(untitled) (Journal of Geography and Environmental Management, 2025)
In the context of increasing demographic instability and regional population polarization, there is a growing need to identify and measure spatially localized labor market risks. This study focuses on assessing the demographic vulnerability of the labor market at the district level in the North Kazakhstan Region using an index-based approach. The objective of the research is to develop an integral demographic risk index incorporating components that reflect resource potential, population ageing, and employment parameters, as well as to analyze the spatial distribution and dynamics of risk at the subregional level. The scientific novelty of the study lies in the formalization of demographic vulnerability through a three-component index model and the classification of districts according to risk profiles. The practical significance is determined by the potential application of the developed index in human capital monitoring systems, strategic planning, and evaluating progress towards the Sustainable Development Goals (SDGs). The methodological framework includes linear normalization, indicator aggregation, cartographic visualization, and dynamic data comparison for the period 2010–2023. The research findings indicate that demographic vulnerability in the region is persistent and cumulative, forming a high-risk belt along the region’s periphery. Stable and critically vulnerable districts are identified, along with causal relationships between index components and types of vulnerability. The study substantiates the need for a territorially differentiated demographic policy and the implementation of spatial monitoring systems. This research contributes to the advancement of applied demography and spatial labor potential analysis by demonstrating the feasibility of adapting index-based models at the subregional level. The results can be utilized for the development of regional strategies, resource allocation, and programs aimed at retaining and reproducing the labor force.