县市分等方法及中国县市等第特征的分异规律
李一飞(1985- ),男,河南镇平人,博士研究生,主要从事城市地理和行政区划方面研究。E-mail: li.yifei@foxmail.com |
收稿日期: 2019-05-13
要求修回日期: 2019-06-16
网络出版日期: 2020-06-24
基金资助
国家自然科学基金项目(41471126)
国家自然科学基金项目(41501187)
国家自然科学基金项目(51778002)
国家自然科学基金项目(41571164)
版权
Classification method for counties and cities' gradation and differentiation rule in China
Received date: 2019-05-13
Request revised date: 2019-06-16
Online published: 2020-06-24
Copyright
对行政区进行适当分类管理是提高行政管理效率的重要手段。县市分等是行政区分类管理的重要内容,也是“因地制宜”推进行政区划管理的直接体现,对于提升地方治理能力和治理水平、激发发展活力和释放发展动能具有重要意义。系统梳理中国县市统计数据,综合运用层次分析法、K均值聚类法等提出县市分等方法,并对县市等第特征的分异规律进行分析。结果显示:① 人口规模是影响县市分等的主要因素,其次是面积和地区生产总值,公共财政支出的影响相对较小。各等第县市数量大体呈梯形分布,高等第县市间差异较大,不同等第县市地域分布存在不均衡现象。② 县市分等管理在实践中具有可行性,按照人口、地理、经济、管理难度分等的方法具有合理性。③ 县市分等过程中,可以考虑采取分省份、按比例的方法对县市等第进行划分,对县市差异小、分等使用的单方面指标值较高县市相对集中,以及县市数量少的省份可以给予特殊安排。④ 在推进国家治理现代化背景下,县市分等的现实需求更加凸显,有助于新时期对不同县市分类施策,促进县市间良性竞争与协同发展。
李一飞 , 王开泳 , 王甫园 . 县市分等方法及中国县市等第特征的分异规律[J]. 地理研究, 2020 , 39(4) : 772 -786 . DOI: 10.11821/dlyj020190369
To classify administrative regions and implement different management policies accordingly is a common practice adopted in many countries. It is essential for big countries like China to divide different types of administrative regions in line with local conditions to achieve effective national governance. As an important demonstration of administrative divisions, the gradation of administrative regions, especially at the county and municipal levels, has long been an important means in the field of administrative management in China's history. This paper, based on the statistical data of counties and cities in China, used mathematical methods such as AHP and K-means cluster to propose the gradation of counties and cities. And a quantitative assessment of the feasibility and effectiveness of the gradation was conducted. Finally, based on the classification of administrative regions and the gradation of counties and cities, and the legal regulations of administrative divisions, the paper discussed the issue of the procedure and dynamic management of counties and cities' gradation. Results show that, the number of high-gradation counties and cities is relatively large, and the number of low-gradation counties and cities is relatively small. The internal differences of high-gradation counties and cities are larger than those of low-gradation ones. The geographical distribution of different gradations of counties and cities is uneven. It is feasible to classify counties and cities in practice. Thus, it is reasonable to classify counties and cities based on indicators such as population, geography, economy, and management difficulty. One possible method is to classify counties and cities at the provincial level and use proportion instead of absolute value. The goal of counties and cities' classification is to give different jurisdictions to different counties and cities. For the provinces with small difference and small number of counties and cities, they need special arrangements. The significance of the counties and cities' classification is to rationalize the management system of counties and cities and improve the management efficiency. Counties and cities' classification could unleash the vitality of local development and promote healthy competition. And counties and cities' classifications are of great significance for promoting the modernization of the national governance system and governance capacity.
