Strategies for Teacher Education Programs to Support Indigenous Teacher Employment and Retention in Schools

This article seeks to contribute to the knowledge base regarding efforts to increase the supply of employed Indigenous teachers. In addition to supporting the learning and well-being of Indigenous students, increasing Indigenous teachers is critical for remote Indigenous communities with chronically understaffed schools. This study was conducted as a scoping review of 50 Teacher Education Programs (TEPs) across Canada, Australia, New Zealand, and the United States that have enacted efforts to increase Indigenous teachers. The study found a range of effective strategies, and this article will depict three strategies that can be enacted by TEPs to support Indigenous teacher graduates as they transition to employment. The strategies are: (1) creating employment opportunities, (2) identifying community needs and collaborating over practicum placements, and (3) providing ongoing support. The article concludes with a call for collaboration, funding, and data collection for the continued evaluation and improvement of strategies to increase Indigenous teachers. Keywords: teacher retention, teacher support, teacher employment, Indigenous teacher education, job transition, Indigenous teachers, Indigenous education, teacher education programs

Skill-driven recommendations for job transition pathways

Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because new technologies emerge or production is moved abroad. Perhaps it is a global crisis, such as COVID-19, which shutters industries and displaces labor en masse. Regardless of the impetus, people are faced with the challenge of moving between jobs to find new work. Successful transitions typically occur when workers leverage their existing skills in the new occupation. Here, we propose a novel method to measure the similarity between occupations using their underlying skills. We then build a recommender system for identifying optimal transition pathways between occupations using job advertisements (ads) data and a longitudinal household survey. Our results show that not only can we accurately predict occupational transitions (Accuracy = 76%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other). We also build an early warning indicator for new technology adoption (showcasing Artificial Intelligence), a major driver of rising job transitions. By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19). They can be leveraged by policy-makers, educators, and job seekers who are forced to confront the often distressing challenges of finding new jobs.

Discrimination and Monopsony Power

Wage inequalities between identical workers of different race, ethnicity, and gender are a persistent feature of labor markets. However, most labor market models either ignore important empirical evidence or focus very narrowly on specific labor market dynamics. To better understand such wage differences, we create a labor market model that integrates firm competition for workers, employee movement between jobs in response to market signals, potential monetary frictions in the job transition process, and workers' collective action which is a function of government support. Our model shows that because of gender- and race-specific historical and social outcomes, like the relatively lower household wealth of Black and Latino families and the increased household responsibilities of women, women and minority workers are more exploitable; employers can push their wage farther below the value of their marginal product. Also, our model shows that the cumulative wage gap for non-White women is greater than the additive gaps of being nonmale and non-White. Lastly, our model shows that a reduction in government support for collective action enables employers to wield monopsony power more freely, independent of changes in employer concentration. Because certain groups are more exploitable, employers' increased capability in wielding monopsony power means increased wage differentials replicating discriminatory biases against marginalized groups of workers.

Returns to Educational Attainment in Urban Ghana: The Role of Job-to-Job Transition

It is well established that additional educational attainment above lower secondary yields higher returns. We find that these returns are mediated by the job transitions, especially for individuals with vocational education. We then study whether the job-to-job transition explains the differences in the returns to educational attainment and find evidence of positive returns of the movement from employee to self-employed. We show that successful employee voluntary move to self-employment to maximize their earnings, while early spell of self-employment tends to have a lasting negative effect on earnings. Our analysis partially explains why self-employment is the top final destination for many workers in developing countries.

Research shows scale of financial compensation, company culture and senior management performance have big influence on decisions to leave companies

