The use of population-level data to advance interdisciplinary methodology: A cell-through-society sampling framework for child development research

The authors argue that population-level data should be used to advance interdisciplinary research about community effects on early development. These data permit the identification of neighborhoods in which development patterns deviate from predictions based on local socioeconomic status (SES). So-called ‘off-diagonal’ places signal where researchers are likely to discover processes that either deflect the risks of low SES or dampen the salutary impact of favorable SES. Since such neighborhoods will be best understood relative to nearby ‘ondiagonal’ neighborhoods where macro-economic and/or public policy factors are constant, the authors present a methodology for illuminating these regional clusters. The method is deployed in British Columbia, Canada, where a team has collected developmental observations from two censuses of kindergarten children (n = 82,632). The article discusses how these clusters can be used to coordinate sampling decisions among academics representing the range of disciplines needed to study child development from cell-through-society, as is recommended in the literature.