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研究生： 朱梅花
Zhu, Mei-Hua
論文名稱： 性別薪資差異：世界趨勢、學生軟實力和專業領域
Gender Wage Gap: World Trend, Soft Skills, and Fields of Study
指導教授： 邱美秀
Chiu, Mei-Shiu
口試委員: 何英奇
Ho, Ying-Chyi
陳揚學
Chen, Yang-Hsueh
陳李綢
Chen, Lee-chou
張景媛
Chang, Ching-Yuan
學位類別： 博士
Doctor
系所名稱： 教育學院 - 教育學系
Department of Education
論文出版年： 2021
畢業學年度： 109
語文別： 英文
論文頁數： 84
中文關鍵詞： 性別薪資差異 、軟技能 、大學專業 、學測成績 、不平等
外文關鍵詞： gender wage gap, soft skill, college major, entrance score, inequality
DOI URL： http://doi.org/10.6814/NCCU202101065
相關次數： 點閱：92  下載：0 
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    • 勞動力市場的性別不平等是一個關鍵的全球性問題，性別薪資差異在許多國家的不同層面廣泛存在，數十年來一直是公眾關注的問題。前所未有的疫情加劇了國家內部和國家之間存在的收入不平等。而教育理應成為縮小薪資差距和收入不平等的工具，因此本文著重探索臺灣教育長期追蹤資料庫:後續調查(TEPS-B) 以及關於薪資差異的文獻，包含以下研究。
    研究一針對1980年至2020年發表的性別薪資差異研究進行了文獻計量分析。它描繪了經濟、社會學和教育三個特定領域中性別薪資差異研究的主要發展及其隨時間的演變。隨後的兩項研究主要通過從TEPS-B中提取數據來研究台灣的相關情況。
    研究二考察了TEPS-B中的學業成績和軟技能的性別差異，及其對性別薪資差異的影響。它通過分析相關數據來呈現性別薪資差異的狀況，以及基於社會文化理論的潛在解釋，從而提供了一些關於性別薪資差異的見解。
    研究三擴展了研究二的研究，進一步探討了大學專業學門對收入、學業成績和軟技能的性別差異的調節作用。最後，第五章通過總結三項研究的發現來概述論文，並提出對未來研究和教育實踐的啟示。

    Gender inequality in the labour market is a key global issue, the gender wage gap is widely existed at different levels in many countries and has been a public concern over decades. The unprecedented COVID-19 pandemic has exacerbated the earning inequality existing both within and across countries. Education is expected to be the great equalizer that narrows the gap and shrinks the income inequality. This thesis presents three studies on gender wage gap.
    Study 1 reports on a bibliometric analysis of gender wage gap research published from 1980 to 2020. It delineates the main development of gender wage gap research in three specific fields of economy, sociology, and education, and its evolution over time. The subsequent two studies primarily focused on Taiwan context by extracting data from Taiwan Education Panel Survey and Beyond (TEPS-B).
    Study 2 examines the gender difference in academic achievement and soft skills in higher education, and their impact on gender wage gap. It provides some insights on gender wage gap by presenting new empirical estimates to illustrate the extent of the gender wage gap and their potential explanations based on sociocultural theory.
    Lastly, Study 3 extends from the previous study and further examines moderating effects of college major on gender differences in income, academic achievement, and soft skills. Finally, Chapter 5 concludes the thesis by summarizing findings across the three studies and proposes implications for future research and educational practice.