Purpose The purpose of this study is to develop tree-based binary classification models to predict the likelihood of employee attrition based on firm cultural and management attributes. Design/methodology/approach After preliminary analysis, the authors tested three hypotheses. One was: “Conditioned on an increase in salary, the magnitude of increase enhances the likelihood that an employee will leave their current firm despite differences between the old and new firm culture.” Two was: “Employees whose original firm has an overall rating greater than the 75th percentile that was also founded before 1900 are more likely to stay…” Finally, three was that: “Employees that maintain a low overall original firm rating are more likely to leave their firm upon a job transition, whereas those with higher overall ratings have a greater chance of remaining.” Findings After analyzing thousands of online resumes submitted to Glassdoor’s portal, the authors found that the scale of financial compensation, the company culture and senior management performance all played a major role in influencing decisions to move on. Originality/value They offered three concrete recommendations based on the study. First, they said it was vital for companies to maintain strong Glassdoor.com ratings. The results revealed that firms in the top 10% of ratings were over 30% more likely to retain employees during a job transition than companies in the lowest 10%. Second, providing competitive salaries was necessary. Finally, the data showed a large discrepancy between senior management and CEO Glassdoor ratings. The researchers advised HR departments to closely monitor the impact of senior management behaviour.

From Traditional Science Teaching to the i2Flex Classroom

The chapter contains a personal reflection of the challenges encountered when a multilayered job transition took place: a PhD scholar doing scientific research and teaching in the Greek high-school system with traditional means and teaching philosophy transformed into an IB (International Baccalaureate) Science teacher using a constructivist teaching approach and technology tools to facilitate instruction. It is discussed how the i2Flex methodology was instrumental in guiding this transition. Relevant interventions in the IB classroom are described and discussed. An account of how previous experience in different sectors affected this transition is presented. Finally, i2Flex-based practices promoting student engagement and fair assessment in a fully online teaching setting are discussed.

Occupational mobility and automation: a data-driven network model

The potential impact of automation on the labour market is a topic that has generated significant interest and concern amongst scholars, policymakers and the broader public. A number of studies have estimated occupation-specific risk profiles by examining how suitable associated skills and tasks are for automation. However, little work has sought to take a more holistic view on the process of labour reallocation and how employment prospects are impacted as displaced workers transition into new jobs. In this article, we develop a data-driven model to analyse how workers move through an empirically derived occupational mobility network in response to automation scenarios. At a macro level, our model reproduces the Beveridge curve, a key stylized fact in the labour market. At a micro level, our model provides occupation-specific estimates of changes in short and long-term unemployment corresponding to specific automation shocks. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having few job transition opportunities. In an automation scenario where low wage occupations are more likely to be automated than high wage occupations, the network effects are also more likely to increase the long-term unemployment of low-wage occupations.

BLUE GRABBING AMIDST THE APPLICATION OF BLUE ECONOMY

Over the past decades, the roles of the ocean have become more crucial. Apart from its increasingly environmental roles, the ocean has been a new global economic frontier. This makes international communities have introduced blue economy, as a new paradigm that integrates the principles of social inclusion, environmental sustainability, and economic growth, to steward the ocean. Nonetheless, the ocean is also threatened by the practices of blue grabbing. This paper aims to investigate to what extend the practices of blue grabbing form a barrier to the application of blue economy in Indonesia. Moreover, this paper aims to discuss the policy implication of this issue. It is revealed that in the case of Indonesia, blue economy has preceded to a better design of policies in governing the ocean. Yet, a threat in the form of blue grabbing, which is mostly disguised by the narratives of providing incentives for investment and recovering the environmental destruction, still exists in this country. Policy implications of this issue, therefore, include engaging more small actors into policy-making processes, preparing job transition for those impacted by marine and coastal development plans, and mainstreaming population policy into the blue economy.

Career self-management of unemployed workers: the role of proactive coping in job-to-job transition

PurposeJob search behavior is an important factor of an individual's career. In this study, proactive individuals' search for career opportunities during the transition from unemployment to employment is investigated. This investigation concentrates on the “in-between jobs” phase to better understand career transition. Proactive coping is a particularly important aspect of the transition from unemployment to work.Design/methodology/approachUsing the career self-management model and proactive coping theory, this paper establishes a conceptual model and adopts path analysis to examine the model with a sample of 208 unemployed workers from Poland.FindingsThe results indicate both direct and indirect effects for proactive coping on job-seeking behavior. Unemployed job seekers, with greater proactive coping, intensify their job search behavior and increase their chances for re-employment.Practical implicationsProactive coping is an important factor in career development. The findings of this study are a promising starting point for career self-development training for unemployed workers in transition.Originality/valueMost of the training for the unemployed prepares them to react and adapt to ongoing circumstances. Our findings show the importance of being proactive during active coping with unemployment.