2.8: The C-modules: contingent modules
In addition to the compulsory content of the core A-module, and the optional content of the non-optional B-modules, a capability theory could also add a third type of module, which I will call the contingent modules . These are either modules that need to be taken on board due to some choices that have been made in a B-module, or else they are entirely optional, independent of what one has chosen in the B-modules. The following table gives an overview of the contingent modules.
Table 2.4 The C-modules: contingent modules
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C1: Additional ontological and explanatory theories C2: Weighing dimensions C3: Methods for empirical analysis C4: Additional normative principles and concerns |
2.8.1 C1: Additional ontological and explanatory theories
Two capabilitarian thinkers could each aspire to make a theory of justice, yet embrace very different views on human nature and on the degree to which certain outcomes can be explained solely by people’s choices or are also affected by structural constraints. This can matter a lot for the particular capability theories that one develops.
For example, in earlier work, I showed that the capability approach’s answer to whether there is anything wrong with the traditional gender division of labour depends a lot on the social ontological claims related to gender that are (implicitly) endorsed as well as the explanatory views of how that division of labour came about (Robeyns 2008c). If one believes that the fact that women end up doing most of the unpaid and care work, while men end up doing most of the paid labour market work, is a result of differences in talents, dispositions and preferences, then one would judge that the different functionings outcomes that result for men and women within households provide them with maximal levels of wellbeing given the formal institutional background that they face. But if one endorses a feminist explanation of this division of labour between men and women within households, then one is likely to stress power differences, the role of societal expectations and social norms in decision making, and so forth (e.g. Okin 1989; Folbre 1994). The same observed functionings outcomes in households with a traditional gender division of labour would then be evaluated differently.
Similarly, Miriam Teschl and Laurent Derobert argue that a range of different accounts of social and personal identity are possible, and this may also impact on how we interpret a person forfeiting a capability that we would all deem valuable (Teschl and Derobert 2008). If we believe that our religious identities are a matter of rational deliberation and decision-making, then we will judge the choice to physically self-harm because of one’s religion differently than if we have an account of identity where there is much less scope for choice and rational deliberation regarding our religious affiliation or other group memberships.
In short, different ontological and explanatory options are available in module C1, and they may have effects on various other elements or dimensions of the capability theory that are being constructed. However, we should be careful and not mistakenly conclude that ‘anything goes’ when we add additional ontological theories, since there should not be any conflicts with the propositions of the A-module — and, in addition, some ontological and explanatory accounts are much better supported by critical analysis and empirical knowledge.
2.8.2 C2: Weighing dimensions
For some capability theories, the prioritising, weighing or aggregating of dimensions (functionings and capabilities) may not be needed. For example, one may simply want to describe how a country has developed over time in terms of a number of important functionings, as a way of giving information about the evolution of the quality of life that may give different insights than the evolution of GDP (e.g. Van Zanden et al. 2014). Weighing dimensions is therefore not required for each capability theory or capability application, in contrast to the selection of dimensions, which is inevitable.
However, for some other choices that one can make in B1, the capabilitarian scholar or practitioner needs to make choices related to the weighing of the different dimensions. If that is the case, then there are different methods for how one could weigh. When considering which weighing method to use, the same factors are relevant as in the case of selecting the dimensions: the purposes of one’s capability theory, and the constraints one has to take into account when choosing a method.
In contrast to the overview works that have been written on how to select dimensions (e.g. Alkire 2002; Robeyns 2005a; Byskov forthcoming), capability scholars have written much less about which methods one could use to decide on the weights given to each dimension, specifically focussing on functionings or capabilities as the dimensions. What lessons and insights can we learn from what has so far been argued in this literature on the weighing of dimensions? (Alkire 2016; Alkire et al. 2015, chapter 6; Robeyns 2006b, 356–58)
First, the selection of weights for the capability approach is structurally similar to other multidimensional metrics (in the case of evaluations) or decision-making procedures (in case one needs to decide to which capabilities to give priority in policies or collective decision making). Hence one should consult existing discussions in other debates where multidimensionality plays an important role. Let us first look at the group of applications in which the capability approach is used to make decisions about what we, collectively, ought to do. That may be in an organisation; or at the level of a community that needs to decide whether to spend tax revenues on investing more in public green spaces, or in social services for particular groups, or in taking measures to prevent crime, or in anything else that can likely be understood as leading to positive effects on our capabilities. In those cases, we can learn from social choice theory, and from theories of democratic decision making, how we could proceed. 38 Decisions could be made by voting, or by deliberation, or by deliberation and/or voting among those who are the representatives of the relevant population.
