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Abstract
New geographic approaches are required to tease apart the underlying sociospatial complexity of neighborhood decline to target appropriate interventions. Typically maps of crime hotspots are used with relatively little attention being paid to geographic context. This article helps further this discourse using a topical study of a neighborhood drug microspace, a phrase we use to include the various stages of production, selling, acquiring, and taking, to show how context matters. We overlay an exploratory data analysis of three cohort spatial video geonarratives (SVGs) to contextualize the traditional crime rate hotspot maps. Using two local area analyses of police, community, and ex-offender SVGs and then comparing these with police call for service data, we identify spaces of commonality and difference across data types. In the Discussion, we change the scale to consider revealed microspaces and the interaction of both “good” and “bad” places. We enrich the previous analysis with a mapped spatial video assessment of the built environment and then return to the narrative to extract additional detail around a crime-associated corner store next to a community center. Our findings suggest that researchers should reevaluate how to enrich typical hotspot approaches with more on-the-ground context.
我们需要崭新的地理学方法来拆解邻里衰败的社会空间的根本复杂性, 以瞄准适合的介入方式。一般而言, 运用犯罪热点地图时, 相对较少关注地理脉络。本文运用邻里毒品微观空间——一个我们用来包含生产、贩售、取得和使用各阶段的措辞——之主题研究, 展现脉络如何相关, 藉此协助推进上述论述。我们对三群空间录像的地理叙事 (SVGs) 覆盖探索性的数据分析, 以脉络化传统的犯罪率热点地图。我们运用两地的警察、社区与前犯罪者的 SVG 分析, 接着将其与报警处理的数据相互比较, 指认出各数据类型之间的共同性与差异空间。我们于讨论中改变尺度, 以考量揭露的微观空间, 以及 “好” 与 “坏” 空间的互动。我们透过标示建成环境地点的空间录像评估, 丰富过往的分析, 接着回到叙事, 以取得社区中心一旁与犯罪相关的街角商店周围的额外细节。我们的研究发现主张, 研究者应该重新评估如何以更贴近现实的脉络来丰富典型的热点方法。
Se requieren nuevos enfoques geográficos para sortear la complejidad socioespacial que se halla detrás de la declinación de los vecindarios para apuntarle a intervenciones apropiadas. Típicamente, los mapas de puntos calientes de criminalidad son usados, prestándole relativamente poca atención al contexto geográfico. Este artículo ayuda a dar mayor impulso al estudio de estas cuestiones usando el examen tópico de un microespacio barrial de drogas, expresión que usamos para incluir las diferentes etapas de producción, venta, adquisición y toma, para mostrar cómo importa el contexto. Revestimos un análisis exploratorio de datos de tres cohortes de geonarrativas en vídeos espaciales (SVGs) para contextualizar los mapas tradicionales de puntos calientes de criminalidad. Usando dos análisis de área local de la policía, la comunidad y SVGs de ex delincuentes para compararlos después con datos de llamadas de servicio a la policía, identificamos espacios para compartir y de diferencia, al través de tipos de datos. En la Discusión, cambiamos la escala para considerar los microespacios revelados y la interacción de lugares “buenos” y “malos”. Enriquecemos los análisis previos con una evaluación espacial mapeada en vídeo del ambiente construido y luego retornamos a la narrativa para extraer detalle adicional en los alrededores de una tienda de esquina asociada con crimen, ubicada al lado de un centro comunal. Nuestros descubrimientos sugieren que los investigadores deben reevaluar la manera de enriquecer los enfoques típicos de los puntos calientes con un contexto más ligado a la realidad.
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Acknowledgments
Part of this paper was supported by the National Institute of Justice, Office of Justice Programs Award No. 2013-R2-CX-0004, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect those of the Department of Justice.
Andrew Curtis would also like to thank Susanne Mitchell, all at South St Ministries, Amy, Neal, and Mike at Radiant, Giancarlo and Lisa at Burning Shed, all at Earthside, King Crow, Panic Room, and Subsignal.
