Can streetblock 311 physical incivility call count shifts predict later changing on-site conditions? Gauging ecological construct validity of 311 litter calls

ABSTRACT

Statement of the problem. 311 call data are replacing on-site assessments as a popular alternative metric to gauge urban streetblock conditions, including physical incivilities like litter, trash and rubbish. Work to date, however, has not yet established the ecological construct validity, and thus the meaning, of streetblock 311 call counts for specific physical incivilities. The current work gauges this validity over time. Procedures. Philadelphia open source geolocated 311 data (35,055 streetblocks within all of Philadelphia’s 45 neighborhoods) were combined with streetblock litter scores from two open source on-site assessments made by trained city raters. Following the Hawley/Bursik change framework, this work examined connections between ecological discontinuities in 311 streetblock litter call counts and later ecological discontinuities in on-site litter assessments. Results/implications. Earlier 311 litter call count shifts connected positively albeit modestly to later assessed litter shifts. Nevertheless, so too did earlier call count shifts in a theoretically unrelated category. For this physical incivility, and perhaps others, category-specific streetblock call count shifts have demonstrated some modest convergent predictive validity, but not discriminant predictive validity. This is the first theoretically aligned, streetblock-level ecological change analysis linking 311 calls about a specific physical incivility to a specific corresponding on-site condition. Neighborhood spatiotemporal inequalities surfaced.

KEYWORDS:

• Community criminology
• ecological construct validation
• physical incivilities
• litter

Acknowledgment

The authors appreciate helpful comments from guest editors, two anonymous reviewers, Elizabeth R. Groff, Alese Wooditch, Graham Quinn and Marc Huffer.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The metadata can be found at https://metadata.phila.gov/#home/datasetdetails/555f812bf15fcb6c6ed44110/representationdetails/5d0d32e0656a70000b75f3a0/.

2. A quote from the metadata page.

3. A thoughtful reviewer questioned whether the 311 data here qualified as big data. Such a question is completely understandable since clarifying the defining characteristics of big data is an ongoing area of scholarly inquiry (Kitchin 2013, 2014b; Kitchin and McArdle 2016). Further, considerable hype surrounds this topic (Rae and Singleton 2015, 1). Kitchin (2014b: Chapter 2) provides an extended discussion of the defining characteristics of a big data set. The current data set contains many of these defining characteristics and so qualifies as ‘big data.’ Further, our treatment of Philadelphia 311 data aligns with O’Brien’s (2018) classification of Boston’s 311 data as ‘big data.’.

Additional information

Funding

The authors received no external funding for the preparation of this article.