A Business Alternative: Changing Employers\u27 Perception of the EEOC Mediation Program

This paper will reveal employers\u27 perception of the EEOC Mediation Program and offer viable changes that may encourage more employer participation in the mediation program. Although the mediation program is supposed to be fair and neutral, the possibility of favoritism, bias, prejudice, or the perception thereof remains high because of the mediation program\u27s structure. If the EEOC were to make changes to its program that also creates a perception of impartiality, then employers would be more willing to participate. To demonstrate this, Part II of this article will begin by discussing the history of the EEOC from its initiating mandate to its current form. Then, Part III will cover EEOC mediation by explaining how the process works and its limitations. Part IV will display statistics concerning the mediation program\u27s work volume and resolution rates, and Part V will discuss reasons why employer participation in the mediation program is so low. Part VI of this article will then discuss the components needed to facilitate a fair and impartial mediation, and whether or not the current EEOC Mediation Program possesses those components. Lastly, Part VII will provide a feasible solution that could eradicate any impropriety, or perception of impropriety, in EEOC mediations

Measuring the Impact of Living Wage Laws: A Critical Appraisal of David Neumark's How Living Wage Laws Affect Low-Wage Workers and Low-Income Families

Drawing on data from the Current Population Survey (CPS), David Neumark (2002) finds that living wage laws have brought substantial wage increases for a high proportion of workers in cities that have passed these laws. He also finds that living wage laws significantly reduce employment opportunities for low-wage workers. We argue, first, that by truncating his sample to concentrate his analysis on low-wage workers, Neumark’s analysis is vulnerable to sample selection bias, and that his results are not robust to alternative specifications that utilize quantile regression to avoid such selection bias. In addition, we argue that Neumark has erroneously utilized the CPS data set to derive these results. We show that, with respect to both wage and employment effects, Neumark’s results are not robust to more accurate alternative classifications as to which workers are covered by living wage laws. We also show that the wage effects that Neumark observes for all U.S. cities with living wage laws can be more accurately explained as resulting from effects on sub-minimum wage workers in Los Angeles alone of a falling unemployment rate and rising minimum wage in that city.

Tools for Tutoring Theoretical Computer Science Topics

This thesis introduces COMPLEXITY TUTOR, a tutoring system to assist in learning abstract proof-based topics, which has been specifically targeted towards the population of computer science students studying theoretical computer science. Existing literature has shown tremendous educational benefits produced by active learning techniques, student-centered pedagogy, gamification and intelligent tutoring systems. However, previously, there had been almost no research on adapting these ideas to the domain of theoretical computer science. As a population, computer science students receive immediate feedback from compilers and debuggers, but receive no similar level of guidance for theoretical coursework. One hypothesis of this thesis is that immediate feedback while working on theoretical problems would be particularly well-received by students, and this hypothesis has been supported by the feedback of students who used the system. This thesis makes several contributions to the field. It provides assistance for teaching proof construction in theoretical computer science. A second contribution is a framework that can be readily adapted to many other domains with abstract mathematical content. Exercises can be constructed in natural language and instructors with limited programming knowledge can quickly develop new subject material for COMPLEXITY TUTOR. A third contribution is a platform for writing algorithms in Python code that has been integrated into this framework, for constructive proofs in computer science. A fourth contribution is development of an interactive environment that uses a novel graphical puzzle-like platform and gamification ideas to teach proof concepts. The learning curve for students is reduced, in comparison to other systems that use a formal language or complex interface. A multi-semester evaluation of 101 computer science students using COMPLEXITY TUTOR was conducted. An additional 98 students participated in the study as part of control groups. COMPLEXITY TUTOR was used to help students learn the topics of NP-completeness in algorithms classes and prepositional logic proofs in discrete math classes. Since this is the first significant study of using a computerized tutoring system in theoretical computer science, results from the study not only provide evidence to support the suitability of using tutoring systems in theoretical computer science, but also provide insights for future research directions

Firm exporting and employee benefits: first evidence from Vietnam manufacturing SMEs

This study examines linkages between the export participation of firms and employee benefits in terms of wages and employment quality. Based on a uniquely matched firmworker panel dataset for 2007 and 2009, we find evidence that export participation by firms in Vietnam has a positive impact on wages when taking into account firm characteristics alone. However, the exporter wage premium falls when both firm and worker characteristics are controlled for, and it decreases further when controlling for time-invariant unobservable factors by spell fixed effect estimation. While there are many studies on the export wage premium, the role of export participation on the quality of employment remains largely unexplored. By using a firm-level balanced panel dataset for the same period, our results suggest that export participation has a negative effect on employment quality. Nevertheless, the impact of export participation on both wages and employment quality vary greatly with respect to levels of technology