Notes
1. [0:21:56] Perception, I think perception kills a neighborhood, because once a neighborhood is deemed bad, it's hard to come in and refurbish and rebuild. It's hard to get people to move into an area that's considered a drug area or a bad area of town. (Police SVG)
2. We understand that neighborhood is a problematic measure of space. Here we use it for convenience to refer to the small sections of city relevant in the participants' residential activity.
3. Responding to a question about when crime is more likely to occur [00:28:32] “Now that it's getting warmer, like we joke around say, you know people are getting stupid because it's getting warm. Well, getting stupid means breaking the law, getting caught, getting in trouble … 'cause in the winter, it be so cold people don't want to go out and do anything. Now that it's warming up, people are like, “Oh I can do whatever I want now.” (Ex-offender SVG)
4. Responding to a question about hotspots [00:36:44] Yeah I don't know, it seems like it kind of migrates, too. When I first started two years ago, J street and K street was a huge area for that kind of activity and it's slowed down a little bit and it seems like they migrated more west and I'm not sure why that is. (Police SVG)
5. [0:04:00] But you have those certain, um, pinpoint areas where, uh, especially where the drug activity takes place, where drug dealers have come in and have been able to feel that sense of apathy in the community and in the neighborhood. And then set down roots there, set down a foundation there because they know that they can do whatever they wanna do and no one will object to it for the most part. (Police SVG)
6. This ex-offender's SVG describes why he believes so much criminal activity happens along one particular road. [0:03:23.3] This is one street where anything goes. You ever been around one of those streets where just anything goes? Because, uh, it seems almost like there's no morality on that street (laughs). (Ex-offender SVG)
7. We have encountered different ex-offenders who use the immediate vicinity around where they “live” to plan a robbery or use the abandoned house as a bolt hole after committing such a crime.
8. We have found that the length of residence is a good indicator of how determined a community member is to maintain that level of vigilance and guardianship.
9. [00:01:53] But they building these new houses in these bad areas, trying to reboost the area but a lot of people don't want them. (Community SVG)
10. Call for service data is a frequently used measure of the crime landscape. These data are also supplemented from other sources, such as police call-ins from a patrol.
11. We have been told in other SVGs that robbing friends and family is a preferred source because they are more likely to take pity and not report the crime.
12. Other forms of income generation include cooking meth and becoming a drug runner.
13. Different police officials have identified the rise of rental properties in a neighborhood as being an indicator of concern. This is especially true if a single individual owns multiple properties and is unscrupulous about the events that happen on his or her land. In our study, these single-owned properties can be identified by the same color of paint used.
14. Although this data source is a welcome addition, it does contain serious potential problems, especially the spatially varying date of coverage, which can change along a single road segment.
15. Google Street View imagery for our microspace of interest is from June 2011.
16. We use this term in its broadest sense to capture those who are victims of crime, of social circumstance, and of their immediate built environment deficiencies, including service accessibility, or suffering from a health disparity.
17. We purposefully do not use the name of the city or the neighborhood as we do not want to add to any negative perception of the area by having a name linked to any of the article's themes.
18. Many SVGs can be linked to an exact building or space: [00:13:58] Dealers and users. They used to have a house now they tore it down. [00:14:06] That used to be a house for dog fighting (on the right). [00:14:09] Interviewer: Hmm, like in the back or in the basement? [00:14:11] Basement. (Community SVG)
19. The following SVG contains Theme 1 followed by Theme 2: [00:17:55] Interviewer: Yeah, there (right) they had to board up their lower windows. [00:17:59] Yup, people in this neighborhood get scared. That's all they do is just shoot, shoot, shoot. (Community SVG)
20. Although different systems have been used, the camera in this study is a Contour Plus 2, which has an internal GPS.
21. Examples of this coding are shown in .
22. According to City-Data.com this neighborhood is approximately one square mile with a population of more than 4,600, approximately evenly split between African American and white residents. Median household income (2013) was slightly less than $25,000, median rent is slightly over $400, the majority of residents have less than a high school education, and over half of the population live in poverty. In 2013 the crime index was over twice the national average.
