Crime is highly concentrated at places that lack capable place managers (i.e., landlords and their delegates). In response, numerous cities have instituted problem property interventions that pressure landowners to better manage properties suffering from decay, nuisance, or crime. This approach is distinctive in that it both targets a place and incentivizes those legally responsible to improve its management, yet little is known about the efficacy of such interventions. We assess the short‐ and long‐term impacts of such interventions in Boston, Massachusetts, using matched difference‐in‐difference analyses. Problem property interventions reduced crime and disorder relative to comparable matched properties. They also led to property investment and landowner turnover, suggesting strengthened place management. In addition, drops in crime and disorder were observed at other properties on the same street, although not at other properties with the same owner throughout the city. This study, therefore, provides evidence that problem property interventions compel landowners to better manage the targeted property and that these effects have a diffusion of benefits on surrounding properties. The effect on place management, however, was limited to the target property and did not reliably generalize to the landowner's other holdings. This study reveals nuance in the ways that problem property interventions can benefit communities.
more » « less- NSF-PAR ID:
- 10490222
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Criminology
- Volume:
- 62
- Issue:
- 1
- ISSN:
- 0011-1384
- Format(s):
- Medium: X Size: p. 64-89
- Size(s):
- ["p. 64-89"]
- Sponsoring Org:
- National Science Foundation
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Objectives Scholars and practitioners have paid increasing attention to problematic properties, but little is known about how they emerge and evolve. We examine four phenomena suggested by life-course theory that reflect stability and change in crime and disorder at properties: onset of issues; persistence of issues; aggravation to more serious types of issues; and desistance of issues. We sought to identify the frequency and dynamics of each. Methods We analyze how residential parcels (similar to properties) in Boston, MA shifted between profiles of crime and disorder from 2011 to 2018. 911 dispatches and 311 requests provided six measures of physical disorder, social disorder, and violence for all parcels. K-means clustering placed each parcel into one of six profiles of crime and disorder for each year. Markov chains quantified how properties moved between profiles year-to-year. Results Onset was relatively infrequent and more often manifested as disorder than violence. Pathways of aggravation led from less serious profiles to a mixture of violence and disorder. Desistance was more likely to occur as de-escalations along these pathways then complete cessation of issues. In neighborhoods with above-average crime, persistence was more prevalent whereas desistance less often culminated in cessation, even relative to local expectations. Conclusions The results offer insights for further research and practice attentive to trends of crime and disorder at problematic properties. It especially speaks to the understanding of stability and change; the role of different types of disorder; and the toolkit needed for problem properties interventions.more » « less
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Abstract This exploratory paper highlights how problem‐based learning (PBL) provided the pedagogical framework used to design and interpret learning analytics from C
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Learning analytic methods have been effective for understanding student learning interactions for the purposes of assessment, profiling student behaviour and the effectiveness of interventions.
However, the interpretation of analytics from these diverse data sets are not always grounded in theory and challenges of interpreting student data are further compounded in collaborative inquiry settings, where students work in groups to solve a problem.
What this paper adds
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The combination of principal component analysis and qualitative interaction analysis was critical in understanding the nuances of student collaborative inquiry.
Implications for practice and/or policy
Self‐directed actions in individual investigations are critical steps to collaborative inquiry. However, students may need to be encouraged to engage in these actions.
Clustering student data can inform which scaffolds can be delivered to support both self‐directed learning and collaborative inquiry interactions.
All students can engage in knowledge‐integration discourse, but some students may need more direct support from teachers to achieve this.
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