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Detecting gradual change and variation: the sensitivity gap


Image: Yohan Marion / Unsplash.com
As Part 1 has illustrated, most democracy indices are designed to identify broad institutional change and support comparison across very different political systems. In high-performing democracies such as the Nordic countries, this can create ceiling effects: overall scores remain high and relatively stable even when gradual or uneven changes occur within particular democratic dimensions.
Building on the Nordic dataset approach outlined above, the next step would be to organise indicators from different sources within a detailed and conceptually coherent framework of democracy. Of the frameworks reviewed in Part 1, V-Dem provides the most elaborate and relevant backbone. Its five dimensions—electoral, liberal, participatory, deliberative and egalitarian democracy—are theoretically established, internationally comparable and connected to an extensive hierarchy of components, subcomponents and indicators. A Nordic framework could retain this architecture while selecting the V-Dem indicators most relevant and sensitive to variation among high-performing democracies. Indicators from other global datasets and comparable Nordic or country-level sources could then be added where they deepen an existing V-Dem component, improve sensitivity within the Nordic range or fill a clearly identified gap. This would preserve conceptual coherence and international comparability while producing a richer measurement framework better suited to detecting variation across the Nordic countries.
TiNDe, the Norwegian democracy assessment, provides a practical precedent for this approach. It uses V-Dem’s five dimensions as its conceptual foundation, supplements them with indicators from international and Norwegian sources, and reports disaggregated results across national, regional and local levels rather than a single overall score. A Nordic approach could apply the same logic in a more limited form, using a smaller set of regularly updated and comparable indicators (Dahlum et al., 2023).