Indicator Framework for the Sustained Support Programme for the Arts (Quadrennial) S4P-24 Policy Brief 6701/2024 - Neves, J. S.; Caramelo, S.; Adrião, J. G.; Lima, M. J.; Alves, Nuno de Almeida (Ciência para as Políticas Públicas, 2026)
Arts funding is a widespread cultural policy mechanism in Western countries that aims to expand and diversify professional cultural offer and democratise access to culture. In Portugal, its legal framework dates back to the early 1990s. It has undergone several changes over time, but no system of indicators has ever been created for its monitoring and evaluation. This project is part of a practice of producing information to support the formulation of public cultural policies in the arts that has been implemented in recent years in Portugal. It is part of a process that converges towards one of the main challenges of current public policies: the growing need for results-oriented management of intervention programmes based on (or informed by) evidence in decision-making, planning, implementation and, where relevant, changing policies, projects and services. The object is the four-year Sustained Support Programme implemented by the Directorate-General for the Arts (DGARTES). Based on the construction of the Programme's Theory of Change, the central objective of the project was to design a Framework of Indicators for monitoring and evaluation that would enable the Programme's decision-makers and management structures to: (i) Identify trends in its various dimensions; (ii) Improve the operational effectiveness of management, particularly in terms of gains in effectiveness, efficiency, equity and sustainability of the intervention; (iii) Implement adjustment or reprogramming processes, as well as improve the design of future policy instruments; (iv) Promote and facilitate the programme evaluation process, strengthening the evaluability and quality of the evaluation exercises. The proposed Indicator Framework consists of 43 indicators, of which 18 are for monitoring and 25 for evaluation. Given the complexity of operationalisation, it is recommended that implementation be gradual, with pilot tests and iterative adjustments, combined with clear guidelines on data quality and the use of results in decision-making processes.