    Acknowledgement ii
    Abstract iv
    Table of Contents v
    List of Tables viii
    List of Figures ix
    Chapter 1 Introduction 1
    Research Motivation 1
    Overview of the Study 2
    Key Terms of the Study 3
    References 5
    Chapter 2 Research on Gender Wage Gap: A Bibliometric Analysis (1980-2020) (Study I) 7
    Abstract 7
    Introduction 8
    Gender Wage Gap and Economy 8
    Gender Wage Gap and Sociology 8
    Gender Wage Gap and Education 9
    Research Questions 10
    Method 11
    Data Sources 11
    Data Analysis 11
    Results 12
    An overview of gender wage gap research 12
    Annual production of gender wage gap research 13
    Journals publishing relevant research 15
    Top authors of relevant research 17
    Most cited documents in gender wage gap research 19
    Analysis of keywords 21
    Discussion 28
    Insights from the Economic studies 28
    Insights from the Sociological studies 29
    Insights from the Educational and Psychological studies 29
    Strengths and Limitations 31
    Conclusions 31
    References 32
    Chapter 3 Transitions from Higher Education to Work: Gender Differences in Soft Skills for Income (Study II) 36
    Abstract 36
    Introduction 36
    The Gender Wage Gap 37
    Theoretical Basis for Gender Wage Gap 38
    Relations between Academic Achievement and Income 39
    Relations between Soft Skills and Income 40
    Taiwan Context 41
    The Present Study and Hypotheses 41
    Methods 42
    Data Sources and Sample 42
    Measures 42
    Data Analysis 43
    Results 44
    The Significant Gender Wage Gap 44
    Correlation and Regression Analyses on Variables 45
    Mediating Effects of Soft Skills on Income 46
    Discussion 49
    The Gender Wage Gap in Taiwan 49
    Gender Difference in the Significance of Education on Wage 50
    Gender Difference in the Significance of Soft Skills on Wage 51
    Conclusion 52
    References 54
    Chapter 4 Transitions from Higher Education to Work: Gender Differences in fields of study for Income (Study III) 57
    Introduction 57
    Rationales for Moderating Effects of College Major on Gender Differences in Income 58
    Rationales for Moderating Effects of College Major on Gender Differences in Soft Skills 58
    Rationales for Moderating Effects of College Major on Gender Differences in Achievement 59
    Research Questions 60
    Methods 60
    Data Sources and Sample 60
    Measures 62
    Data Analysis 63
    Results 64
    Gender differences in achievement, job income and soft skills for different college majors 64
    Path estimate differences in Model B for different gender, domain, and gender by domain 65
    Discussion 74
    Different effects of soft skills on wage between Humanities and Science majors 74
    Different effects of academic achievement on wage between Humanities and Science majors 74
    Conclusion 75
    References 77
    Chapter 5 General Discussion 80
    Summary of Findings: Studies 1-3 80
    Implications for Educational Practice 81
    References 82
    Appendices 83
    A: The Measures from TEPS-B 83
    B: The R Syntax for Path Analysis 84
    C: The R Syntax for Multi-group Analysis 84

    Table 1 An Overview of Gender Wage Gap Research Paper 12
    Table 2 Most cited articles by total citations and total citations per year 20
    Table 3 Results of correlation test for income, scores, and soft kills 45
    Table 4 Results of income regressed on college entrance scores and soft skills 46
    Table 5 Selected parameters for models A-B 47
    Table 6 Descriptive Statistic 67
    Table 7 Results for Tests of Between-subjects Effects with Gender and Major as the Independent Variables (Effect) and the Three Measures (soft skills, scores, and income) as the Dependent Variables 68
    Table 8 Results for Tests of Between-subjects Effects with Four Groups (2 genders * 2 majors) as the Independent Variables (Effect) and the Three Measures (soft skills, scores, and income) as the Dependent Variables 69
    Table 9 Selected parameters, fit indices, and information criteria values for Model B (multiple group SEM) 70
    Table 10 Selected parameters for Model B (single group SEM) 70

