Beyond "beyond GDP indicators:" The need for reflexivity in science for governance

Abstract:

"Beyond GDP" initiatives flag the limits of the quantitative indicators of progress currently used for governance. Focusing on the quality assessment of quantitative information used for governance, we use some of the conceptual tools of theoretical ecology and evolutionary biology in order to identify the pre-analytical choices that determine the usefulness and pertinence of a model. Starting from the definition of a model as a formal representation of a specific and necessarily subjective observation, we show that the production of indicators is the final result of a series of decisions on what to observe and how. These choices, in turn, depend on the narrative, or set of narratives, adopted. Narratives provide causality and context to knowledge claims and are needed to select the indicators to be used for policy. Moving beyond the GDP debate requires reflexivity, that is, awareness of the key role that pre-analytical choices play in the definition of both the relevance of the chosen perceptions and narratives (determined by the normative stands of different actors - who defines wellbeing?), and the usefulness of the chosen models and data (determined by the pertinence of the resulting representation - how to measure wellbeing?). Reflexivity is essential in order to take into account the purposes for which different indicators were created and to define new purposes for the "beyond GDP" indicators.

Año de publicación:

2015

Keywords:

• Complexity
• quality assurance
• Integrated Assessment
• Sustainability
• Post-normal science
• UNCERTAINTY

Fuente:

scopus