Spatial Inequality in Potential Employment Supply and Actual Employment Access Under Differentiated Housing Costs: A Case Study of Urumqi

The spatial imbalance in the distribution of employment opportunities and other key urban resources is profoundly impacting social equity and sustainable urban development. Taking Urumqi as a case study, this research integrates multi-source big data—including mobile phone signaling, residential information, points of interest (POIs), online job postings, and enterprise records—and applies an interpretable machine learning approach (CatBoost combined with SHAP) to systematically evaluate inequalities in both potential employment supply and actual job access across neighborhoods with varying housing rents. In the absence of individual income data, housing rent is used as a proxy for residents’ economic capacity, and low-rent neighborhoods are treated as spatial representations of low-income communities. The results reveal that residents in low-rent areas face consistent disadvantages in terms of job quantity, wage levels, and commuting accessibility, and also encounter structural constraints in realizing actual employment outcomes. Furthermore, two critical thresholds are identified: approximately 20 CNY/m²/month and 23 CNY/m²/month, which correspond to notable turning points for potential employment supply and actual job attainment, respectively. These findings reflect a nonlinear “resource concentration–diminishing return” mechanism between housing cost and employment access. From the perspective of the interaction between spatial structure and individual capability, this study reveals the deeper causes of job–housing mismatch and opportunity inequality. It calls for integrated policy interventions—such as the provision of affordable housing, improvements in transit accessibility, and localized employment support—to systematically mitigate the multidimensional disadvantages faced by low-income communities, and offers empirical evidence and policy insights for fostering a more equitable and inclusive urban spatial structure.