Who are the People in my Neighborhood?: The “Contextual Fallacy” of Measuring Individual Context with Census Geographies

Abstract

Scholars frequently use counts of populations aggregated into geographic units like census tracts to represent measures of neighborhood context. Decades of research confirm that variation in how individuals are aggregated into geographic units can dramatically alteranalyses conducted with these units. While most researchers are aware of the problem, they have lacked the tools to determine its magnitude or its capacity to affect analytical results obtained using these contextual measures. Using confidential access to the complete 2010 U.S. Decennial Census, we can construct-for all persons in the U.S.-individualspecific contexts, which we group according to Census-assigned block, block group, and tract. We compare these individual-specific measures to the published statistics at each scale, and we then determine the degree to which published measures could be affected by how boundaries are drawn using a simple statistic, the standard deviation of individual context (SDIC). For three key measures (percent Black, percent Hispanic, and Entropy-a measure of ethno-racial diversity), we find that block-level Census statistics frequently contain a high degree of uncertainty meaning that they may not capture the actual context of individuals within them. More problematic, we uncover systematic spatial patterns in the uncertainty associated with contextual variables at all three scales.

Spatial equity implications and neighborhood indicators of ridehailing trip frequency and vehicle miles traveled in the phoenix metro region

“…Finally, this study of neighborhood-level socioeconomic context factors somewhat assumes significant predictors of ridehailing activity are reflective of individuals who adopt these services. This contextual fallacy (Fowler et al 2020) can only be resolved by analyzing person-level data that have usually been collected by intercept surveys which have other biases and often produce smaller sample sizes to investigate. While these limitations warrant future consideration, this study has identified how ridehailing services prior to the Covid-19 pandemic impacted urban neighborhoods in divergent and disproportionate ways.…”

Quantitative geography III: Future challenges and challenging futures

“…Petrović et al (2018b) find different probabilities of interaction in the Netherlands comparing individual responses to official aggregates. Fowler et al (2020) also show the representativeness of 2010 US census data aggregates varies geographically. This does not invalidate "intentional" census data, but shows areal census data requires critical empiricism, too.…”

Quantitative Geography III: Future Challenges & Challenging Futures

“…find different probabilities of interaction in the Netherlands comparing individual responses to official aggregates. Fowler et al (2020) also shows the representativeness of 2010 US census data aggregates varies geographically. This does not invalidate aggregate data, but shows areal census data requires critical empiricism, too.…”