It’s A Kind of Magic! Addressing The Arnstein Gap in Planning with the QICE Public Participation Performance Framework

Abstract

The gap between citizens’ aspirational desires for public involvement quality in planning and the perceived current level, a.k.a. the Arnstein Gap, is well-documented (Bailey and Grossardt 2006, 2010). Authors Bailey and Grossardt have demonstrated in recent work how this Arnstein Gap is consistent across different geographical contexts and that it has remained more or less consistent across twenty-five years of these measurements (Bailey 2019, Bailey and Grossardt 2025). To the degree that Arnstein Gap presents a societal problem, for instance, a large Gap reflects lack of public confidence in professional activities and plans, and thereby signals a lack of legitimacy in the planning system overall, it is a problem that merits attention, analysis, and efforts directed at solution – even if these can only ever be partial (Weymouth and Hartz-Karp 2019). Building on previous work including CORP here I explore strategies that planners can use for delivering strong public involvement performance and thereby nudging the Arnstein Gap smaller. Strategically avoiding engineering process aims around slippery, opaque, loaded and contradictory terms including “trust” and “consensus” (Shakeri 2025), this paper applies the QICE (Quality, Inclusion, Clarity, and Efficiency) framework for public involvement design and measurement and explores how QICE allows planners to address the competing desires of multiple stakeholder groups including citizens, planners, and project managers and sponsors (Bailey et al. 2015). Performance measurements are presented and the impacts are discussed using extensive real-world data from more than twenty years of project work. With acknowledgment to Freddie Mercury and his bandmates, this is not really “A Kind of Magic”; instead, these results suggest that public involvement process design using a multistakeholder framework in conjunction with careful operationalization that includes logical method selection and sequencing can deliver high performance across multiple criteria