Get Complete Project Material File(s) Now! »
CHAPTER V A STATISTICAL ANALYSIS OF ACADEMIC CAREERS IN INDONESIA: COMPARING A RELIGIOUS AND A SECULAR UNIVERSITY
Overview
In this chapter I present some statistical data analysis on academic careers in Indonesia to understand the influence of gender compared to other independent variables such as educational qualification, age, and length of career. As mentioned in Chapter 2, academic career advancement in Indonesia is different to that in New Zealand’s system. This chapter presents statistical data to begin to explore whether the gender gap operates similarly across different national frameworks (a discussion of New Zealand follows in the next chapter). In addition, as the higher education system in Indonesia is a dual system -a state/public vs private system, and a religious vs secular system- the discussion will cover the comparison of a state/public religious and a secular university in Jakarta. Accordingly, this chapter is based on data obtained from Jakarta Indonesia; specifically, from a public religious and a public secular university. The data from the religious university consists of the curriculum vitae of 749 tenured academics with the status of civil of servants in 2013. This is almost all the civil servants employed at the university. The data from the secular university consists of 1570 academic profiles for 201422, which is around 65.5% of the available data from the Centre of Higher Education data from the Ministry of Education. While the datasets are not perfect matches, both encompass material about gender, year of appointment and length of tenure, age, and educational qualification. The most recent research around the topic of my thesis in Indonesia, and using multivariate analysis of variance (MANOVA), shows a trend where gender affects the career success of academic staff, and male academic staff are advantaged (Kholis 2013). The research by Kholis (2013) was conducted at Islamic higher education institutions in seven provinces in Indonesia, with 221 respondents. The seven provinces are South Kalimantan, West Nusa Tenggara, East Java, Central Java, West Java, Yogyakarta, Riau, and Aceh. However, it did not include Islamic higher education in Jakarta, the capital city. It tested the gender affect for two kinds of dependent variables: career productivity and career success. It used six indicators to measure career productivity: thesis supervision, committee appointment, publication, teaching, research, and scholarly presentation. There were four indicators to measure career success: academic rank, leadership position, monthly income, and career satisfaction. Other, intervening, variables consisted of gender, higher education, age, marital status, parental status, spouse education, and spouse occupation. The conclusion of the Kholis’ research is that women and men differ significantly only for publication. Other indicators (thesis supervision, committee appointment, teaching, research, and scholarly presentation) are statistically insignificant. On the other hand, in terms of career success, men obtain higher academic rank as well as salary; and reach better leadership positions than women. Following Dunkin’s thesis (1991), Kholis (2013) concluded that gender is influential in terms of objective measurement with men being advantaged. In terms of career satisfaction, women have a mean higher score, but it is not statistically significant. Likewise, men have a better mean score for work engagement, but the score is also not statistically significant. The argument goes that there is nearly equal scoring between men and women for the subjective measurements which cover career satisfaction and work engagement. The influential variables are age, spouse education and spouse occupation. On the other hand, marital status is marginally significant. Factors that are insignificant for career productivity are gender, highest education of respondent (educational qualification), and parental status.
Measurement and Variables
The Dependent and Independent Variables
The dependent variable in my research is academic career advancement.The independent variables are mostly demographic variables available in curiculum vitae such as gender, length of career, age, education qualification, type of university (origin of degree), marital status, number of children.The data set is classified into comparable and uncomparable variables because the datasets are not perfect matches. Comparable variable means that information is available in both universities, on the other hand, uncomparable variable means that information only avalailable in one university. The dependent variable can be classified as comparable variable. Some independent variables are comparable such asgender, length of career, age, education qualification. On the other hand, type of university, marital status, number of children are classified as uncomparable independent variables, accordingly, these variables are only used in descriptive statistics not in inferential statististics (binary and ordinal regression). Type of university is available in both universities but the number of missing data points for the secular university is significant, therefore, type of university is classified as an uncomparable variable.
Academic Career Advancement
Academic career advancement is measured by academic rank in the civil servant system. Based on Decree 38/1999, there are fiveacademic ranks:Tenaga Pengajar(teaching staff),Asisten Ahli (junior level), Lektor (lower mid-level), Lektor Kepala (upper-mid-level) and Professor/Guru Besar (senior level). The lowest level is coded 0 for Tenaga Pengajar, 1 for Asisten Ahli, 3 for Lektor, 4 for Lektor Kepala, and 5 for Professor/Guru Besar.For the reason of binary regression analysis, academic career advancement is classified into low and high rank; where the low rank consists of the three lowest levels in academic rank (Tenaga Pengajar, Asisten Ahli, Lektor), on the other hand, high rank consists of Lektor Kepala and Professor/Guru Besar. For the ordinal regression, academic rank is classified into three levels: low, middle, and high rank. The low rank is Tenaga Pengajar, Asisten Ahli; the middle rank is Lektor, and high rank covers Lektor Kepala and Professor/Guru Besar.
