Ethnic minority immigrants and their children in Britain

According to the 2001 UK Census ethnic minority groups account for 4.6 million or 7.9 percent of the total UK population. The 2001 British Labour Force Survey indicates that the descendants of Britain’s ethnic minority immigrants form an important part of the British population (2.8 percent) and of the labour force (2.1 percent). In this paper, we use data from the British Labour Force Survey over the period 1979-2005 to investigate educational attainment and economic behaviour of ethnic minority immigrants and their children in Britain. We compare different ethnic minority groups born in Britain to their parent’s generation and to equivalent groups of white native born individuals. Intergenerational comparisons suggest that British born ethnic minorities are on average more educated than their parents as well more educated than their white native born peers. Despite their strong educational achievements, we find that ethnic minority immigrants and their British born children exhibit lower employment probabilities than their white native born peers. However, significant differences exist across immigrant/ethnic groups and genders. British born ethnic minorities appear to have slightly higher wages than their white native born peers. But if British born ethnic minorities were to face the white native regional distribution and were attributed white native characteristics, their wages would be considerably lower. The substantial employment gap between British born ethnic minorities and white natives cannot be explained by observable differences. We suggest some possible explanations for these gaps

Intermarriage and immigrant employment: the role of networks

The social integration of immigrants is believed to be an important determinant of immigrants’ labor market outcomes. Using 2000 U.S. Census data, we examine how and why marriage to a native, one measure of social assimilation, affects immigrant employment rates. We show that even when controlling for a variety of human capital and assimilation measures, marriage to a native increases the probability that an immigrant is employed. An instrumental variables approach which exploits variation in marriage market conditions suggests that the relationship between marriage decisions and employment rates is not likely to arise from positive selection into marrying a native. We then present several pieces of evidence suggesting that networks obtained through marriage play an important part in explaining this effect

Interethnic marriage decisions: a choice between ethnic and educational similarities

This paper examines the effect of education on intermarriage and specifically, whether the mechanisms through which education affects intermarriage differ by immigrant generation and race. We consider three main paths through which education affects marriage choice. First, educated people may be better able to adapt to different customs and cultures making them more likely to marry outside of their ethnicity. Second, because the educated are less likely to reside in ethnic enclaves, meeting potential spouses of the same ethnicity may involve higher search costs. Lastly, if spouse-searchers value similarities in education as well as ethnicity, then they may be willing to substitute similarities in education for ethnicity when evaluating spouses. Thus, the effect of education will depend on the availability of same-ethnicity potential spouses with a similar level of education. Using U.S. Census data, we find evidence for all three effects for the population in general. However, assortative matching on education seems to be relatively more important for the native born, for the foreign born that arrived at a fairly young age, and for Asians. We conclude by providing additional pieces of evidence suggestive of our hypotheses

I’ll marry you if you get me a job: cross-nativity marriages and immigrant employment rates

This paper tests whether marriage to a native affects the probability that an immigrant is employed. We provide a theoretical background which explains how marriage to a native may positively or negatively affect an immigrant’s employment probability. Utilizing the 2000 U.S. Census, we first look at the effect of cross-nativity marriages on employment using a linear probability model. Then, we estimate a two stage least squares model instrumenting for cross-nativity marriages using local marriage market conditions. Results from a linear probability model controlling for the usual measures of human capital and immigrant assimilation suggest that marriage to a native increases the employment probability of an immigrant by approximately 5 percentage points. When controlling for the endogeneity of the intermarriage decision, marriage to a native increases the employment probability by about 11 percentage points. We provide alternative explanations and suggest policy implications

From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks

Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need several components to realize this potential. We investigate the crucial component of student modeling, in particular, the ability to automatically infer students' misconceptions for predicting (synthesizing) their behavior. We introduce a novel benchmark, StudentSyn, centered around the following challenge: For a given student, synthesize the student's attempt on a new target task after observing the student's attempt on a fixed reference task. This challenge is akin to that of program synthesis; however, instead of synthesizing a {solution} (i.e., program an expert would write), the goal here is to synthesize a {student attempt} (i.e., program that a given student would write). We first show that human experts (TutorSS) can achieve high performance on the benchmark, whereas simple baselines perform poorly. Then, we develop two neuro/symbolic techniques (NeurSS and SymSS) in a quest to close this gap with TutorSS

Custom architecture for multicore audio Beamforming systems

The audio Beamforming (BF) technique utilizes microphone arrays to extract acoustic sources recorded in a noisy environment. In this article, we propose a new approach for rapid development of multicore BF systems. Research on literature reveals that the majority of such experimental and commercial audio systems are based on desktop PCs, due to their high-level programming support and potential of rapid system development. However, these approaches introduce performance bottlenecks, excessive power consumption, and increased overall cost. Systems based on DSPs require very low power, but their performance is still limited. Custom hardware solutions alleviate the aforementioned drawbacks, however, designers primarily focus on performance optimization without providing a high-level interface for system control and test. In order to address the aforementioned problems, we propose a custom platform-independent architecture for reconfigurable audio BF systems. To evaluate our proposal, we implement our architecture as a heterogeneous multicore reconfigurable processor and map it onto FPGAs. Our approach combines the software flexibility of General-Purpose Processors (GPPs) with the computational power of multicore platforms. In order to evaluate our system we compare it against a BF software application implemented to a low-power Atom 330, amiddle-ranged Core2 Duo, and a high-end Core i3. Experimental results suggest that our proposed solution can extract up to 16 audio sources in real time under a 16-microphone setup. In contrast, under the same setup, the Atom 330 cannot extract any audio sources in real time, while the Core2 Duo and the Core i3 can process in real time only up to 4 and 6 sources respectively. Furthermore, a Virtex4-based BF system consumes more than an order less energy compared to the aforementioned GPP-based approaches. © 2013 ACM

Employers and the Gender Wage Gap

The demand side of the labor market contributes to the gender wage gap through the sorting of women into low-wage firms and through pay-setting behavior which leads some women to be paid less over their careers than their male co-workers. Policies that increase transparency and accountability in managerial decisions are effective in reducing unequal treatment. However, equally important are policies which remove the barriers to combining work with caring responsibilities

DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints