  Modern city governance relies heavily on crowdsourcing to identify problems
such as downed trees and power lines. A major concern is that residents do not
report problems at the same rates, with heterogeneous reporting delays directly
translating to downstream disparities in how quickly incidents can be
addressed. Here we develop a method to identify reporting delays without using
external ground-truth data. Our insight is that the rates at which duplicate
reports are made about the same incident can be leveraged to disambiguate
whether an incident has occurred by investigating its reporting rate once it
has occurred. We apply our method to over 100,000 resident reports made in New
York City and to over 900,000 reports made in Chicago, finding that there are
substantial spatial and socioeconomic disparities in how quickly incidents are
reported. We further validate our methods using external data and demonstrate
how estimating reporting delays leads to practical insights and interventions
for a more equitable, efficient government service.
