Sensing spatial inequality of socio-economic factors for deploying permanent deacons in the UK

感知社会经济因素的空间不平等,以便在英国部署常驻执事

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Abstract

Integrating spatial inequality perspectives in strategic decision-making can ensure positive impacts on resource distribution for public welfare and sustainable development. This study aims to apply evidence-based approaches in deploying permanent deacons. The empirical case study has been conducted at the St Helens denary of the Liverpool archdiocese, UK. Assisting with charitable works is one of three served areas by the Roman Catholic Church facilitated by deacons. The deployment of permanent deacons could benefit from being evidence-based so that a deacon can serve to ease the socio-economic (e.g., population density, long-term health conditions, housing system, employment status, education level, social status) inequality in the most deprived area. We used geographic information system (GIS) based algorithms, Getis-Ord Gi* for hot spot analysis to find the clustered area by considering the socio-economic factors. The open/freely available government census dataset was found to help extract socio-economic parameters. Furthermore, a GIS-based multi-criteria assessment technique was conducted by applying map algebra (raster calculator) to identify the deprived area with ranks considering multiple socio-economic conditions, where served areas by the existing deacons were considered to constrain. The served areas were estimated by applying network analysis where OpenStreetMap and location existing deacons were used as input. Our empirical case study identified the central and northern parts of the deanery as the most and least deprived areas, respectively. Finally, Liverpool archdiocese could consider deploying new permanent deacons in St Helens denary based on suggested deprivation ranks. Therefore, the appropriate number of deacons in the deprived areas can quickly and effectively respond to the needy and enhance communities' resilience and sustainable development by ensuring proportionate resource distribution.

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