Second, the applications of the capability approach that involve a multidimensional metric of wellbeing or wellbeing freedom could use (most of) the weighing methods that have been discussed for multidimensional metrics in general. Koen Decancq and María Ana Lugo (2013) have reviewed eight different approaches to set weights for multidimensional metrics, which they categorize in three classes: data-driven weights in which the weights are a function of the distribution of the various dimensions in the population surveyed; normative approaches in which either experts decide on the weights, or the weights are equal or arbitrary; and hybrid weights that are in part data-driven but in addition depend on some normative decision. Note that in the data-driven and hybrid approaches, the selection of dimensions and the weights tends to be done through a process in which the selection of dimensions and the determination of the weights go hand in hand. One example is the proposal by Erik Schokkaert (2007) of using happiness as the master-value by which we weigh the various capabilities that together form the multidimensional account of wellbeing. In this proposal, if the functionings do not contribute to one’s happiness, they are given a zero weight and hence no longer count in the wellbeing index. In methods such as this one, there are two rounds of the selections of the dimensions: the first before one collects the data, and the second when one uses econometric techniques to determine the contribution that the various functionings make to the master-value (here: life-satisfaction) and uses those as weights; those functionings that will make no contribution will receive a weight of zero, which is the same as being deleted as a dimension in the wellbeing index.
Third, for non-empirical applications, we can categorize methods to determine weights in the same way as we could categorise methods for the selection of dimensions. Morten Fibieger Byskov (forthcoming) distinguishes between ad-hoc methods (such as the data-driven methods discussed by Decancq and Lugo), procedural methods, or foundational methods. A theoretical capability application could include answers to all B-modules (including the selection of dimensions) yet decide that the weighing of those dimensions should be done in a procedural way, e.g. via a democratic decision-making process. Alternatively, one could introduce one master-value that will determine which capabilities are relevant, and also what weights they should be given. One example is the empirical work done by Erik Schokkaert (2007), which was discussed above. Another example, which is theoretical, is Rutger Claassen’s capabilitarian theory of justice, in which the selection and weighing of capabilities is done based on their contribution to that person’s “navigational agency” (Claassen 2016).
Note that in the case in which one has essentially a monistic theory in which there is a master-value, one may doubt whether this doesn’t violate property A7 from the A-module. At first value, it seems that it does. But proponents of a monistic theory may respond that all theories or measures ultimately must choose one principle or value that tells us something about the relative weight of the different dimensions. In Nussbaum’s work, they argue, there is also an implicit master-value, namely human dignity. It seems to me that this issue is not sufficiently analysed and the dispute not settled. One question one could raise is whether all master-values have the same function. It seems to be different whether the capabilities constitute the dimensions of a good life (as in the case of flourishing), or whether they contribute to the master-value. For the time being, we should in any case flag this as an issue to which more attention should be paid in the further development of our understanding of the capability approach.
2.8.3 C3: Methods for empirical analysis.
If in B1 one chooses an empirical study, one needs to know which methods to use. This is the task of the module C3. For example, the study could contain choices about which multivariate analysis tools to use or whether certain existing data sets are capturing functionings, capabilities, or merely rough indicators. In C3, we also make methodological choices related to empirical analysis: does a particular capability issue require quantitative analysis, qualitative analysis, or a combination? In part, the contours of the empirical analysis will be influenced by one’s ambitions and goals: is one trying to measure functionings and/or capabilities directly, or is one measuring resources and conversion factors in order to infer the capability set?
For empirical capability applications, these are of course huge methodological questions that need to be answered. These empirical methods questions may be particularly challenging for the capability approach for two reasons. First, because it is a radically multidimensional approach, and multidimensional analysis is by its very nature more complicated than a one-dimensional analysis. Second, in many cases, the relevant dimensions will include dimensions on which the collection of data is difficult, or on which no data are available — such as the quality of our social networks, the degree to which we do not suffer from excessive levels of stress, or our mental health. Nevertheless, as Alkire (2005, 129) rightly points out in her discussion on what is needed for the empirical operationalisation of the capability approach, one has to adopt the best existing empirical research (and its methods) that exists, and either master those new techniques that have been developed in other fields, or else engage in collaborations. Hick and Burchardt (2016, 88) raise the related point that there is a need for capability scholars to reach out and engage with related fields where similar themes and problems are faced. Only after that route has been travelled can we know the limits of empirical analyses of the capability approach.
2.8.4 C4: Additional normative principles and concerns
Finally, module C4 provides room for additional normative concerns or moral principles that capability scholars aim to add to their capability theory. For example, in a particular capability theory, a principle of non-discrimination may play a role or, alternatively, one may want to work out a capabilitarian theory that subscribes to the non-domination principle as it has been defended by Republican political theory (Pettit 2001, 2009). Or, if one ascribes to a rich account of empowerment that stresses the relevance of ‘power’ and hence strongly incorporates relational aspects (e.g. Drydyk 2013; Koggel 2013), then one may add a principle related to enhancing people’s empowerment, or prioritising the empowerment of the worst-off, as an additional normative principle to be added in module C4. Again, there are several elements belonging to module C4 that could be added to a capability theory.
38 In the case of democratic theory, the discussion is often about which laws to implement, but the same insights apply to policy making. Both the literature on democratic theory (e.g. Dryzek 2000; Gutmann and Thompson 2004) and social choice theory (e.g. Arrow, Sen and Suzumura 2002, 2010; Sen 1999c, 2017; Gaertner 2009) are vast and will not be further discussed here.