Length of tenure and age
Length of tenure has become a debatable independent variable for measuring career advancement because, in principle, it is not included in criteria for career advancement in many countries. However, the literature demonstrates its significant influence (Pezzoni, et.al 2012). Similarly, age does not formally affect career advancement, but the variable of age is clearly influential. Therefore, this research uses age and length of tenure as control/covariate variables. Both variables have characteristics as variables with ratio scales, and therefore can be incorporated directly in the model.
Educational Qualification
Educational qualification is expected to represent field-relevant capital for an academic career. According to Pierre Bourdieu (1986 86):“…academic qualification, a certificate of culture competence which confers on its holder a conventional, constant, legally guaranteed value with respect to culture; social alchemy produces a form of cultural capital which has a relative autonomy vis-à-vis its bearer the cultural capital he effectively possesses at a given moment.” Furthermore, Bourdieu (1986, 86) mentioned:“It makes it possible to establish conversion rates, between cultural capital and economic capital by guaranteeing the monetary value of a given academic capital. The material and symbolic profits which the academic qualification guarantees also depends on its scarcity, the investment made (in time and effort) may turn out to be less profitable than was anticipated when they were made (there having been a de facto change in the conversion rate between academic capital and economic capital). The strategies for converting economic capital into cultural, which are among the short term factors of schooling explosion and inflation of qualification are governed by changes in the structure of chances of profit offered by the different types of capital.” In contrast, it is interesting that the highest education level in one previous research paper is a statistically insignificant variable (Kholis 2013), while the promotion system by the law is determined, officially, by education qualification. The education qualification which has been accepted recently for an academic career in Indonesia is a Masters degree. However, as many academic staff still hold Bachelors degrees, the education qualification variable still includes the three levels of higher education which are coded: 1 for a Bachelors degree, 2 for a Masters degree, and 3 for a PhD/Doctoral degree. As each type of degree shows that one is higher than the other, the coding can also represent the value of each degree. However, some analysis uses two categories of educational qualification, low level coded 1 for Bachelors and Masters and high level coded 2 for PhDs.
Type of University (Origin of Degree)
The type of university is also a quite controversial issue. The most often used method to measure the type of university is the university rank system, either internationally, regionally or nationally. This thesis follows the idea that the form of social capital can be seen from all the social ties of actors and their relationship to prestigious universities. In Indonesia, for academics, obtaining a degree from international universities can be considered as having a better level of social capital, as they have expanded their networks into other countries and learnt to communicate in a different language. However, in terms regional rank, some public universities in Indonesia have reached a quite good rank among Asian countries, such as the University of Indonesia (UI), Bandung Institute of Technology (ITB), Gajah Mada University (UGM), Airlangga University, and Bogor Agriculture Institute, Padjajaran University (UNPAD) which have been ranked according to QS Top University in 2016 at 67, 85, 105, 109, 135, 191, 199 respectively out of the top 300.23 In terms of local universities, the prevailing modelling is based on the assumption that obtaining a degree from a public secular university is better than that from a public religious or private university. Some public universities have been ranked among the top 300 universities in Asia, but public religious universities have not achieved this position. A public religious university is considered better than a private university as it is a public university, and the percentage of academic staff holding only a Bachelorsdegrees is lower than that at private universities. As it has been argued, the quality of private higher education has been challenged by the lower percentage of formally qualified, competent staff. By 1990, only 11% of academic staff in private higher institution educations had earned more than a Bachelors degree (Buchori & Malik, 2004; Welch, 2007). Similarly, World Bank studies in 1996 presented that only 5.5% of academic staff in private higher education institutions held Masters or Doctoral qualifications. The limitation of the variable type of university is that the rank is based on assumptions which relied on the previous literature on undergraduates in private and public universities in university in general, not the situation in post-graduate programmes. In fact, the data for analysing the type of university is the data for the highest educational qualifications; either a Bachelors degree, a Masters degree, or a Doctoral degree. Despite the weaknesses of the classification of universities, data from Indonesia is classified based on three types of university: foreign, public and private universities. Academic staff holding Masters or Doctoral degrees from a foreign university are considered to have obtained better networks and experiences than those who hold degrees from Indonesia. Likewise, the measurements in this thesis are based on the assumption that academic staff who graduated from a public university in Indonesia have better social capital than those who graduated from a private university. However, for binary regression analysis the type of university is classified into national (coded 1) and overseas university (coded 2).
Gender, Marital Status, Number of Children.
Gender, marital satus and number of children are demographic varibles and relate to family life and the divison labour in society. However, for statistic analysis gender is similar to sex. Gender and marital status are dummy varible because both represent two different categories male and female (for gender) and yes or no (for marital status). Male is coded 1 and female 0; and similarly for marital status yes is coded 1, and no is coded 0. On the other hand, number of children is ratio scale variable.
