이 논문은 2022년 6월 1일 윤석열정부에서 치러진 민선8기 지방선거 결과 광주·전남지역에 관한 것이다. 그동안 호남지역은 더불어민주당의 텃밭으로 민주당의 핵심축으로 역할을 해 왔다. 그러나 더불어민주당은 2022년 3월 대선에서 패배하였으며, 6월 지방선거에서도 참패를 당했다. 이러한 참패는 더불어민주당의 독주체제와 오만, 국민들의 민심 이반에 그 원인을 찾을 수 있다. 2022년 6월 지방선거에서 광주투표율은 37.7% 로 전국 최하위로써 역대 최저치를 나타냈는데 이는 대선패배와 더불어 민주당에 대한 실망감으로 보인다. 반면 전남은 투표율 58.5%로 전국 최고치를 나타냈는데 이는 더불어민주당의 공천 불공정에 대한 반발로 무소속 후보에 대한 적극적인 투표효과로 보인다. 민선8기 광주·전남 국 민의힘 시·도지사 후보 득표율은 15% 이상으로 선거비용 보전이 가능하 게 되었다. 이러한 득표결과는 국민의힘의 지속적인 호남지역에 대한 서 진정책(西進政策)효과라고 분석된다.

The purpose of this study was to analyze the general characteristics of coffee house consumers as well as the importance and satisfaction of selection attributes of specialty coffee houses according to length of coffee education period. Applicants in the Gwangju and Jeonnam area who had finished their Barista 2 grade certificate examination participated in a survey on March 12, 2011. Further, university students living in Gwangju participated as subjects who had never experienced coffee education from March 15 to March 31, 2011. Two-hundred and one subjects participated in the survey, and 184 questionnaires were used for analysis. Regardless of coffee education experience, quality of coffee was important, but higher educated subjects showed the lowest satisfaction of coffee from a coffee house (p<0.01) in terms of attributes such as freshness of coffee beans (p<0.01) and overall taste (p<0.01). Further, subjects who received no or little education demonstrated high correlation between importance/satisfaction of 'brand' and 'employee' compared to subjects who studied more than 2 semesters. These results provide future coffee house entrepreneurs and baristas with market information and marketing strategies for understanding customers' coffee house selection attributes.

This study was conducted to examine the relationship between dietary habits and time spent watching TV and using internet, in elementary school children. The data were collected by a questionnaire survey of 712 elementary school children, within Gwangju and Jeonnam area. The SPSS 12.0/win program was used to analyze the 523 samples. Amount of TV-watching time was found to be related to the dietary habit score in the subjects. The children who watch TV “less than 1 hour/day” on weekdays had a better dietary habit score than those who watch TV “more than 1 hour” (p<0.0001). The children who watch TV “less than 2 hours/day” on weekends had a better dietary habit than the children who watch TV “more than 2 hours/day” (p<0.0001). The internet usage was also related to the dietary habit score in these children: those who use internet “less than 1 hour/day” on weekdays had a better dietary habit score than the children who use internet “more than 2 hours/day” (p<0.0001). The children who use internet “less than 2 hours/day” on weekends had a better dietary habit score than the children who use internet “more than 2 hours/day” (p<0.0001). These results indicate that the children tend to have a better diet when their TV and internet time is limited and thus healthy dietary behavior is negatively associated with a sedentary pattern of activity in elementary school children.

When an age of low growth and population decline, population migration plays an important role in spatial structure of region. There have been many researches on migration and regional spatial structure. The purpose of this study is to examine the changes of Gwangju and Jeonnam region’s spatial structure and central area using social network analysis methods. For analysis it was used that population and migration data and passenger OD(Origin and Destination) travel data released by Statistics Korea and Korea Transport Database(KTDB). Using Gephi 0.8.2, migration and passenger OD networks were visualized, and this describe network flow and density. The results of the network centrality analysis show that the most populated village is not always network center though population mass is an important factor of central places. The average eigenvector centrality of 2010 migration is the lowest during 2005-2015, and it means few regions have high centralities. When comparing migration and travel networks, travel data is more effective than migration data in determining the central location considering spatial functions.