The Health Silk Road (HSR) of the Belt and Road Initiative (BRI) of China aims to enhance public health and foster international cooperation in the healthcare sector. HSR objectives include strengthening healthcare infrastructure, expanding China’s global health leadership, and enhancing international health cooperation. The aim of this study was to examine the HSR and its implications for global health and international relations by using expert opinion analysis on known major HSR initiatives. We analyzed the objectives of HSR, including improving healthcare infrastructure, enhancing global health cooperation, and expanding China’s global health leadership. Additionally, as a case study, an in-depth analysis of the China-Pakistan collaboration on healthcare under the China-Pakistan Economic Corridor (CPEC) was conducted. This research posits that the HSR has a mix of positive and negative implications. Positive impacts of HSR include improved healthcare services, infrastructure, and capacity-building in participating countries. The main challenges include the quality and sustainability of the infrastructure and services provided, debt sustainability, transparency of projects, and China’s geopolitical influence. This research identified five motives behind China’s HSR: economic interests, diplomatic influence, reputation building, regional stability, and health security. The summary centers on CPEC and the WHO/Global collaboration. This research contributes to a nuanced understanding of the HSR’s multifaceted impacts and underscores the importance of open dialogue, cooperation, and the sharing of best practices among stakeholders. By assessing the motives, implications, and concerns of the HSR, this study offers valuable insights for policymakers, global health practitioners, and scholars, highlighting the significance of international collaboration.
{"title":"The Health Silk Road: A Double-Edged Sword? Assessing the Implications of China’s Health Diplomacy","authors":"Shaoyu Yuan","doi":"10.3390/world4020021","DOIUrl":"https://doi.org/10.3390/world4020021","url":null,"abstract":"The Health Silk Road (HSR) of the Belt and Road Initiative (BRI) of China aims to enhance public health and foster international cooperation in the healthcare sector. HSR objectives include strengthening healthcare infrastructure, expanding China’s global health leadership, and enhancing international health cooperation. The aim of this study was to examine the HSR and its implications for global health and international relations by using expert opinion analysis on known major HSR initiatives. We analyzed the objectives of HSR, including improving healthcare infrastructure, enhancing global health cooperation, and expanding China’s global health leadership. Additionally, as a case study, an in-depth analysis of the China-Pakistan collaboration on healthcare under the China-Pakistan Economic Corridor (CPEC) was conducted. This research posits that the HSR has a mix of positive and negative implications. Positive impacts of HSR include improved healthcare services, infrastructure, and capacity-building in participating countries. The main challenges include the quality and sustainability of the infrastructure and services provided, debt sustainability, transparency of projects, and China’s geopolitical influence. This research identified five motives behind China’s HSR: economic interests, diplomatic influence, reputation building, regional stability, and health security. The summary centers on CPEC and the WHO/Global collaboration. This research contributes to a nuanced understanding of the HSR’s multifaceted impacts and underscores the importance of open dialogue, cooperation, and the sharing of best practices among stakeholders. By assessing the motives, implications, and concerns of the HSR, this study offers valuable insights for policymakers, global health practitioners, and scholars, highlighting the significance of international collaboration.","PeriodicalId":23705,"journal":{"name":"WORLD","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135821220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joyce de Souza Zanirato Maia, Ana Paula Arantes Bueno, Joao Ricardo Sato
Education plays a critical role in society as it promotes economic development through human capital, reduces crime, and improves general well-being. In any country, especially in the developing ones, its presence on the political agenda is necessary. Despite recent educational advances, those developing countries have increased enrollments, but academic performance has fallen far short of expectations. According to international evaluations, Latin American countries have made little progress in recent years, considering the level of investment in education. Thus, Artificial Intelligence (AI) models, which deal with data differently from traditional analysis methods, can be an option to better understand educational dynamics and detect patterns. Through a literature review using the PRISMA methodology, we investigated how AI has been used to evaluate educational performance in basic education (elementary and high school) in several countries. We searched five platforms, resulting in a total of 19,114 works retrieved, and 70 articles included in the review. Among the main findings of this study, we can mention: (i) low adherence to the use of AI methodology in education for practical actions; (ii) restriction of analyzes to specific datasets; (iii) most studies focus on computational methodology and not on the meaning of the results for education; and (iv) a less trend to use AI methods, especially in Latin America. The COVID-19 pandemic has exacerbated educational challenges, highlighting the need for innovative solutions. Given the gap in the use of AI in education, we propose its methods for global academic evaluation as a means of supporting public policy-making and resource allocation. We estimate that these methods may yield better results more quickly, enabling us to better address the urgent needs of students and educators worldwide.
