interest.

### Data availability

I have shared the link to my data in Supplementary Material and Data.

## Appendix A. Detailed scores for social assessment

<caption>Table A.1</caption>

Scores for Uganda for each dimension of the social foundation for both the baseline and policy scenarios. n.a. stands for 'non-applicable', norm.score for 'normalized score'.

<table><thead><tr><th rowspan="2">Dimension</th><th rowspan="2">Indicator</th><th>Absolute</th><th rowspan="2">Baseline scenario</th><th colspan="2">Policy scenario</th></tr><tr><th>boundaries</th><th>Score</th><th>Score</th><th>Norm. score</th></tr></thead><tbody><tr><td>Food</td><td>Fraction of population undernourished (%)</td><td>0%</td><td>41.4%</td><td>0.586</td><td>2016; (FAO, 2023)</td><td>41.4%</td><td>0.586</td></tr><tr><td>Water</td><td>Fraction of population using safely managed drinking water services (%)</td><td>100%</td><td>6.44%</td><td>0.0644</td><td>2015; (WHO/UNICEF, 2017)</td><td>6.44%</td><td>0.0644</td></tr><tr><td>Sanitation</td><td>Fraction of population with access to improved sanitation (%)</td><td>100%</td><td>No data</td><td>n.a.</td><td>n.a.</td><td>No data</td><td>n.a.</td></tr><tr><td>Housing</td><td>Fraction of urban population living in slums, informal settlements or inadequate housing (%)</td><td>0%</td><td>53.6%</td><td>0.464</td><td>2014; (United Nations, 2023a)</td><td>53.6%</td><td>0.464</td></tr><tr><td>Health</td><td>Life expectancy at birth (years)</td><td>75 yr</td><td>yr</td><td>0.762</td><td>2012; (WHO, 2023)</td><td>yr</td><td>0.884</td></tr></tbody></table>

(continued on next page)
<table><caption>Table A.1 (continued)</caption><thead><tr><th rowspan="2">Dimension</th><th rowspan="2">Indicator</th><th colspan="2">Absolute</th><th colspan="2">Baseline scenario</th><th colspan="2">Policy scenario</th></tr><tr><th>boundaries</th><th>Score</th><th>Norm. score</th><th>Year and Source</th><th>Score</th><th>Norm. score</th></tr></thead><tbody><tr><td rowspan="2">Income</td><td>Fraction of population living below the national poverty line (%)</td><td>0%</td><td>19.7%</td><td>0.665</td><td>2012; (World Bank, 2023b)</td><td>19.7%</td><td>0.665</td></tr><tr><td>Unemployment rate, by sex, age and persons with disabilities (%)</td><td>5.0%</td><td>9.40%</td><td>0.927</td><td>2017; (ILOSTAT - LFS, 2023)</td><td>9.33%</td><td>0.928</td></tr><tr><td rowspan="3">Education</td><td>Children aged 12–15 out of school (%)</td><td>0%</td><td>31.4%</td><td>0.686</td><td>2008; (UNESCO - Institute for Statistics, 2023)</td><td>31.4%</td><td>0.686</td></tr><tr><td>Fraction of population with access to electricity (%)</td><td>100%</td><td>19.0%</td><td>0.190</td><td>2016; (IEA, 2017)</td><td>56.8%</td><td>0.568</td></tr><tr><td>Number of victims of intentional homicide per 100,000 people</td><td>0</td><td>11.5</td><td>0.890</td><td>2014; (United Nations, 2023b)</td><td>11.5</td><td>0.890</td></tr><tr><td>Networks</td><td>Number of victims of intentional homicide per 100,000 people National average of responses to the question “If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?”</td><td>100% ‘yes’</td><td>74%</td><td>0.740</td><td>2014; (Helliwell et al., 2019)</td><td>74%</td><td>0.740</td></tr><tr><td rowspan="3">Gender equality</td><td>Share of women in national parliaments (%)</td><td>50%</td><td>34.3%</td><td>0.686</td><td>2018; (Inter-Parliamentary Union (IPU), 2023)</td><td>34.3%</td><td>0.686</td></tr><tr><td>Palma ratio</td><td>1.2</td><td>2.0</td><td>0.862</td><td>2017; (UNDP, 2018)</td><td>2.0</td><td>0.862</td></tr><tr><td>Voice and Accountability index</td><td>1.0</td><td>- 0.6</td><td>0.518</td><td>2017; (World Bank, 2023a)</td><td>- 0.6</td><td>0.518</td></tr><tr><td>Life</td><td>Voice and Accountability index</td><td>1.0</td><td>- 0.6</td><td>0.518</td><td>2018; (Helliwell et al., 2019)</td><td>- 0.6</td><td>0.518</td></tr><tr><td>Satisfaction</td><td>Cantril life ladder</td><td>6.5</td><td>4.3</td><td>0.665</td><td>2018; (Helliwell et al., 2019)</td><td>4.3</td><td>0.665</td></tr></tbody></table>

## Appendix B. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.eiar.2023.107098.

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