Transformational Leadership and Job-related Learning

Various empirical studies have examined transformational leadership on the effects of followers and organisations. Transformational leadership has been related to individual attitudes and behaviors such as satisfaction with leaders, organisational citizenship behavior, organisational commitment, motivation, trust in leader, creativity, performance, employee involvement, and empowerment. It has also been linked to such organisational outcomes as innovation, change, productivity, ethical climate, and organisational learning. Organisational learning occurs at three levels: individual, group, and organisational. The focus of the present study is on the individual level—job-related learning. Job-related learning is a measure of individual job behavior pertaining to acquisition of knowledge and skills and enhancement of job performance within the context of the individual’s workplace. It argues that transformational leadership inculcates individuals’ drive to learn. The aim of the study is to examine the relationship between transformational leadership and job-related learning. Transformational leadership is composed of four unique but interrelated facets--idealised influence, individualised consideration, inspirational motivation, and intellectual stimulation. The research results support the hypothesis that transformational leadership is positively related to job-related learning. The implications of the research findings and suggestions for future research are discussed

A multi-species functional embedding integrating sequence and network structure

A key challenge to transferring knowledge between species is that different species have fundamentally different genetic architectures. Initial computational approaches to transfer knowledge across species have relied on measures of heredity such as genetic homology, but these approaches suffer from limitations. First, only a small subset of genes have homologs, limiting the amount of knowledge that can be transferred, and second, genes change or repurpose functions, complicating the transfer of knowledge. Many approaches address this problem by expanding the notion of homology by leveraging high-throughput genomic and proteomic measurements, such as through network alignment. In this work, we take a new approach to transferring knowledge across species by expanding the notion of homology through explicit measures of functional similarity between proteins in different species. Specifically, our kernel-based method, HANDL (Homology Assessment across Networks using Diffusion and Landmarks), integrates sequence and network structure to create a functional embedding in which proteins from different species are embedded in the same vector space. We show that inner products in this space and the vectors themselves capture functional similarity across species, and are useful for a variety of functional tasks. We perform the first whole-genome method for predicting phenologs, generating many that were previously identified, but also predicting new phenologs supported from the biological literature. We also demonstrate the HANDL embedding captures pairwise gene function, in that gene pairs with synthetic lethal interactions are significantly separated in HANDL space, and the direction of separation is conserved across species. Software for the HANDL algorithm is available at http://bit.ly/lrgr-handl.Published versio

Effects of lipids on the water sorption, glass transition and structural strength of carbohydrate-protein systems

peer-reviewedEncapsulant systems are gaining wide practical interest due to their functional and nutritional properties. This paper was focusing on understanding structural relaxations in that systems near glass transition temperature. Freeze-dried trehalose-whey protein isolate-sunflower oil systems with various ratios of the last were used as a carbohydrate-protein-lipid food model. The Guggenheim-Anderson-de Boer (GAB) water sorption relationship was used as a tool to model water sorption isotherms. The glass transition temperature was obtained by differential scanning calorimetry (DSC). Structural α-relaxation temperatures were measured by dynamical mechanical analyses (DMA), dielectric analysis (DEA) and combined to cover a broad range for strength assessment. The microstructure was characterized by optical light microscopy, confocal laser scanning microscopy and scanning electron microscopy. The C1 and C2 constants for Williams-Landel-Ferry (WLF) equation and structural strength parameter were calculated for each system. The effect of sunflower oil and water contents on strength of carbohydrate-protein system was analyzed. Strength shows decreasing with increasing of lipid concentration in the mixtures and more complex dependence on the water content in a system.This investigation was supported by the Food Institutional Research Measure (FIRM) project “Formulation and Design for Food Structure and Stability” funded by the Department of Agriculture, Food and Marine (11-F-001), coordinated by prof. Y.H. Roos, UCC, Ireland and by the Food Institutional Research Measure (FIRM) project “Developing the next generation of high protein spray dried dairy powders with enhanced hydration properties” (15-F-679) funded by the Department of Agriculture, Food and Marine, coordinated by Dr. Mark Auty, Teagasc Food Research Centre, Moorepark, Co. Cork, Ireland