Minding the Gap: Multi-Channel Citizen Voice as a Policy-Analysis Capacity

Governments that invest heavily in service-delivery infrastructure often find that citizen perception does not track operational improvement. This paper analyses Vision Vecino (“Neighbour’s View”), a citizen-listening framework operated by the Government of the City of Buenos Aires (GCBA) since 2022, as an attempt to bridge operational indicators and citizen perception for policy-analysis purposes. Using Parasuraman, Zeithaml and Berry's servicequality Gap Model and Bovaird's co-production typology, the paper reads Visi.n Vecino not as a satisfaction survey but as a policy-analysis capacity: a multi-channel architecture designed to explain divergences between operational dashboards and perception data, and to feed that explanation back into service redesign. Four cases — street cleaning, street lighting, sidewalks, and public health — are used to test where the framework produces usable insight and where it does not. The central finding is that Visi.n Vecino's real constraint is methodological heterogeneity: its strength (multiple, incommensurable data sources) is also its limit, because synthesis requires expert qualitative judgment that resists standardisation. The paper closes with an agenda-setting caveat: service improvements only translate into political capitalisation when citizens first recognise the problem as a problem, a precondition the Gap Model assumes rather than explains.