Abstract
Innovation in demography has been driven by new data, tools, and methods and less by theoretical advances. The thesis of this chapter is that new scholarship in demography requires a synthesis of existing theories and conceptualizations of place. More rigorous conceptual models will help enhance our understanding of the processes by which place ‘gets into people.’ Here we focus on measuring place in contextual analysis; this is, ironically, one of the weakest theoretical areas of current practice in demography and other disciplines new to spatial analysis. For the most part, studies of the relationship between demographic and health outcomes and place have been based on several conventional, and we argue naïve, assumptions about place. Specifically, places are often administratively bounded, static, and exist as isolated islands removed from meaningful nested and non-nested contexts. With revised conceptual models we will be better able to take advantage of the new spatial data on people and places and the emerging GIS-related technologies of the twenty-first century.
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Notes
- 1.
The discipline of geography has a long established literature on fundamental spatial concepts, the spatial patterns or spatial dimensions of daily life including constraints on human behavior/activities and in humanistic geography, specifically phenomenological approaches, to the study of meanings associated with, and attachment to, place (for a sample see: Abler et al. 1971; Carlstein et al. 1978; de Smith et al. 2013; Golledge and Stimson 1997; Hägerstrand 1967, 1970; Haggett 1965; Janelle and Goodchild 2011; Tuan 1977). See also Gregory et al. (2009).
- 2.
It is noteworthy that the use of different contextual units can produce different results in analyses (Flowerdew et al. 2008; Mobley et al. 2008; Riva et al. 2008; Roux et al. 2001; Spielman and Yoo 2009; Speilman et al. 2013). Detail discussions on the modifiable areal unit problem (Openshaw 1984) have been given elsewhere (e.g., Fotheringham and Wong 1991; Moon et al. 2005; Root 2012). Readers should be aware that using smaller geographic units may provide better context-measures (Clapp and Wang 2006; Coulton et al. 2011; Hipp 2007), but the call for smaller and smaller nesting units can lead to a non-beneficial degree of reduction (see later example based on Duncan et al. 1961).
- 3.
As noted in Matthews (Chap. 17, this volume), the instructional opportunities in the area of spatial demography do not necessarily facilitate or promote exposure to the geographical literature.
- 4.
Academic amnesia refers to the lack of acknowledgment and/or awareness of the work of previous generations of scholars, see Gans 1992.
- 5.
Individual lives include long commutes, multiple jobs, night shifts, juggling family, daycare, education, social networks and work, finding, preparing, and eating food, practicing one’s faith, engaging in leisure activities and exercise, and coping with illness and disease.
- 6.
Similarly, the bounded and discrete view of the world reinforces the focus in our analysis on the residential place and also the use of measures of accessibility (potential accessibility) over utilization (revealed accessibility); see Joseph and Phillips 1984.
- 7.
It is worth noting that several of the leading multilevel or hierarchical statistical software packages have their origins in educational and organizational research where many strict nested hierarchies exist: HLM was developed by Bryk & Raudenbush at the University of Chicago while MLN/MLwiN was developed by Goldstein at the Institute of Education, London.
- 8.
It is beyond the scope of this chapter to discuss how macro-level measures or statistical analysis affect debates over causal mechanisms in multilevel research. Discussion on the relevance of multilevel modeling for identifying casual context effects is given elsewhere (Subramanian 2004). The logic & philosophy of causal inference from statistical analysis is also available elsewhere (Greenland 2011). More detail discussion on the challenges of inferring causality in micro-outcomes (like demography & health) with hierarchical modeling are available (Oakes 2004; Roux 2004) as are calls for improving measurements of group-level constructs when exploring causal mechanisms (Roux 2008).
- 9.
Over a century ago, Ravenstein (1876) noted the link between birthplace and migratory behavior. In the early part of the twentieth century Park (1926, p. 18) wrote that the use of statistical methodologies in social science were important only “because social relations are so frequently & so inevitably correlated with spatial relations.”
- 10.
It is beyond the scope of this paper but we note that there is a growing realization that there is need for both the development of new and the validation of existing relevant place-level measures (e.g., built environment measures). Similarly, there is a need for research on identifying sources of spatial uncertainty (i.e., inaccuracy or instability) in both existing & new kinds of data demographers will utilize.
- 11.
Clapp and Wang (2006, p. 260) suggest that a lack in definitional precision but wide use of the term “neighborhood” may occur because “the ordinary language definition is considered so compelling as to require little elaboration.” While using the label neighborhood may provide a perception of conceptual power, arguably modest scientific insight is afforded by the ambiguous use of the term.
- 12.
Our ability today to collect data at increasingly finer temporal scales, and aggregate up as needed, provides analytical flexibility never before seen.
- 13.
In some states school districts may align with counties but in others they do not. That is, some pairs of levels within the census hierarchy do not have a consistent relationship across the whole country.
- 14.
There is not space in this chapter to discuss boundary changes over time or that in some states but this is another important wrinkle.
- 15.
We are using this diagram from Glass and McAtee out of context. Our interest is only on discussing the main dimensions of interest.
- 16.
- 17.
Parenthetically the absence of these local resources in the residential tract or context does not necessarily make these areas a childcare desert, a school desert, a medical desert, or a park desert.
- 18.
Demographers who have been used to relying on the Summary Tape Files or Summary Files (the census long-form) data to define neighborhood attributes now have to use the American Community Survey 5-year estimates. As the margin of error can be high for both the population & the housing variables from the ACS it might be prudent to start thinking about using larger contextual units and tapping in to alternative sources of data on the social, built, and physical environment.
The American Community Survey (ACS) implies a focus on “community;” a phrase that along with “neighborhood” has been employed loosely across the social & health sciences.
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Siordia, C., Matthews, S.A. (2016). Extending the Boundaries of Place. In: Howell, F., Porter, J., Matthews, S. (eds) Recapturing Space: New Middle-Range Theory in Spatial Demography. Spatial Demography Book Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-22810-5_3
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