Hong Kong Journal of Social Sciences

This study aims to examine and analyze the effect of the competence of the defense apparatus and military leadership on military intuition and the performance of defense policy implementation. This study uses a quantitative approach by conducting a quantification study related to the perspective of the defense policy of the defense apparatus. The data used are primary data with the research instrument in the form of a questionnaire. The population in this study is the entire community in the city of Bandung, Indonesia. The sample of this study was 200 respondents consisting of civilians and soldiers who served in the city of Bandung, Indonesia. Data analysis used the structural equation model (SEM) measurement model with the help of the WarpPLS package computer program. The results showed that: 1) Defense apparatus competence and military leadership have a positive and significant impact on military intuition; 2) Military intuition has a positive and significant effect on Defense Policy Performance, besides that Military Leadership and Military Intuition have a positive but not a significant effect on Defense Policy Performance; 3) Defense force competence has a significant effect on defense policy performance through military intuition and military leadership has a significant effect on defense policy performance through Military Intuition. Currently,  in several countries, there has been much research in the field of defense, but this article contains a novelty in that the researchers have more focused on the dimensions of analyzing the performance of capacity-building-based defense policy implementation.

Keywords: defense apparatus, military leadership, military intuition, policy implementation, structural equation model, WarpPLS.

To encourage economic growth to reduce the gap between provinces, the Indonesian government has implemented a decentralization policy implemented since 2001. Decentralization in Indonesia has been carried out until 2019 and has changed the country’s economic order. Researchers suspect that the development of the policy will impact the gap in the level of welfare between regencies and provinces in Indonesia. Armstrong and Taylor (2000) argued that the gap in the level of welfare between provinces should get important attention because this phenomenon will cause dissatisfaction, disappointment, and even resistance from people living in poor areas. This study implements the NEG framework model in dealing with regional disparities in Indonesia at the regencies and city levels, consisting of 514 regions. By use of quantitative method, the analysis used panel data regression analysis. The data analyzed are GRP per capita as the dependent variable and the independent variables are Domestic Market Access, Foreign Market Access, Urbanization, and Human Capital in 2016–2019. The novelty of this work is the first attempt to discuss the NEG model using panel data from all regencies and cities in Indonesia from 2016–2019. The application of the New Economic Geography Model framework in responding to the GRP gap per capita at the regency and city levels in Indonesia shows that the role of Domestic Market Access, Foreign Market Access, and Urbanization has a substantive impact on the GRP per capita gap between regencies and cities in Indonesia.

Keywords: new economic geography, disparities, regions, regencies, cities, Indonesia.

With the rapid development of multimedia and the internet, traditional discourse analysis, which only studies text, is gradually transferred to multimodal discourse analysis (MDA), studying image, language, color, sound, etc. Informed by Systemic Functional Linguistics, this paper tries making a multimodal discourse analysis of the BBC documentary Chinese New Year: The Biggest Celebration on Earth (CNY). Based on Kress & Van Leeuwen’s Visual Grammar and Zhang Delu’s visual-verbal Inter-semiotic relations, the paper examines how different semiotic modes combine to provide meaning in a documentary. After a synthesis analysis, it is concluded that the employment of various modes in this dynamic discourse contributes to the spreading of Chinese culture and the representation of “Cultural China” image. It is hoped that this paper will provide a new perspective for the semiotic studies of documentaries. The study's importance lies in demonstrating how numerous modes and sub-modes are employed in the source domains as part of a larger persuasion campaign to skew public perceptions of China. Additionally, we look at the metaphorical implications.

Keywords: multimodal discourse analysis, systemic functional linguistics, BBC documentary.

This study is the result of testing the concept of a flipped classroom (FC) in an ESP class in the aftermath of COVID-19 scenario at a private university in Oman. The recent shift from online classes to face-to-face classes in the university exposed a significant knowledge gap that existed in the learners of English for ESP courses. To address this challenge, the authors decided to experiment on the concept of the FC in an ESP class for business administration students. As a result, instead of a classroom lecture, the simplified summary of prescribed lessons along with useful illustrations were posted online for the students to read at home before coming to the class. Consequently, the class-time was mainly used for solving application questions individually or in groups of mixed ability students. Additionally, special attention was given to slow learners during the experiment. This experiment proved to be very beneficial for the students as there was significant improvement in their grades for both ongoing and final assessments compared to the grades of students in another section of the same course that followed the traditional lecture method. The focus of the experimental class was on making students solve critical homework tasks during the class-time with appropriate teacher intervention. The first part of this paper describes the important FC concepts and their implementation in an ESP classroom and the second part analyses the final grades of both FC and traditional classes to understand the relevance of the FC model for ESP students. Therefore, the research goal of this study is to determine the effectiveness of the Flipped Classroom methodology by critically evaluating its pros and cons compared to the traditional lecture method. The novelty of this study consists in recommending complete inversion of the role of the traditional lecture method and homework tasks. In other words, FC believes that traditional lectures should be replaced with critical home-work tasks during the class-time to achieve the goal of education. The revolutionary concept of solving critical home-work tasks and exploring the practical applications of fundamental theories during the class-time can empower students to reconstruct and apply knowledge in practical and personally meaningful ways instead of spending their time listening passively to lectures. Therefore, implementing Flipped Classroom methodology in ESP classes can enhance the critical and cognitive skills of learners effectively.

Keywords: critical thinking, ESP course, flipped classroom, problem-solving, traditional class.

The unemployment crisis has been a persistent issue for both developed and developing countries, resulting in an economic indicator deficit. Women are at a disadvantage and continue to encounter significant obstacles to gaining employment. Nigeria, like many other developing countries with high unemployment rates, has a 33% unemployment rate. Consequently, there has been minimal research on the factors that affect women's unemployment. As a result, the purpose of this study investigates the factors that influence women's unemployment in Nigeria. Although the Random Forest model has been widely applied to classification issues, there is a gap in the literature's use of the random forest as a predictor for analyzing factors influencing women's unemployment. The random forest model was employed in this study because of its characteristics such as strong learning ability, robustness, and feasibility of the hypothesis space. As a result, the Random forest prediction model was benchmarked with seven different cutting-edge classical machine learning prediction models, which include the J48 pruned tree, Support Vector Machine, AdaBoost, Logistic Regression, Naive Bayes, Logistic Model Tree, Bagging, and Random Forest. The experimental results demonstrate that Random Forest outperformed the other seven machine learning classifier models using ten commonly used performance evaluation metrics. According to the study's findings, age groups, ethnicity, marital status, and religion were the essential factors affecting women's unemployment in Nigeria.

Keywords: machine learning, National Demographic and Health Survey, random forest, influencing factors, women unemployment.