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This article examines whether the chances of job placements improve if the unemployed are counselled by caseworkers who belong to the same social group, defined by gender, age, education and nationality. Based on an unusually informative dataset, which links Swiss unemployed to their caseworkers, we find positive employment effects of about 3 percentage points if the caseworker and his unemployed client belong to the same social group. Coincidence in a single characteristic, e.g., same gender of caseworker and unemployed, does not lead to detectable effects on employment. These results, obtained by statistical matching methods, are confirmed by several robustness checks.

This article reports the results from a randomized experiment designed to evaluate the direct and indirect (displacement) impacts of job placement assistance on the labor market outcomes of young, educated job seekers in France. We use a two-step design. In the first step, the proportions of job seekers to be assigned to treatment (0%, 25%, 50%, 75%, or 100%) were randomly drawn for each of the 235 labor markets (e.g., cities) participating in the experiment. Then, in each labor market, eligible job seekers were randomly assigned to the treatment, following this proportion. After eight months, eligible, unemployed youths who were assigned to the program were significantly more likely to have found a stable job than those who were not. But these gains are transitory, and they appear to have come partly at the expense of eligible workers who did not benefit from the program, particularly in labor markets where they compete mainly with other educated workers, and in weak labor markets. Overall, the program seems to have had very little net benefits.

We examine labour market performance in the US and the UK prior to the onset of the Covid-19 crash. We then track the changes that have occurred in the months and days from the beginning of March 2020 using what we call the Economics of Walking About (EWA) that shows a collapse twenty times faster and much deeper than the Great Recession. We examine unemployment insurance claims by state by day in the US as well as weekly national data. We track the distributional impact of the shock and show that already it is hitting the most vulnerable groups who are least able to work from home the hardest – the young, the least educated and minorities. We have no official labour market data for the UK past January but see evidence that job placements have fallen sharply. We report findings from an online poll fielded from 11–16 April 2020 showing that a third of workers in Canada and the US report that they have lost at least half of their income due to the Covid-19 crisis, compared with a quarter in the UK and 45 per cent in China. We estimate that the unemployment rate in the US is around 20 per cent in April. It is hard to know what it is in the UK given the paucity of data, but it has gone up a lot.

To be competitive, universities across the world are embedding an international perspective into every layer of an institution’s operational structure. For higher education (HE) providers that offer sandwich degrees (4-year undergraduate courses with a compulsory placement after the second year), this allows students to choose a range of options. Students can enter the labour market for one year, or they can go overseas to study at a foreign institution. For some students, it might even be possible to do both. However, regarding final year degree performance, which option leads to higher student performance? In this paper, we aim to shed light on this empirical question. Our results are drawn from Aston University (UK) which is a world-leading University in Advanced Technology. Overall, using a large student dataset, we find that for students who have a compulsory placement built into their degree programme, the work placement has a more powerful impact on student performance compared to an international study placement abroad. Our findings have important implications for universities across the world that offer sandwich degrees to their students.

Machine Learning concept learns from experiences, inferences and conceives complex queries. Machine learning techniques can be used to develop the educational framework which understands the inputs from students, parents and with intelligence generates the result. The framework integrates the features of Machine Learning (ML), Explainable AI (XAI) to analyze the educational factors which are helpful to students in achieving career placements and help students to opt for the right decision for their career growth. It is supposed to work like an expert system with decision support to figure out the problems, the way humans solve the problems by understanding, analyzing, and remembering. In this paper, the authors have proposed a framework for career counseling of students using ML and AI techniques. ML-based White and Black Box models analyze the educational dataset comprising of academic and employability attributes that are important for the job placements and skilling of the students. In the proposed framework, White Box and Black Box models get trained over an educational dataset taken in the study. The Recall and F-Measure score achieved by the Naive Bayes for performing predictions is 91.2% and 90.7% that is best compared to the score of Logistic Regression, Decision Tree, SVM, KNN, and Ensemble models taken in the study.

