NCJ Number
253177
Annotation
This study poses questions that advance the science of geonarratives through a case study of criminal ex-offenders.
Abstract
The importance of including a contextual underpinning to the spatial analysis of social data is gaining traction in the spatial science community. The challenge, though, is how to capture these data in a rigorous manner that is translational. One method that has shown promise in achieving this aim is the spatial video geonarrative (SVG), In the current study, 11 ex-offenders provided sketch maps and SVGs that identified high-crime areas of their community. Wordmapper software was then used to map and classify the SVG content; its spatial filter extension was used for hot-spot mapping with statistical significance tested using Monte Carlo simulations. Then, each subject's sketch map and SVG were compared. Results reveal that SVGs consistently produce finer spatial-scale data and more locations of relevance than the sketch maps. SVGs also provide explanation of spatial-temporal processes and causal mechanisms linked to specific places, which are not evident in the sketch maps. SVG can be a rigorous translational method for collecting data on the geographic context of many phenomena; therefore, this paper makes an important advance in understanding how environmentally immersive methods contribute to the understanding of geographic context. (publisher abstract modified)
Date Created: January 28, 2021