A New Approach for Rural Classification:An Empirical Study of Ziyuan County Using the Hourglass Model System

ZHOU You; HU Yangrong; LEI Zheng; ZHENG Yun

doi:10.3969/j.issn.1000-0232.2025.01.011

Abstract：With the comprehensive implementation of the rural revitalization strategy,village management is becoming increasingly stringent and refined.To support the unique development path of villages,it is essential to classify and promote rural development rationally based on the development status,location,and resource endowment of each village.An innovative village classification method was proposed in this study,the hourglass model system.The reliability and applicability of the hourglass model system were verified through an empirical study in Ziyuan County.This study aims to address the limitations of existing quantitative and qualitative rural classification methods,putting forward a classification method that can reflect the core features of different types of villages.Methodologically,the hourglass model system integrates both qualitative and quantitative approaches and classifies villages through hierarchical screening.This method has multiple advantages,including objectivity,flexibility,universality,and technical feedback.Based on the theoretical basis of qualitative and quantitative studies,two research hypotheses were proposed:Firstly,village features can be decomposed into multi-directional factor evaluations,and secondly,differences are a key point of distinction for village classification and screening.On this basis,two classification models,a qualitative"hourglass model"and a quantitative"hourglass mode",were built.Test results from a field test and sampling comparison were returned to the model system to enable dynamic adjustments to the hierarchy and order of the hourglass.In the empirical study,Ziyuan County,which is located at the border between Guangxi and Hunan,was chosen as the study area.It is a county with multiple ethnic populations.Villages in Ziyuan County were classified using the qualitative and quantitative hourglass models.The qualitative hourglass model mainly screens according to ecological environmental protection,historical cultural relics protection,and urban-village integrative development imperatives.It finally classifies villages according to natural landscape villages,historical and cultural heritage protection villages,and relocation & merger villages.The quantitative hourglass model evaluates the development potential of villages according to resource reserves,location conditions,population vitality,economic development,and supporting facilities.It finally classifies villages as suburban villages,agglomeration development villages,sustainable enhancement villages,and governance improvement villages.The results demonstrate that the hourglass models show high accuracy in the empirical study of Ziyuan County.The models provide planning guidance and governance strategies for the development of different types of villages.Verified by expert evaluations and field surveys,the classification results of hourglass models are consistent with practical simulations,showing high accuracy.The hourglass model system is an innovative village classification method and can offset the limitations of existing classification methods effectively.It has strong self-adaptation and universal application potential.The hourglass model is not only applicable to village classification but can also be expanded to multiple research fields,including urban classification,public service facility classification,and behavioral classification of participants.With respect to limitations,hourglass models face some challenges and uncertainties in data acquisition,testing,and feedback.These shall be discussed in more detail in future studies,promoting the continuous improvement of technical classification methods.To sum up,the proposed hourglass model system provides a new perspective and method for village classification.It has theoretical and practical significance to guide the implementation of rural vitalization strategies.