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This article draws on recent studies to argue that researchers need to be attentive to the limits of the neighborhood effect as conventionally understood. It highlights the complexities of contextual influences and the challenges in accurately representing and measuring individual exposures to those influences. Specifically, it discusses the idiosyncratic and multidimensional nature of contextual effects, the temporal complexities of contextual influences, the frame dependence of exposure measures, selective mobility bias, and publication bias in neighborhood effects research. It also discusses how contextual uncertainties could be mitigated in future research (e.g., through collecting and using high-resolution space-time data and moving toward frame-independent exposure measures with results that are not affected by how data are organized with respect to space and time). [ABSTRACT FROM AUTHOR]

The uncertain geographic context problem (UGCoP), first articulated by Kwan (2012; The uncertain geographic context problem. Annals of the Association of American Geographers, 102 (5), 958–968), refers to the problem that findings about the effects of area-based contextual variables on individual behaviors or outcomes may be affected by how contextual units (e.g., neighborhoods) are geographically delineated and the extent to which these areal units deviate from the true geographic context. It is a significant methodological problem because it means that analytical results can differ for different delineations of contextual units even if everything else is the same. Drawing upon Kwan (2012) and recent social science studies (especially environmental health and neighborhood effects research), this article further elaborates on the nature of the UGCoP and explores how recent advances in geographical information system (GIS) and geospatial technologies can help address the problem. It discusses possible means for mitigating the UGCoP, especially with regard to the collection of detailed individual space–time data with global positioning systems, construction of individual activity spaces, and the use of qualitative and web-based GIS to capture people's activity locations and everyday experiences. It also discusses the challenges for future research that seeks to address the UGCoP. [ABSTRACT FROM AUTHOR]

Any study that examines the effects of area-based attributes on individual behaviors or outcomes faces another fundamental methodological problem besides the modifiable areal unit problem (MAUP). It is the problem that results about these effects can be affected by how contextual units or neighborhoods are geographically delineated and the extent to which these areal units deviate from the true geographic context. The problem arises because of the spatial uncertainty in the actual areas that exert the contextual influences under study and the temporal uncertainty in the timing and duration in which individuals experienced these contextual influences. Using neighborhood effects and environmental health research as a point of departure, this article clarifies the nature and sources of this problem, which is referred to as the uncertain geographic context problem (UGCoP). It highlights some of the inferential errors that the UGCoP might cause and discusses some means for mitigating the problem. It reviews recent studies to show that both contextual variables and research findings are sensitive to different delineations of contextual units. The article argues that the UGCoP is a problem as fundamental as the MAUP but is a different kind of problem. Future research needs to pay explicit attention to its potential confounding effects on research results and to methods for mitigating the problem. [ABSTRACT FROM AUTHOR]