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In this chapter, we take up the distinction between applied and general fields of study in order to consider how patterns of gender stratification between them may differ. Purporting to offer industry- and firm-specific skills, applied fields of study are often differentiated from general education pathways that are offered within the university sector. However, as our research demonstrates, there is considerable interplay between these two forms of education when higher education engagement over the life course is examined. Using sequence and cluster analysis, we illustrate five ideal-typical higher education pathways in a sample of males and females over a 22-year period in the Canadian province of British Columbia. The gendered patterns of how individuals choose and move between general and applied fields of study offer a deeper account of stratification within general and applied skill acquisition and provide nuance concerning how vocational education can be conceptualised in relation to the actual higher education pathways students undertake. In Canada, where a high percentage of students gain university-level credentials, vertical and horizontal gender stratification within applied and general fields of study is distinctive and highlights system-specific engagement.

The purpose of this research is to investigate the interdisciplinary relations in some high‐priority fields of science and technology based on ISI data.

This is an applied study using scientometric, citation analysis and network analysis methods. The study population consists of scientific articles of Iranian researchers in five fields that have been indexed in “WOS” database. These fields are included nanotechnology, biophysics, nuclear physics, sociology and communication. After identifying and extracting data from “WOS” (included 1,777 records), in order to determine the interdisciplinary relations and the evolution of these relationships, the citations of these records (41,080 citations) have been extracted and analysed.

The results indicate all the studied scientific fields have self‐citation and other‐citation. Depending on the type of field, the rate of intra‐disciplinary and extra‐disciplinary citations is various. There is a positive correlation between co‐authorship and interdisciplinary approach in all the studied fields. There is no significant relation between the number of citations and interdisciplinary approach. Overall, the results showed the use of only a bibliographic method cannot specify all aspects of interdisciplinarity of the scientific field. Simultaneous use of different analysis methods such as citation analysis, co‐authorship analysis and bibliographic coupling is necessary in order to data exchange between fields.

The analysis and mapping of interdisciplinary relations in a scientific field can provide useful information regarding connectivity and interdependence among areas. Through such studies, the status of cooperation between disciplines and the evolutionary trend of it is well defined. The results of these studies would also be useful in developing the interdisciplinary collaboration among professionals and understanding their information needs and plan to meet these needs.

The purpose of this paper is to sharpen the intellectual identity of the field of educational administration (EA) and to understand its scholarly boundaries by comparing between the writings of this field and those of the field of organisational behaviour (OB), an area of study usually located in faculties of management, and share many commonalities with EA.

A qualitative content analysis of textbooks and journal papers in OB and EA, reading of previous writings that revolved around the epistemological dimensions of these fields.

The author sheds light on the theoretical and empirical distinctions of OB and EA historically and provides insight into the distinctive intellectual identity of the latter field during the 2000s. A special attention is given to paradigms and theories in EA imported to the field from outside and transformed in a way that specify the unique identity of EA in the academic world.

This comparison is warranted in order to clarify more profoundly the unique contributions of EA, both theoretically and practically, to emphasise the differences that separate it from other disciplines, and to legitimate its independent position in higher education.

Despite the impressive record of advancing toward higher education, women are substantially underrepresented in science, technology, engineering, and math (STEM) fields compared to men. Less is known about the factors that explain gendered patterns of participation in STEM in countries with dissimilar national characteristics and educational systems. To fill this gap in the literature, this study first examines the historical trends of female representation in STEM fields cross-nationally. Then, this paper explores the relationship between women’s and men’s enrollments in STEM with various structural, national characteristics. Recognizing that the relationship may vary by subfields of STEM, the study further investigates the association separately for natural science and for engineering. Using time- and entity-fixed effects panel regression models pooled between 1970 and 2010, the study’s analyses built on earlier studies on gender segregation across fields of study and gender inequality in higher education. The findings suggest that the common assumption of tight, positive linkage between societal development and participation in STEM holds for only men at an aggregate level under the period covered. The authors find a negative association between national economic development and women’s participation in STEM, especially for engineering. On the other hand, they find positive associations between men’s enrollment in STEM as well as women’s enrollment in other fields of study with women’s participation in STEM. Taken together, the results suggest the significance of the diffusion of an inclusive logic in higher educational institutions.