Data Analysis
There are at least two strategies for analysing the data. The first method is descriptive; to present data based on gender and related percentages using means analysis, graphics and tables to illuminate the gender gap. The second method is statistical including binary and ordinal regression. Those method are considered the most appropriate because the characteristic of data does not meet the requirement of ordinary least square regression. The purpose of using binary and ordinal regression is to answer the next question: does gender matter for career advancement in both countries? Both descriptive and statistical analysis will test the following hypotheses: Based on the Gender Gap Index, it can be assumed that the gender gap in academic careers between men and women at universities in Indonesia very significant. Based on previous literature, the gender gap will be prevalent and gender is expected to be a significant factor for career advancement in Indonesia. The data classification into religious and secular universities is expected to answer another research question: how do cultural and religious interpretations, as well as institutional policies, influence academic career advancement? Based on existing literature about women in Indonesia, it can be assumed that the circumstances of family life of lecturers in Indonesia has been significantly influenced by religious and cultural interpretations that prevent women’s academic career advancement and support men’s careers. The religious interpretation of the role of women has been argued to be a factor in women’s marginalisation (Shaheed 1986). For example, literature on women in Indonesia (e.g. Brenner 1999; Adamson 2007) demonstrated that under existing religious and cultural discourses, women are expected to take on family responsibilities and domestic work as their primary occupations and they are not free to engage in public roles and careers. From these assumptions it is expected that the gender gap will be greater, and that gender will affect academic career advancement more significantly, in religious universities than in secular ones.
CHAPTER I – INTRODUCTION AND LITERATURE REVIEW
1.1.Problem Statement
1.2.Understanding the Gender Gap in Academic Careers in Western and non-Western Countries
1.3.Research Problem and Aims
1.4.Research Questions
1.5.Importance of Research
1.6.Literature Review
1.7.Proposed Structure of the Thesis
CHAPTER II – THE FIELD-RELEVANT CAPITAL OF ACADEMIC CAREERS: POLICY AND PRACTICE
2.1.Academic Life in Transition
2.2.Academic Life in Developing Countries
2.3.Academic Life and Academic Careers in Indonesia
2.4.University and Academic Careers in New Zealand
2.5.Conclusion
CHAPTER III – RESEARCH METHODS
3.1.Introduction to the Chapter
3.2.Philosophical Assumption & Research Paradigm Guiding the Study
3.3.Autoethnography
3.4.Starting My Autoethnography
3.5.Quantitative Data Analysis Using Secondary Data
3.6.Quatitative Data Analysis
3.7.Qualitative data analysis
CHAPTER IV – AUTOETHNOGRAPHY AND HABITUS
4.1.Context
4.2.My Career Field
4.3.My Career Advancement
4.4.Dealing with the Complexity of Career Promotion
4.5.My Educational Qualifications
4.6.My Family Background and Habitus
4.7.Religion, Culture, Islamic University
4.8.Conclusion
CHAPTER V – A STATISTICAL ANALYSIS OF ACADEMIC CAREERS IN INDONESIA: COMPARING A RELIGIOUS AND A SECULAR UNIVERSITY
5.1.General Overview
5.2.Measurement and Variables
5.3.Data Analysis
5.4.Data from a Religious University in Indonesia
5.5.Data from a Secular University in Indonesia
5.6.Discussion, Comparison and Conclusion
CHAPTER VI – A STATISTICAL ANALYSIS OF ACADEMIC CAREERS IN NEW ZEALAND: A FOCUS ON THE UNIVERSITY OF AUCKLAND
6.1.General Overview……
6.2.Academic Career Promotion Procedurec in New Zealand
6.3.The Gender Gap in New Zealand
6.4.Length of Career at The University of Auckland
6.5.Correlation and Regression
6.6.Conclusion
CHAPTER VII – QUALITATIVE DATA ANALYSIS FROM INDONESIA
7.1.Introduction to the Chapter
7.2.Female Academics: Household, Domestic Roles and Their Position in the Family
7.3.Being a Single Academic Female
7.4.Academic Careers: an Ideal Career for Women in Indonesia (?)
7.5.The Motherhood Penalty; Flexible Work and Female Academics as Secondary Earners
7.6.Gendered Career Ambition and Motivation
7.7.Academic Careers from a Male Academic Perceptive
7.8.Additional Income & Being late in Academic Career Advancement
7.9.Conclusion
CHAPTER VIII – QUALITATIVE DATA ANALYSIS FROM NEW ZEALAND
8.1.Introduction to the Chapter
8.2.Domestic Roles, Child Rearing and Female Academic Career Advancement
8.3.Gender stereotype, Race and the Intersectionality of Gender and Race
8.4.Indigenous and Local Academics
8.5.Perspective on Merit Based Standard
8.6.Subjectivity of the Committee
8.7.Conclusion
CHAPTER IX – DISCUSSION AND CONCLUSION
9.1.Introduction to the Chapter
9.2Field & Habitus
9.3.Career Capital
9.4.Neo-Institutional Analysis
9.5.Narrowing Trend for the Gender Gap, Balancing Family Life and The Gender Gap Index
9.6.Research Limitation
9.7.Recommendations for Future Research
GET THE COMPLETE PROJECT
A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Sociology