Measuring and Assessing Regional Education Inequalities in China under Changing Policy Regimes

Xiang, Lili; Stillwell, John; Burns, Luke; Heppenstall, Alison

doi:10.1007/s12061-019-09293-8

Cited by 40 publications

(33 citation statements)

References 48 publications

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“…S9, p value=0.0013, 9.81E-05, 8.18E-06 respectively for GDP increase, average annual GDP, and median annual GDP). Compared to previously reported GDP map of China (He, et al 2014; Xiang, et al 2020), there was an apparent association between the first reduced genetic feature of KLFDAPC and the provincial economic development metrics that would not be observed if we used PCs, although the association is not significant after correcting for multiple testing (Fig. S10).…”

Section: Resultscontrasting

confidence: 69%

KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure Analysis

Qin

Chiang

Gaggiotti

2021

Preprint

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Geographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect geographic patterns from genetic data is principal components analysis (PCA) or a hybrid linear discriminant analysis of principal components (DAPC). However, genetic features produced from both approaches are only linear combinations of genotypes, which ineluctably miss nonlinear patterns hidden in the genetic variations and could fail to characterize the correct population structure for more complex cases. In this study, we introduce Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC), a nonlinear approach for inferring individual geographic genetic structure that could rectify the limitations of these linear approaches by preserving the nonlinear information and the multimodal space of samples. We tested the power of KLFDAPC to infer population structure and to predict individual geographic origin using simulations and real data sets. Simulation results showed that KLFDAPC significantly improved the population separability compared with PCA and DAPC. The application to POPRES and CONVERGE datasets indicated that the first two reduced features of KLFDAPC correctly recapitulated the geography of individuals and significantly improved the accuracy of predicting individual geographic origin when compared to PCA and DAPC. Therefore, KLFDAPC can be useful for geographic ancestry inference, design of genome scans and correction for spatial stratification in GWAS that link genes to adaptation or disease susceptibility.

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Section: Resultscontrasting

confidence: 69%

KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure Analysis

Qin

Chiang

Gaggiotti

2021

Preprint

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“…Specifically, gender differences have been shown to play a role in various aspects of L2 learning, such as the level of language anxiety in the EFL learning context (Jiang & Dewaele, 2019), and attitudes toward learning French (L2) and English (L1) and French learning orientations (Baker & Maclntyre, 2000). Furthermore, university locations have been found relevant to the regional inequality of general education (Xiang et al, 2020); yet few studies have looked into the role of regional differences in L2 settings. It is assumed that L2 learning in universities is a process that progresses dynamically from the first year to the fourth.…”

Section: The Importance Of Demographic Factors To L2 Learningmentioning

confidence: 99%

Second language psychological speaking and listening needs: Scale development, symbiosis, and demographic differences

Qiu²

2022

10.14746/ssllt

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This study aimed to develop and validate two parallel scales to measure the psychological L2 speaking and listening needs of 863 English-as-a-foreign language (EFL) learners. The associations between three psychological needs (i.e., autonomy, competence, and relatedness) of L2 speaking and of L2 listening were examined to develop insights into oracy (i.e., integration of speaking and listening) in L2 communication. Subsequently, the impact of demographic variables was explored. The data, collected via a 5-point Likert-scale questionnaire, were analyzed through descriptive and correlation analysis, factor analysis, and ANOVA. Exploratory factor analysis was conducted to determine the factor structures, followed by confirmatory factor analysis for validation. Results demonstrated that the validity and reliability of the two developed scales were satisfactory. L2 speaking autonomy was significantly related to L2 listening autonomy, as were competence and relatedness. The three psychological needs of both L2 speaking and listening revealed varying patterns in terms of gender, major, university geographical context, schooling stage (first year to fourth year), and study-abroad experiences. The research findings reinforce the need for integration of L2 speaking and L2 listening when satisfying university students’ psychological needs, contribute to the research field with the measurement scales of psychological needs in L2 speaking and listening settings, and yield implications for teaching the two language skills integratedly.

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“…Access to education does not mean that women can obtain development opportunities and be liberated. It seems that there are broader and deeper factors at work [6]. In short, the equality of educational opportunity does not necessarily bring about the educational result, that is, the equality of development opportunity.…”

Section: The Influences On Femalesmentioning

confidence: 99%

Chinese Rural Female Students’ Situation in Accessing to Education Resources

Huang¹,

Huang²,

Lin³

et al. 2021

Proceedings of the 2021 International Conference on Public Relations and Social Sciences (ICPRSS 2021)

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This paper reviews and examines rural education's financial and family planning policies in China to explore the influencing factors of gender differences in education in China and the differences in access to educational resources between urban-rural female students. Below are three main arguments that this review show from three factors:(1) Finance: there are differences in the economic development level of each region in China, and insufficient educational investment issued by local governments restricts the development of rural schools. Meanwhile, elementary education resources and funds in China are allocated according to household registration, which also leads to the unfair developing opportunity for students; (2) Schools: due to unsafe risks caused by disadvantageous school locations, teachers' and textbooks' unbalanced care to boys' leadership, incomplete courses to support girls' art interests, these could cause negative impacts on cultivating characters and access to the educational resource for rural female students;(3) Family: under the influence of family planning disparity and boy preference, family is a significant factor in female students' education, especially for rural girls, who are facing more intense sibling competition than urban girls. Rural households are more willing to invest in boys' education, resulting in unequal educational resources due to gender inequality at the family level. This review also indicates the consequences of this phenomenon on rural female students in China: due to the lack of education, it is hard for them to realize their self-cognition and ideology, leading to early pregnancy, an unwanted marriage, and even mental illness. Therefore, it is important to further improve the female student's education, and it is worthy of our in-depth thinking.

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Measuring and Assessing Regional Education Inequalities in China under Changing Policy Regimes

Cited by 40 publications

References 48 publications

KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure Analysis

KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure Analysis

Second language psychological speaking and listening needs: Scale development, symbiosis, and demographic differences

Chinese Rural Female Students’ Situation in Accessing to Education Resources

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