Similar to community colleges in the United States, the Israeli tertiary system includes two-year technological colleges, which provide students with a labor-market relevant qualification. Nonetheless, unlike the community colleges, the technological colleges are not considered to be part of the higher education system and their transfer function is irregular and confined. In order to understand these differences, the chapter has two complementary objectives: (a) to describe the emergence and development of technological colleges and (b) to evaluate the implications for social inequality in access to higher education in Israel. We use a mixed-methods research design, including analyzing primary and secondary sources describing the official policy and public discourse around these colleges (qualitative/historical research) and comparing students attending academic institutions to students attending technological colleges and students across different fields of study offered by these colleges (quantitative research). Drawing on Phillip's (2004) model for policy attraction in education, we find that technological colleges in Israel were based on the Dutch HTS model, while the founding of these colleges was initiated by local impulse. The implementation of the technological colleges in the Israeli context was shaped by a cultural logic for higher education that emphasizes research and knowledge production, creating a binary tertiary system. Drawing on sociological literature on diversification and stratification in tertiary education, we find that technological colleges attract more students from disadvantaged groups and more students with relatively low academic ability than academic institutions. In addition, within technological colleges, students from advantaged background and higher academic ability are more likely to study in more prestigious fields of study. These findings suggest that if policy makers in Israel aspire to increase access to higher education, they should rethink policy instruments and cultivate the transfer function of technological colleges. This is among the first studies to examine technological colleges in Israel and we conclude with different directions for further research.

We focus our study on children of immigrants in science, technology, math, and engineering (STEM) fields because children of immigrants represent a diverse pool of future talent in those fields. We posit that children of immigrants may have a higher propensity to prepare for entering STEM fields, and our analysis finds some evidence to support this conjecture. Using the National Education Longitudinal Study (NELS: 88-00) and its restricted postsecondary transcript data, we examine three key milestones in the STEM pipeline: (1) highest math course taken during high school, (2) initial college major in STEM, and (3) bachelor’s degree attainment in STEM. Using individual level NELS data and country-level information from UNESCO and NSF, we find that children of immigrants of various countries of origin, with the exception of Mexicans, are more likely than children of natives to take higher-level math courses during high school. Asian and white children of immigrants are more likely to complete STEM degrees than third-generation whites. Drawing on theories of immigrant incorporation and cultural capital, we discuss the rationales for these patterns and the policy implications of these findings.

In this chapter, the interplay between the development of the discipline, the development of the field of study, and the emergence of professional fields is examined using the example of mathematics. In connection with the formation of the modern research university, mathematics has emerged as an independent scientific discipline and as an independent field of study. In the process, mathematics attains a high degree of formalization and internal coherence. This is the basis for the penetration of mathematicians into more and more professional fields, even outside science. Real problems or real facts are reduced to aspects that are amenable to mathematical modeling by treating them as quantifiable parameters. As mathematics expands as a field of study, more and more professional sectors become applications of mathematical models. As a consequence, more mathematical fields of study are differentiating themselves, specializing in these application fields. This chapter analyzes this dynamic and its preconditions.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy and main Islands (Sicily and Sardinia).

The analysis is firstly carried out at the national level, and secondly, it focusses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The authors analyse data in a regression setting (logit models) within the multilevel framework, which considers students at level 1 and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for clustering of students in fields of study and random slopes to allow the gender effect to differ among them.

Findings show that university student mobility in Italy leads evidence of gender bias. This has been detected using a multilevel random slope approach that allowed the authors to jointly estimate a slope parameter for gender within each field of study. Moreover, using a regression setting allowed the authors to control for heterogeneity in geographical, educational and socio-demographic characteristics across students. In line with previous empirical findings, the authors' data highlight the presence of a relevant mobility flow of university students from the South toward the North-Centre of Italy and lower mobility of female students compared to male students from the South and Islands.

To the best of the authors' knowledge, there are no studies in Italy, which investigate if families' investment in higher education in terms of selection of no-local universities are affected by gender bias and if geographical differences in this behaviour between macro-areas are in place. Thus, investigating students' choices in tertiary education allows the authors to shed light on the presence of gender bias in families' education strategies addressed to increase the endowment of students' assets for future job opportunities.