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This report describes the current educational and employment situation of Australian Indigenous youth in terms of their pathways from school to work. A literature review and analysis of statistical data identify barriers to successful transition from school to work, including forms of teaching, curriculum, and assessment that pose greater educational challenges for Indigenous youth, as well as broader social issues such as racism, poverty, poor health, remote location, incarceration, and absence of employment opportunities. The report also highlights the need for improvements in educational outcomes as the key to improved results in the labor market. The literature review provides an overview of common features associated with successful transitions and programs, systemic weaknesses inhibiting success, relevant government programs, and issues and solutions at various youth transitions: primary to junior high school, junior high to senior high school, school to postsecondary vocational education, school to higher education, school to work, and unemployment to school or work. The statistical report uses data from the 1991 and 1996 censuses to examine the participation of Indigenous youth in education and their subsequent educational attainment and labor market participation. Data tables and analysis cover demography by geographic area and age, continuation in school to year 12 and dropout rates, participation in schooling and tertiary education, vocational education and training, higher education enrollment and persistence, educational attainment, labor market participation and assistance, and employment and unemployment in relation to educational attainment. An annotated bibliography contains 124 entries published 1988-98. (Contains 58 data tables.) (TD)

The relationship between prior educational attainment and participation in formal and On-the-Job Training (OJT) in Australia was examined through an analysis of unit record data from the 1993 Survey of Training and Education that was conducted by the Australian Bureau of Statistics. Univariate analyses were performed to document employee participation by level of educational attainment in three different types of training activities: external training, in-house training, and OJT. Multivariate analyses were then conducted to separate the effect of educational attainment from other variables (for example, age and occupation) that might affect training participation. Educational attainment was found to have a significant impact on employee participation in both formal and on-the-job training. Low levels of participation in training were particularly evident for individuals who had not completed secondary school and who held no postschool educational qualifications. Females, individuals in the 30-44 age bracket, individuals born in Australia or other English-speaking countries, individuals with their current employer for fewer than 3 years, individuals working in the public sector, and full-time employees in nonmetropolitan rural locations were most likely to participate in training. (Five tables and two graphs constitute approximately 50% of this document. (Contains 16 references.) (MN)

This study examines how cone penetration test (CPT) parameters, such as cone tip resistance and friction sleeve resistance, can be used to assess the compressibility of fine-grained soils across the Netherlands based on a database of 286 paired CPTs and oedometer tests from across the country. This is done with the aim of refining and simplifying the parameterisation of the Koppejan consolidation coefficients, a procedure which can yield significant error and is prone to misinterpretation. It was found that there is significant potential in using gradient boosting methods to obtain a relationship between the CPT parameters and the Koppejan parameters, with further investigation required into the noise within the dataset and the acquisition of additional high-quality samples. The use of such methods will offer a means of reducing the influence of human error or misinterpretation on the prediction of settlement and provide further confidence in the use of machine learning methods in engineering practice, Geo-engineering