AbstractThe increased use of student internships and other forms of work placements in higher education programmes brings recognised benefits to students but also changes the risks for higher education institutions (HEIs) globally. This paper responds to the under-addressed problem for HEI managers of understanding the varying levels of risk of harm to students and HEIs, and the HEIs’ strategic responsibilities to understand how to mitigate the risk for both parties. We develop a typology of the main types of internship placements and theorise their associated levels of risk according to the HEI’s levels of responsibility and operational control. The risk types are then plotted in a model of risk mitigation, mapped against the frequency of their occurrence and the severity of their impact, with a focus on HEIs and students. We conclude with practical and policy implications for HEIs and their managers. Our paper argues that HEIs must balance their risks and responsibilities with the costs and benefits of student internships and work placements, and contributes to understanding potential gaps between HEI strategic decision-making and operational practice at the programme level, along with solutions to address these.

Undergraduate internships have gained popularity among students, universities, governments and firms since the creation of the European Higher Education Area. However, empirical research on the relationship between internships and labour market performance of graduates is still scarce, particularly in Spain. This paper examines whether internships improve job attainment in the short run (first employment after graduation) and in the medium/long term (employment 4 years later). We use the first Spanish University Graduate Job Placement Survey (2014) to estimate linear probability models and probit models. A novel econometric technique is also implemented to evaluate the sensitivity of our findings to omitted variable bias. We disentangle the internship effect on (i) the time it takes to find the first job; (ii) the vertical, horizontal and skills matching with the first job; (iii) being employed in the medium/long term; (iv) the vertical and horizontal matching with the current employment; and (v) wage quintiles of the current job. Our results show that internship experience facilitates the university-to-work transition for Spanish graduates. Although the effects of internships on being employed do not vanish in the medium/long term, there is weak evidence of positive effects on matching four years after graduation and no effects are found on wages. (HRK / Abstract übernommen).

Transition-age youth with autism (TAY-ASD) experience poor employment outcomes and gaps in services that could assist them in securing jobs. Vocational rehabilitation (VR) is a source of public assistance for people with disabilities seeking employment and TAY-ASD are a growing segment of VR service users. Postsecondary education (PSE) is essential for building vocational skills, contributing to employment satisfaction and better wages. VR provides services to support PSE success. Fewer TAY-ASD received PSE training from VR (18%) than TAY with other disabilities (32%), but more than TAY with an intellectual disability (15%). TAY-ASD who received PSE training were more likely to exit VR with a job. The importance of PSE to employment should be considered in TAY-ASD who seek employment supports.

In this paper we explore how the 'employable' student and 'ideal' future creative worker is prefigured, constructed and experienced through higher education work placements in the creative sector, based on a recent small-scale qualitative study. Drawing on interview data with students, staff and employers, we identify the discourses and practices through which students are produced and produce themselves as neoliberal subjects. We are particularly concerned with which students are excluded in this process. We show how normative evaluations of what makes a 'successful' and 'employable' student and 'ideal' creative worker are implicitly classed, raced and gendered. We argue that work placements operate as a key domain in which inequalities within both higher education and the graduate labour market are (re)produced and sustained. The paper offers some thoughts about how these inequalities might be addressed.

This paper examines the impact of hukou and college education on job placement and wage attainment for Chinese rural migrant workers in the cities. The analysis of the 2010 Chinese General Social Survey shows that when rural-born individuals gain both urban hukou and college education, they enjoy equal job-sector placement and they earn significantly higher wages than the college-educated locals. But in the absence of a rural-to-urban hukou transfer, migrants have fewer opportunities to go to college than local peers, and even college education does not gain a migrant an equal chance of working in the state sector or receiving equal earnings. A major contribution of this study is to suggest a nine-category analytic scheme, which takes into account how education, hukou and type of workplace affect one another in jointly influencing labour market inequality between rural migrants and urbanite workers. 本文考察了户籍和大学教育对中国城市农民工就业安排和工资收入的影响。对2 0 1 0年中国全 面社会调査的分析表明，当出生于农村的人同时获得城市户口和大学教育时，他们享有同等的 就业机会，他们的工资比受过大学教育的本地人高得多。但是，如果没有从农村到城市的户籍 转换，外来人口上大学的机会就少于本地同龄人，即使大学教育也没有给外来人口在国有部门 工作或获得同等收入的平等机会。本研宄的一个主要贡献是提出了一个九类分析方案，该方案 考虑了教育、户口和工作场所类型如何相互影响，共同影响农民工和城市工人在劳动力市场中 遭遇的不平等现象。