Notas para definição do conceito de GeoNarrativas
(1) Curtis, A; Curtis, J W; Porter, L C; Jefferis, E ;Shook*, E (Annals of the American Association of Geographers, 106(4) 2016) Context and Spatial Nuance Inside a Neighborhood’s Drug Hotspot: Implications for the Crime–Health Nexus
Preocupação do artigo: "New geographic approaches are required to tease apart the underlying sociospatial complexity of neighborhood decline to target appropriate interventions. "
Uso das GNs: "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." >> Identificar espaços de comunalidade e diferença
Distribuição de papéis na produção e uso dos dados: Pressupõe agregação de dados por especialistas, com pessoas locais, a serem encaminhadas para tomadores de decisão governamentais. Não se pressupõe auto-mobilização nem dos sujeitos atingidos pelo eventos (degradação de vizinhanças), nem pelos promotores dos eventos, nem por representantes parlamentares ou agentes judiciais (além da polícia, que inclui, no caso dos EEUU, promotorias de justiça): da conclusão: "Geographers are well placed to use the tools sug gested here and develop new theories and approaches to better educate governmental, private, and nonprofit organizations as to the complexity of neighborhood space, the importance of social context, and institu- tional spatial knowledge. To not rethink such inter- vention strategies is criminal. "
Definições e menções a geonarrativas:
Sobre "Spatial Video Geonarratives": uma estratégia para "capture fine-scale built environment visual qualities before providing an analysis of contextual understanding. Working at a microscale is vital if we are to understand “crimes” that have a surrounding social complexity: child exposure to violence, gang activity, and drug use. (...) to look for additional context with regard to one microspace of neighborhood notoriety and show how, in the planning of neighborhood assets, spatial context matters. (...) the processes that create hotspots, even for the
same type of event, could vary geographically. (...) To account for this, analyses could consider subneighborhood spaces such as street segments or block face aggregations or events aggregated to other subneighborhood artificial polygons such as a buffer, grid, or even viewshed (Stucky, Ottensmann, and Payton 2012; Payton, Stucky, and Ottensmann 2015). When analyses are conducted at the semiaggregate level (point-level crimes being aggregated to street sections), geographic crime unevenness starts to be revealed. (...) broken windows theory calls attention to
the physical and social conditions of a particular space. (...) The fact that either call for service or police incident data do not capture “the whole picture” is not a revelation; indeed, it is known that multiple sources of data are needed (Eck et al. 2005). (...) It is also important to tap into local voices to interpret these spaces correctly because the sequence that happens on one street is not replicated equally everywhere. As collecting built environment data is expensive and difficult to coordinate, some researchers have started to creatively utilize spatial resources such as Google Street View14 as a virtual windshield assessment into the character of the neighborhood being studied (Rundle et al. 2011). The challenge for many problematic urban areas is a lack of Google Street View coverage, both spatially and for the correct time frame, especially if the analysis is focused on the current situation (...).
>> Spatial video provides a similar resource to Google Street View but with more flexibility and control in terms of when and where data are collected, and an SVG, which can broadly be defined as a spatially informed commentary on the neighborhood, adds that missing context. § Spatial video and SVG also fit into the current theoretical shift in the health and crime field to incorporate the nexus of behavior and physical environment of “victims” in microspaces. (Berke 2010; Oliver 2010; Garner et al. 2012; Zonfrillo, Melzer-Lange, and Gittelman 2014). (...) is a relatively easily operated form of data collection and analysis that means multiple narratives can be overlaid to build a contextual census, resulting in a method that has transferability to different environments. This is imperative if we intend to examine the geographic transferability of microspace crime theories. In turn, these can help us interpret associated health outcomes, such as child injury locations, leading to more effective and comprehensive intervention strategies. (...) § SVG is a logical extension of previous work in qualitative geographic information systems (GIS; Jung and Elwood 2010), mixed methods (Knigge and Cope 2006), and the use of narratives (Hawthorne and Kwan 2013). One geographically focused form of interview is the geonarrative, which can include drive-along or walk-along interviews where the comments are inspired by the passing landscape (Anderson 2004; Jones et al. 2008; Kwan and Ding 2008; Carpiano 2009; Miaux et al. 2010; Evans and Jones 2011; Bell et al. 2015). The benefit of these approaches is that the environment, interviewee, and interviewer interact in a way that is captured and can be subsequently mapped. The SVG contains references to specific locations (e.g., house or corner store), as well as more general impressions and beliefs, such as the impact drugs have on the community. In addition, these narratives are stored in a spatial archive with associated images that facilitate subsequent reinvestigation for either validation or to provide “depth” if a pattern is revealed. From a spatial perspective, SVG can generate two types of narrative data suitable for spatial analysis: location specific and fuzzy space. §§§
>>The SVG consists of a typical spatial video collection with the addition of an “expert” sitting inside the car and making comments about the passing landscape. His or her commentary is captured on a digital audio recorder with an output cord splitting the narration onto each of the cameras. After data collection, the SVG audio is transcribed with media time stamps preceding any substantive comment or key location. The transcription is matched to the audio on the video source and the media time for both are noted. By extracting the GPS path from the camera, the associated Greenwich Mean Time (GMT) is matched to the media time. The High-Performance Computing and GIS Lab (HPCGIS) at Kent State University developed a textual interpolation program (G-Code) that interpolates every word across the spatial video collection path by matching the transcription time stamps to the corresponding GMT. G-Code uses a Web-based interface and the output is manipulated in a spreadsheet and imported into a GIS where the GPS path of the data collection route and the file of words (with their associated GMT) are joined. Using basic GIS operations, this layer can be mapped, manipulated, queried, and analyzed like any other point layer in a GIS.
**Conclusion** (...) to gain a better understanding of one particular problem, in this case a drug microspace, we need to work at the finest of scales and rethink our approaches to typical hotspot analysis. Although it is unrealistic to think that what we have suggested here will replace traditional data and analyses, in some instances it might complement it and at the very least raise the question as to where deficiencies might be found. In this regard, our academic contribution is in arguing for a greater appreciation of on-the-ground context. Our approach here has been using SVG, and although we must always be careful about placing too much weight on the observations of a single individ- ual, or even a small group, by the process of overlaying multiple SVGs, we achieve the triangulation necessary to gain previously unrecorded insight about places and their interactions at the finest of scales. "
Curtis, J W (Geographical Review 106 (3) July 2016) Transcribing from the mind to the map: tracing the evolution of a concept
Constroi o Estado-da-arte da pequisa sobre mapeamento produzido com expressões dos residentes/locais/participantes.
Curiosamente, não distingue operações de mapeamento de foco administrativo e participativo. Joga o próprio trabalho no mesmo balaio do do de Nold (Nold, Christian (Ed.) (2008? 2009?)_Emotional_Cartography) e Kwan e Ding (Kwan M. P.; G. Ding. 2008. Geo-Narrative: Extending Geographic Information Systems for Narrative Analysis in Qualitative and Mixed-Method Research). O primeiro é um mapeamento colaborativo devolvido aos participantes, de cunho poético-conceitual; o segundo, é uma investigação de estrito desenvolvimento metodológico, ou seja, com a própria geografia como interpretante final - o caso, de mudanças de percurso de mulheres muçulmanas sob pressão logo depois dos atentados de 11 de setembro, é tratado estritamente como exemplo: sequer é mencionado o encaminhamento político dos dados agregados.