23. As reported in a presentation by the city police department.
24. There are different perspectives on the loss of the school, even within each SVG cohort. There is an idea that the school is a loss to the community and the kids now have to be bussed some distance, but the consensus seems to be that it was not in the best of conditions. [00:00:33] No, I mean, I used to go to this school when I was little. And they just recently tore it down, I don't know why. [00:00:47] I'm glad they did—it has a whole lot of effect on kids but I'm glad they took the school down because it's so much drugs in this neighborhood, crime, robberies, you know. (Community SVG) What sort of impact do you think that had on the community? [0:23:27] Well, I don't think it had a whole lot because this school was old, it was not really flourished and the quality, to me, of teachers was not that great. (Police SVG)
25. A recent example is the new Centers for Disease Control guide at http://www.cdc.gov/nccdphp/dch/built-environment-assessment/, but many audit tools exist (e.g., Day et al. Citation2006; Seymour, Reynolds, and Wolch Citation2010; Wong et al. Citation2011).
26. The built environment survey was coded using a variant of the recovery score (RS) developed to assess building condition during postdisaster recovery (Curtis and Mills Citation2011).
27. [00:32:06] There's actually a guy that just got murdered here, I don't know a couple, two months ago, three months ago, he supposedly had a meth lab in his basement. [00:32:14] He was a meth cook. (Police SVG)
28. If a mention of drugs occurs at the edge of the neighborhood, because there are fewer residential parcels in the denominator, the rate is exaggerated. Clipping by the neighborhood boundary reduces this effect, although the rates of nodes close to the edge should also be interpreted carefully.
29. It is possible that selecting a different set of subjects will result in a different map. This is more likely with B than A. With the contextual maps of both community members and ex-offenders identifying this space, however, there is enough evidence to warrant further investigation. In this way the approach we detail here should be seen as a representative sample of the neighborhood, but results still might have a fuzziness that varies by year, season, and even subject choice.
30. Ibid.
31. [00:51:13] This carry-out up here used to be a bad area for us, here as you guys can see on the right they're actually tearing down one of the houses. So I think we've seen, what, three or four of those already in this area that they're still tearing down after all these years. (Police SVG)
Additional information
Notes on contributors
Andrew Curtis
ANDREW CURTIS is Co-Director of the GIS Health & Hazards Lab and Professor in the Department of Geography at Kent State University, Kent, OH 44242. E-mail: [email protected]. His research interests include methodological advances in understanding fine-scale complex geographical interactions in health, hazard, and crime landscapes for data-poor environments.
Jacqueline W. Curtis
JACQUELINE W. CURTIS is Co-Director of the GIS Health & Hazards Lab and Assistant Professor in the Department of Geography at Kent State University, Kent, OH 44242. E-mail: [email protected]. Her research interests include geospatial approaches to understanding the linkage between environmental perception and behavior in postdisaster and other derelict places and with marginalized communities, especially children.
Lauren C. Porter
LAUREN C. PORTER is an Assistant Professor of Criminology and Criminal Justice at the University of Maryland, College Park, MD 20742. E-mail: [email protected]. Her research interests include punishment, the overlap between demography and crime, and the relationship between crime and place.
Eric Jefferis
ERIC JEFFERIS is an Associate Professor in the Department of Social and Behavioral Sciences, College of Public Health, Kent State University, Kent, OH 44242. E-mail: [email protected]. His interests include evaluations of community-based violence prevention programs and studies of intentional injuries.
Eric Shook
ERIC SHOOK is Director of the High-Performance Computing and GIS Laboratory and Assistant Professor in the Department of Geography at Kent State University, Kent, OH 44242. E-mail: [email protected]. His research is situated at the intersection of geographic information science and computational science with particular emphasis in the areas of cyberGIS, spatiotemporal analytics and modeling, and location-based social media.