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The declining populations of many regions in Europe have led to a significant restructuring of services of general interest which, in many cases, meant concentrating them in fewer locations (Lang, 2012, p. 1749). This raised a discussion about the policy goals that should be at the core of these reconfigurations and, namely, how to balance the increasing per capita costs of these services with the need to guarantee minimum standards (Wiechmann & Pallagst, 2012). In other words, the shrinking number of users often imposes difficult policy decisions on whether to maximize equity in the accessibility to services, accepting that this implies increasing costs, or to maximize efficiency, decreasing service provision. Efficiency and equity can, in this sense, be considered elementary dimensions to assess public policies. But, while providing a useful framework (Bellinger, 2007; Le Grand, 1990), this dichotomy also raises important issues. Kunzmann (1998), for example, notes that spatial equity can mean “equal access to basic public facilities, measured in distances” (p. 103), but can also include the choices that are available and the way they relate to social equity. And, if spatial equity is understood as “justice with respect to location” (Morrill & Symons, 1977, p. 217), this stresses the importance of different theories of justice to understand differences in the spatial accessibility to amenities. Efficiency, on its turn, is generally concerned with minimizing the means necessary to achieve a given policy goal, having a more straightforward definition. However, this concept also raises questions regarding the distinction between means and goals, as well as the way in which the costs and benefits people draw from a given policy are considered (Bromley, 1990).
A further challenge is to translate these concepts into concrete measures to assess spatial layouts and to aid planning policy decisions. Technological development has, in this regard, created new opportunities for decision support systems, through a range of solutions based on optimized computational processing or data analysis. This has helped to establish a new contemporary planning praxis (Silva, 2010), increasingly concerned with incorporating tools to aid planning decisions (geographic information systems or algorithms) or to implement collaborative approaches (Machado & Azevedo, 2020; Somarakis & Stratigea, 2019; Wolf, Borges, Marques, & Castro, 2019).
This article contributes to this field by analyzing the spatial distribution of primary schools of the municipality of Vagos, in Portugal, while trying to find answers to a question raised when working with the municipality to devise a local school planning instrument (the so called school charts): How to adapt the distribution of primary schools to the decreasing number of students? For this analysis, it is important to take into consideration that primary schools in Portugal administer the first four years of formal education, corresponding to the first level of the International Standard Classification of Education (ISCED 2011), while municipalities are the second lowest tier of local government and are responsible for planning school facilities, but considering central government regulations and guidelines.