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Study On The Distribution Characteristics And Influencing Factors Of National Youth Campus Football Characteristic Schools

Posted on:2024-07-15Degree:MasterType:Thesis
Country:ChinaCandidate:Z G MaFull Text:PDF
GTID:2557307124953339Subject:Physical Education and Training
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"Youth is strong,then the country is strong","Sports is strong,then the country is strong",selecting and building national youth campus football characteristic schools is an effective way to enhance the physical quality of young people,is the basic guarantee of national football talent cultivation,is an important strategy to achieve a healthy China,is the inevitable demand for China’s development today,is a powerful grasp of China from a "sports power" to a "sports power".The selection and construction of youth campus football featured schools not only improves students’ sports skills,promotes their physical and mental health,enhances their physical fitness,and sharpens their indomitable will to fight,but also promotes the development of campus football,and is more conducive to cultivat ing football talents with comprehensive development in morality,intelligence,physique,beauty,and labor for the country,realizing the dream of a healthy China and a strong football country.Based on the background that the development of campus football in China presents polarization and the construction of campus football characteristic schools is uneven,this article mainly uses relevant theoretical foundations such as demography,economics,sports science,and geography,and uses software such as GIS 10.4,GeoDa,and SPSS to conduct analysis methods such as Lorentz curve,Gini coefficient,geographical concentration index,spatial autocorrelation,hot spot analysis,imbalance index,abundance index,and multiple linear regression The paper systematically expounds the spatial distribution characteristics,influencing factors,and formation mechanism of the national youth campus football characteristic schools through the methods of literature review and mathematical statistics.This basis can promote the overall balanced distribution and development of youth campus football featured schools,and has theoretical guiding significance for the formulation and implementation of policies for the selection and construction of youth campus football featured schools in the later stage of the country.The research conclusions are as follows:1.With the later review and the continuous strengthening of the regulatory mechanism,the overall trend of youth campus football featured schools in 2015-2021 has been downward,especially in 2021,where the number of featured schools barely exceeds 2000.2.Analyze the distribution characteristics of football featured schools on Chinese youth campuses from different geographical regions,economic zones,and provincial administrative regions.Using the GIS map,it can be clearly seen that the visual map of the seven major geographical regions shows that the distribution number of football featured schools on youth campuses is in the order of East China,Central China,Southwest,North China,Northwest,South China,and Northeast from high to low;The distribution number of youth football characteristic schools in the three major economic zones:eastern zone>central zone>western zone;It can be clearly seen from the visual image of the provincial administrative region that the distribution characteristics of football featured schools on Chinese youth campuses are highly consistent with the geographical distribution characteristics of the population,forming a significant uneven distribution trend of polarization in the southeast coastal cities,central and western regions.Among them,provinces with a population of over 50 million have also ranked among the topin the construction of youth campus football characteristic schools,forming a high value gathering area;In provinces and cities with a population of less than 10 million,the number of youth campus football characteristic schools is rare,especially in Qinghai and Tibet,where the number of youth campus football characteristic schools is very small,forming a low value gathering area.3.It can be known through analysis using the cold hot spots and spatial autocorrelation tools in GeoDa software.The hot spots are mainly concentrated in the southeast of China,Beijing and Tianjin in North China,the southeast coastalareas,the middle and lower reaches of the Yellow River,and the Yangtze River Middle and lower reaches;Other hot spots are mainly distributed in the economically backward and geographically rugged northwest,southwest,and northeast regions;The cold spot region is located in the Tibet Autonomous Region,known as the "Roof of the World" in China.The Morans’I index chart of various provinces shows that the distribution of characteristic schools for campus football in China presents a certain degree of aggregation,with high-highland areas and low-hig hland areas only appearing in East China,North China,and Central China.The rest of the regions are not significant areas,but present a certain degree of aggregation,indicating that the selection of characteristic schools for campus football presents a certain degree of aggregation,but the aggregation effect is not significant,and the spatial distribution state is closer to random distribution.The spatial dispersion effect of northwest,southwest,south China,and northeast regions is stronger than that of central and eastern regions,as shown by the specific province aggregation pattern map and the Morans’I index.4.By analyzing the fairness and balance of the distribution characteristics of youth football featured schools in China,it can be seen.There is a significant difference in the density index of characteristic schools for youth campus football.The density index in East China,Central China,and South China is generally higher than that in Northwest,Southwest,North China,and Northeast China.The three provinces with the highest density index are Tianjin,Beijing,and Shanghai,while Ningxia and Chongqing have the highest density index in their respective regions;From the demand of various regions,it can be seen that the northwest(except Ningxia),northeast,southwest,and north China(except Beijing and Tianjin)have the largest demand,followed by central and south China;East China has the lowest demand.From the analysis of the quantity and proportion of deficiency,it can be seen that the northwest and southwest regions have the largest gaps,Inner Mongolia and Shanxi have the largest gaps in North China,and the southeast coastal regions have the smallest gaps.From the analysis of equilibrium evaluation indicators,it can be seen that the Gvalue of China’s campus footb all characteristic schools from 2015-2021 is below the warning line of 0.4.According to the analysis of imbalance index and geographical concentration index,it can be seen that the overall concentration trend of campus football characteristic schools is uneven,with the most significant concentration trend in 2018 and 2021.According to the abundance index,the poverty level of campus football characteristic schools in Qinghai and Tibet is the most serious.5.Analyze the current situation and formation factors of the spatial distribution of youth football featured schools in China.It is believed that geographical environment factors,economic factors,policy guidance factors,and manpower reserves are the main factors restricting the construction of characteristic schools.Through multiple linear regression analysis,it can be seen that education expenditure,per capita GDP,and population density play a certain guiding and supporting role in the construction of campus football featured schools,and the influencing factors are the mutual flow and proximity of high-density areas and neighboring low-density areas.6.The spatial distribution of football featured schools on campus follows the"gradient" transition theory and "unbalanced development" theory widely cited in economic,social,demographic,and geographical fields.
Keywords/Search Tags:National Youth Campus Football Characteristic School, Distribution characteristics, Dynamic factors, Formation mechanism, GIS spatial analysis, Geostatistical analysis
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