    Figure 1 Annual production of gender wage gap research in economic journals 13
    Figure 2 Annual production of gender wage gap research in social journals 14
    Figure 3 Annual production of gender wage gap research in educational journals 14
    Figure 4 Top ten economic journals publishing gender wage gap research 16
    Figure 5 Top ten social journals publishing gender wage gap research 16
    Figure 6 Top ten educational journals publishing gender wage gap research 17
    Figure 7 Top economists’ production over time 18
    Figure 8 Top sociologists’ production over time 18
    Figure 9 Top psychologists’ production over time 19
    Figure 10 Keywords with the strongest citation bursts in economic studies 23
    Figure 11 Keywords with the strongest citation bursts in social studies 24
    Figure 12 Keywords with the strongest citation bursts in educational studies 25
    Figure 13 Co-occurrence network by keywords in economic studies 26
    Figure 14 Co-occurrence network by keywords in social studies 27
    Figure 15 Co-occurrence network by keywords in educational studies 27
    Figure 16 Path model for all 48
    Figure 17 Path model for females 48
    Figure 18 Path model for males 49
    Figure 19 The mediating effects examined in this study 62
    Figure 20 Path Model for Humanities 71
    Figure 21 Path Model for Science 71
    Figure 22 Path Model for Male-Humanities 72
    Figure 23 Path Model for Female-Humanities 72
    Figure 24 Path Model for Male-Science 73
    Figure 25 Path Model for Female-Science 73

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    Chapter2
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    García-Aracil, A. (2008). College major and the gender earnings gap: A multi-country examination of postgraduate labour market outcomes. Research in Higher Education, 49(8), 733–757. https://doi.org/10.1007/s11162-008-9102-y
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    Morrissey, T. W., Hutchison, L., & Winsler, A. (2014). Family income, school attendance, and academic achievement in elementary school. Developmental Psychology, 50(3), 741–753. https://doi.org/10.1037/a0033848
    Olitsky, N. H. (2014). How do academic achievement and gender affect the earnings of STEM majors? A propensity score matching approach. Research in Higher Education, 55(3), 245–271. https://doi.org/10.1007/s11162-013-9310-y
    Reardon, S.F. (2013). The widening income achievement gap. Educational Leadership, 70 (8), 10–16. https://www.gc.cuny.edu/CUNY_GC/media/LISCenter/2019%20Inequality%20by%20the%20Numbers/Instructor%20Readings/Conwell-2.pdf
    Ritter, B. A., Small, E. E., Mortimer, J. W., & Doll, J. L. (2017). Designing management curriculum for workplace readiness: Developing students’ soft skills. Journal of Management Education, 42(1), 80–103. https://doi.org/10.1177/1052562917703679
    Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48 (2), 1–36. https://doi.org/10.18637/jss.v048.i02
    Thoemmes, F., Mackinnon, D. P., & Reiser, M. R. (2010). Power analysis for complex mediational designs using Monte Carlo methods. Structural Equation Modeling, 17(3), 510–534. https://doi.org/10.1080/10705511.2010.489379
    Walker, R. M., Damanpour, F., & Devece, C. A. (2011). Management innovation and organizational performance: The mediating effect of performance management. Journal of Public Administration Research and Theory, 21(2), 367–386. https://doi.org/10.1093/jopart/muq043
    Zafar, B. (2009). College major choice and the gender gap. Federal Reserve Bank of New York, Staff Reports, 48. https://doi.org/10.2139/ssrn.1348219

    Chapter5
    International Labour Office (ILO) (2019). World employment and social outlook: trends 2019. Geneva: Publications Production Unit (PRODOC) of the ILO. https://www.ilo.org/global/research/global-reports/weso/2019/WCMS_670542/lang--en/index.htm
    Landivar, L. C., Ruppanner, L., Scarborough, W. J., & Collins, C. (2020). Early signs indicate that COVID-19 is exacerbating gender inequality in the labor force. Socius: Sociological Research for a Dynamic World, 6, 2378023120947997. https://doi.org/10.1177/2378023120947997
    Reardon, S.F. (2013). The widening income achievement gap. Educational Leadership, 70 (8), 10–16. https://www.gc.cuny.edu/CUNY_GC/media/LISCenter/2019%20Inequality%20by%20the%20Numbers/Instructor%20Readings/Conwell-2.pdf
    Wood, W., & Eagly, A. H. (2012). Chapter two - Biosocial construction of sex differences and similarities in behavior. In J. M. Olson & M. P. Zanna (Eds.), Advances in Experimental Social Psychology (Vol. 46, pp. 55–123). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-394281-4.00002-7

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