Remote Human Settlements in Developed Nations
New Horizons in Regional Science series
Edited by Andrew Taylor, Dean B. Carson, Prescott C. Ensign, Lee Huskey, Rasmus O. Rasmussen and Gertrude Saxinger
Chapter 7: Sources of data for settlement level analyses in sparsely populated areas
Paul Peters, Andrew Taylor, Dean B. Carson and Huw Brokensha INTRODUCTION Research in areas such as demography, social sciences and population health normally utilise secondary population data sources to address key questions. Large and nationally representative datasets are usually the sources for such analyses. These datasets have allowed for broader generalisations to be drawn and in- epth analysis of changes at settlements level, d as well as for population sub- roups. Such datasets, which include national g censuses and survey programmes, are administered by national statistical agencies (NSAs) covering topics like demographic characteristics, employment and health. While large and nationally representative datasets are considered the ‘gold standard’ for research, it is recognised they have limitations for understanding demographic change at small scales of g eography and for population sub- roups, in particular for those residing g in sparsely populated areas (SPAs) and Indigenous peoples (Axelsson, 2010; Taylor et al., 2011). Despite the intense application of census data for research aimed at plotting and understanding demographic change for settlements in SPAs, in recent years cutbacks to the budgets of NSAs have placed the frequencies of censuses, their content and their comprehensiveness under threat in many nations. Changed methods and output characteristics have also affected the utility of this important data source for research purposes in some cases (Coleman, 2013; Kukutai et al., 2014). The implications of these changes are disproportionately large for analysis relating to SPA populations, making the need for alternative data sources and methods more apparent. In this chapter...
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