{"title":"Applications of Artificial Intelligence Models in Educational Analytics and Decision Making: A Systematic Review","authors":"Joyce de Souza Zanirato Maia, Ana Paula Arantes Bueno, Joao Ricardo Sato","doi":"10.3390/world4020019","DOIUrl":"https://doi.org/10.3390/world4020019","url":null,"abstract":"Education plays a critical role in society as it promotes economic development through human capital, reduces crime, and improves general well-being. In any country, especially in the developing ones, its presence on the political agenda is necessary. Despite recent educational advances, those developing countries have increased enrollments, but academic performance has fallen far short of expectations. According to international evaluations, Latin American countries have made little progress in recent years, considering the level of investment in education. Thus, Artificial Intelligence (AI) models, which deal with data differently from traditional analysis methods, can be an option to better understand educational dynamics and detect patterns. Through a literature review using the PRISMA methodology, we investigated how AI has been used to evaluate educational performance in basic education (elementary and high school) in several countries. We searched five platforms, resulting in a total of 19,114 works retrieved, and 70 articles included in the review. Among the main findings of this study, we can mention: (i) low adherence to the use of AI methodology in education for practical actions; (ii) restriction of analyzes to specific datasets; (iii) most studies focus on computational methodology and not on the meaning of the results for education; and (iv) a less trend to use AI methods, especially in Latin America. The COVID-19 pandemic has exacerbated educational challenges, highlighting the need for innovative solutions. Given the gap in the use of AI in education, we propose its methods for global academic evaluation as a means of supporting public policy-making and resource allocation. We estimate that these methods may yield better results more quickly, enabling us to better address the urgent needs of students and educators worldwide.","PeriodicalId":23705,"journal":{"name":"WORLD","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135626368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Acculturative stress can be a big problem for international students. Among the adaptation difficulties they may face, adjusting to new foods in a new environment is crucial to their well-being. Existing studies related to dietary acculturation point to gender differences, mostly on objective health impacts. Using the information processing approach, this study aims to examine the subjective perception of dietary acculturation difficulties, with a focus on the influence of social connectedness. Using the Bayesian inference approach with the Hamiltonian Markov Chain Monte Carlo (MCMC) technique on a sample of 268 students from a Japanese international university, we found that female students are more likely to have perceived difficulties in the process of adjusting to new foods, but social connectedness lessens this effect. We also found no significant differences between domestic and international students regarding perceived difficulties of food adjustment in this study site, likely due to its highly multicultural environment. We suggest international universities provide better information about the food situations on campuses, especially for female students, and organize more cultural exchange events and food-related social activities to help students overcome barriers of food stress.
{"title":"A Gender Study of Food Stress and Implications for International Students Acculturation","authors":"Ruining Jin, Tam-Tri Le, Thu-Trang Vuong, Thi-Phuong Nguyen, Giang Hoang, Minh-Hoang Nguyen, Quan-Hoang Vuong","doi":"10.3390/world4010006","DOIUrl":"https://doi.org/10.3390/world4010006","url":null,"abstract":"Acculturative stress can be a big problem for international students. Among the adaptation difficulties they may face, adjusting to new foods in a new environment is crucial to their well-being. Existing studies related to dietary acculturation point to gender differences, mostly on objective health impacts. Using the information processing approach, this study aims to examine the subjective perception of dietary acculturation difficulties, with a focus on the influence of social connectedness. Using the Bayesian inference approach with the Hamiltonian Markov Chain Monte Carlo (MCMC) technique on a sample of 268 students from a Japanese international university, we found that female students are more likely to have perceived difficulties in the process of adjusting to new foods, but social connectedness lessens this effect. We also found no significant differences between domestic and international students regarding perceived difficulties of food adjustment in this study site, likely due to its highly multicultural environment. We suggest international universities provide better information about the food situations on campuses, especially for female students, and organize more cultural exchange events and food-related social activities to help students overcome barriers of food stress.","PeriodicalId":23705,"journal":{"name":"WORLD","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135441694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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