Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Equity in Resident Crowdsourcing: Measuring Under-reporting without
  Ground Truth Data   Modern city governance relies heavily on crowdsourcing (or "co-production")
to identify problems such as downed trees and power-lines. A major concern in
these systems is that residents do not report problems at the same rates,
leading to an inequitable allocation of government resources. However,
measuring such under-reporting is a difficult statistical task, as, almost by
definition, we do not observe incidents that are not reported. Thus,
distinguishing between low reporting rates and low ground-truth incident rates
is challenging. We develop a method to identify (heterogeneous) reporting
rates, without using external (proxy) ground truth data. Our insight is that
rates on $\textit{duplicate}$ reports about the same incident can be leveraged,
to turn the question into a standard Poisson rate estimation task -- even
though the full incident reporting interval is also unobserved. We apply our
method to over 100,000 resident reports made to the New York City Department of
Parks and Recreation, finding that there are substantial spatial and
socio-economic disparities in reporting rates, even after controlling for
incident characteristics.

21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess