Concordance of the Index of Relative Rurality with Contemporary USDA and Census Measures

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Abstract

Defining rurality is a persistent challenge in rural geography and spatial demography, where threshold-based classifications often obscure the heterogeneity of the rural-urban spectrum. The Index of Relative Rurality (IRR), a continuous and multi-dimensional measure, offers a theoretically-informed alternative. This study explores the areas of agreement and divergence between the 2020 IRR and the 2023 Rural-Urban Continuum Codes (RUCC) and investigates the methodological sources of these differences.Ordered logistic regression models confirm a significant, moderate association, with the IRR explaining approximately 21% of the variance in RUCC classifications. A subsequent analysis of the model's residuals reveals that this divergence is systematic: a county's spatial remoteness is a powerful and statistically significant predictor of the disagreement between the two measures. A structural examination further confirms the high inter-correlation between the proxy variables for the IRR's four components. The findings demonstrate that the IRR's primary value lies not in replicating official classifications, but in providing a distinct, spatially-informed perspective on rurality, making it a valuable complementary tool for nuanced research.

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