表1 县市分等综合评价指标体系Tab. 1 Evaluation factors system of gradation of counties and cities |
因素 | 指标 | 权重 | 代码 |
---|---|---|---|
人口 | 总人口(万人) | 0.472 | W1 |
地理 | 行政区域面积(km2) | 0.2242 | W2 |
经济 | 地区生产总值(万元) | 0.2063 | W3 |
管理难度 | 公共财政支出(万元) | 0.0976 | W4 |
表2 全国尺度县市分等参考结果Tab. 2 Comparison of grading result of counties and cities at the national level |
县市等第 | 县市个数 | 县市个数占比(%) | 综合评价值区间 | 综合评价值区间差 |
---|---|---|---|---|
一等县市 | 58 | 3.06 | 0.1920~0.4858 | 0.2938 |
二等县市 | 513 | 27.09 | 0.0876~0.1916 | 0.1040 |
三等县市 | 1323 | 69.85 | 0.0058~0.0873 | 0.0815 |
表3 全国尺度县市分等参考结果分省分布情况Tab. 3 Comparison of grading result of counties and cities by provincial-level region at the national level |
省份 | 一等县市数量 | 二等县市数量 | 三等县市数量 | 省份 | 一等县市数量 | 二等县市数量 | 三等县市数量 |
---|---|---|---|---|---|---|---|
河北 | 0 | 22 | 99 | 湖南 | 3 | 42 | 42 |
山西 | 0 | 1 | 91 | 广东 | 4 | 23 | 30 |
内蒙古 | 2 | 18 | 60 | 广西 | 1 | 15 | 58 |
辽宁 | 1 | 10 | 30 | 海南 | 0 | 3 | 12 |
吉林 | 0 | 13 | 26 | 重庆 | 0 | 6 | 6 |
黑龙江 | 0 | 11 | 52 | 四川 | 0 | 36 | 94 |
江苏 | 15 | 24 | 2 | 贵州 | 0 | 12 | 60 |
浙江 | 7 | 21 | 25 | 云南 | 0 | 11 | 103 |
安徽 | 1 | 28 | 32 | 西藏 | 3 | 4 | 63 |
江西 | 2 | 17 | 58 | 陕西 | 0 | 4 | 75 |
福建 | 3 | 13 | 40 | 甘肃 | 0 | 2 | 67 |
山东 | 9 | 55 | 19 | 青海 | 2 | 3 | 32 |
河南 | 3 | 60 | 42 | 宁夏 | 0 | 0 | 13 |
湖北 | 0 | 34 | 29 | 新疆 | 2 | 25 | 63 |
表4 省域尺度县市分等参考结果Tab. 4 Comparison of grading result of counties and cities at the provincial level |
省份 | 一等县市个数(评价值区间) | 二等县市个数(评价值区间) | 三等县市个数(评价值区间) |
---|---|---|---|
河北 | 14(0.3656~0.6167) | 51(0.1924~0.3496) | 56(0.0285~0.1854) |
山西 | 9(0.5110~0.7543) | 36(0.2916~0.4687) | 47(0.0601~0.2830) |
内蒙古 | 5(0.4458~0.5616) | 34(0.2292~0.4118) | 41(0.0313~0.2136) |
辽宁 | 3(0.7050~0.8597) | 29(0.2522~0.5525) | 9(0.0200~0.2378) |
吉林 | 3(0.7544~0.8166) | 13(0.3412~0.6079) | 23(0.0166~0.3053) |
黑龙江 | 2(0.7947~0.8591) | 28(0.3285~0.5927) | 33(0.0508~0.3148) |
江苏 | 8(0.5471~0.8235) | 15(0.3334~0.5136) | 18(0.0224~0.3121) |
浙江 | 7(0.5946~0.8410) | 14(0.3345~0.5611) | 32(0.0106~0.3136) |
安徽 | 20(0.4659~0.6986) | 29(0.2387~0.4434) | 12(0.0205~0.2203) |
福建 | 1(0.8020) | 9(0.3354~0.5746) | 46(0.0208~0.2759) |
江西 | 3(0.7122~0.8068) | 22(0.3206~0.5666) | 52(0.0334~0.3031) |
山东 | 16(0.5198~0.8241) | 35(0.3318~0.5089) | 32(0.0000~0.3201) |
河南 | 8(0.5305~0.7395) | 52(0.3048~0.5083) | 45(0.0118~0.2999) |
湖北 | 7(0.6030~0.7996) | 21(0.3410~0.5741) | 35(0.0741~0.3285) |
湖南 | 5(0.6187~0.9340) | 44(0.2991~0.5700) | 38(0.0090~0.2833) |
广东 | 8(0.5657~0.8371) | 20(0.3043~0.5219) | 29(0.0000~0.2812) |
广西 | 6(0.6225~0.9369) | 14(0.3563~0.5968) | 54(0.0063~0.3287) |
海南 | 7(0.5396~0.8531) | 6(0.2236~0.4229) | 2(0.0001~0.0672) |
重庆 | 5(0.5527~0.8364) | 6(0.3174~0.4645) | 1(0.1250) |
四川 | 21(0.4629~0.7558) | 41(0.3554~0.4551) | 68(0.0246~0.2232) |
贵州 | 2(0.8046~0.8297) | 18(0.2687~0.5747) | 52(0.0223~0.2536) |
云南 | 9(0.4587~0.8146) | 42(0.2269~0.4221) | 63(0.0454~0.2256) |
西藏 | 13(0.3795~0.6021) | 31(0.1868~0.3523) | 26(0.0159~0.1493) |
陕西 | 1(0.8113) | 32(0.2851~0.5846) | 46(0.0274~0.2747) |
甘肃 | 7(0.5609~0.6648) | 22(0.3529~0.5262) | 40(0.0406~0.3357) |
青海 | 5(0.5439~0.6674) | 10(0.1547~0.3759) | 22(0.0292~0.1344) |
宁夏 | 5(0.5700~0.7305) | 6(0.2629~0.4452) | 2(0.0078~0.1106) |
新疆 | 9(0.4053~0.6212) | 39(0.1728~0.3269) | 42(0.0257~0.1673) |
评审专家对本研究提出客观、准确、详实的审稿意见,特致以诚挚感谢。
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