Studying in the United Kingdom

The United Kingdom is among the world leaders in recruiting international students.Joanna Burke,Cultural Counselor in the Cultural and Education Section of the British Embassy in China,recently spoke about international students,especially Chinese students in the United Kingdom,with Beijing Review reporter Wang Hairong.

Study on the Management of Chronic Diseases in American and British Community Pharmacy

Objective To provide a reference for promoting the construction of chronic disease management in community pharmacies in China.Methods Literature research and comparative research methods were used to analyze the management of chronic disease carried out by community pharmacies in the United States and the United Kingdom.Results and Conclusion The management of chronic diseases in American and British community pharmacies has formed retail health clinic and online chronic disease mode.It is recommended that Chinese government should issue measures and supporting guidelines for the management of chronic diseases in community pharmacies as soon as possible.Community pharmacies should be encouraged to carry out chronic disease management with the concept of prudent inclusion and gradual progression.Meanwhile,the concentration of drug retail industry should be improved to carry out the systematic construction of chronic disease management and build a standardized chronic disease service process.Besides,community pharmacies should make full use of new technologies such as the Internet,cloud computing and big data,smart wearable devices,and chronic disease management Apps to explore and carry out online professional chronic disease management mode.

The Study-to-work Transition of Chinese International Students: Navigating a Future in the Global Labour Market

In the global competition for talents,the massive inflow of Chinese students into the UK has drawn great attention.However,only a few studies examine students’interactions with socioeconomic structures in their study-to-work transition.This study used Higher Education Statistics AgencyHESA,22data and interview data collected from Chinese postgraduate students,and it aims to:investigate structural factors that influence post-study migration patterns of Chinese students;and explore how Chinese students interact with wider social structures.This study found that different configurations between students"goals,""actions,"and"reflexivity"would lead to different employment outcomes.Three different study-to-work transition strategies were identified:"proceeding without a fixed plan";"reaching a compromise";and"knowing goals and approaching goals".Findings suggest that the transition between study and work is more complex than what is described in human capital and push-pull approaches.A better understanding of students’decision-making processes would help higher education institutions in preparing graduates for careers in the global labour market.

Determinations of strategy responding to COVID-19

This study explores what determines the selection of strategies by governments responding to COVID-19.To answer the question,we propose concepts of individual utility and societal utility and build a simple model.By applying the model,we predict that countries with an individualist culture would adopt more passive strategies while countries with a collectivist culture would adopt more active strategies.The comparison between strategies adopted in China and in the United Kingdom supports the prediction.Furthermore,as the spread of COVID-19 virus continues,governments’response may change and individualist countries may switch to more active strategies.So we extend our model to incorporate the dynamics of strategy selection,and explain the switch between passive and active strategies.We then predict in particular that facing the unexpected infections and deaths,the countries with an individualist culture would temporally adopt a relatively more active strategy responding to COVID-19.The evidence from Spain shows the dynamic feature of strategy selection as predicted by our model.