The Compensating Income Variation of Social Capital

There is a small but growing literature on the determinants of social capital. Most of these studies use a measure of trust to define social capital empirically. In this paper we use three different measures of social capital: the size of the individual’s social network, the extent of their social safety net and membership of unions or associations. A second contribution to the literature is that we analyze what social capital contributes to our well-being. Based on this, we calculate the compensating income variation of social capital. We find differences in social capital when we differentiate according to individual characteristics such as education, age, place of residence, household composition, and health. Household income generally has a statistically significant effect. We find a significant effect of social capital on life satisfaction. Consequently, the compensating income variation of social capital is substantial.social capital, life satisfaction

Accuracy of different machine learning algorithms and added-value of predicting aggregated-level energy performance of commercial buildings

As with many other sectors, to improve the energy performance and energy neutrality requirements of individual buildings and groups of buildings, built environment is also making use of machine learning for improved energy demand predictions. The goal of achieving energy neutrality through maximized use of on-site produced renewable energy and attaining optimal level of energy performance at building-cluster level requires reliable short term (resolution shorter than one day) energy demand predictions. However, the prediction and analysis of the energy performance of buildings is still focused on the individual building level and not on small neighborhood scale or building clusters. In a smart grid context, to better understand electricity consumption at different spatial levels, prediction should be at both individual as well as at building-cluster levels, especially for neighborhoods with definite boundaries (such as universities, hospitals). Therefore, in this paper, using data from 47 commercial buildings, a number of machine learning algorithms were evaluated to predict the electricity demand at individual building level and aggregated level in hourly intervals. Predicting at hourly granularity is important to understand short-term dynamics, yet most of the neighborhood scale studies are limited to yearly, monthly, weekly, or daily data resolutions. Two years of data were used in training the model and the prediction was performed using another year of untrained data. Learning algorithms such as; boosted-tree, random forest, SVM-linear, quadratic, cubic, fine-Gaussian as well as ANN were all analysed and tested for predicting the electricity demand of individual and groups of buildings. The results showed that boosted-tree, random forest, and ANN provided the best outcomes for prediction at hourly granularity when metrics such as computational time and error accuracy are compared.</p

The Flamingo Test:A new diagnostic instrument for dyslexia in Dutch higher education students

In this study, we present a new diagnostic test for dyslexia, called the Flamingo Test, inspired by the French Alouette Test. The purpose of the test is to measure students' word decoding skills and reading fluency by means of a grammatically correct but meaningless text. Two experiments were run to test the predictive validity of the Flamingo Test. In the first experiment, we compared reading times, error rates and, sensitivity and specificity of the Flamingo Test for samples of students with and without dyslexia. In the second experiment, we compared performance on the Flamingo Test with reading performance on two Dutch standard word reading tests: the Leestest Een Minuut voor Studenten (LEMs; 'one-minute word reading test for students') and the Klepel, a one-minute pseudo-word reading test. Again, students with dyslexia and matched non-dyslexic students were included. Our results show that sensitivity and specificity, as well as the positive predictive value (PPV), of the Flamingo Test are high, with even slightly higher PPVs for the Flamingo Test than for LEMs and Klepel. Together with the fact that the test is short and easy to administer, we believe that the Flamingo Test is a valuable new diagnostic instrument to assess reading skills

Overeducation in the labor market: a meta-analysis.

Abstract This paper contains a meta-analysis of studies on overeducation and undereducation in the labor market. It is found that of the four different definitions of overeducation distinguished in the literature, only the one based on variation in years of education within occupational groups appears to yield significantly lower-than-average rates of overeducation. The average rate of undereducation in the labor market depends on the definition of the undereducation variable. There is no indication that mismatches between education supplied and education required for the job have increased significantly in the past 20 years. The labor force growth rate has a positive effect on the incidence of overeducation, while the unemployment rate has a negative effect on the rate of return to education

UvA-DARE (Digital Academic Repository) THE EFFECTS OF EDUCATION ON CRIME

Abstract In this paper we use a unique data-set on criminal behavior to analyze the effects of education on offences and crimes committed. The findings suggest that substantial savings on the social costs of crime can be obtained by investing in education. We find that the probability of committing crimes like shop lifting, vandalism and threat, assault and injury decrease with years of education. The probability of committing tax fraud, however, increases with years of education. We further find that higher educated people have more permissive attitudes and social norms towards criminal behavior

Dynamic assessment of the effectiveness of digital game-based literacy training in beginning readers: a cluster randomised controlled trial

In this article, we report on a study evaluating the effectiveness of a digital game-based learning (DGBL) tool for beginning readers of Dutch, employing active (math game) and passive (no game) control conditions. This classroom-level randomized controlled trial included 247 first graders from 16 classrooms in the Netherlands and the Dutch-speaking part of Belgium. The intervention consisted of 10 to 15 min of daily playing during school time for a period of up to 7 weeks. Our outcome measures included reading fluency, phonological skills, as well as purpose built in-game proficiency levels to measure written lexical decision and letter speech sound association. After an average of 28 playing sessions, the literacy game improved letter knowledge at a scale generalizable for all children in the classroom compared to the two control conditions. In addition to a small classroom wide benefit in terms of reading fluency, we furthermore discovered that children who scored high on phonological awareness prior to training were more fluent readers after extensive exposure to the reading game. This study is among the first to exploit game generated data for the evaluation of DGBL for literacy interventions

Dynamic assessment of the effectiveness of digital game-based literacy training in beginning readers:a cluster randomised controlled trial

In this article, we report on a study evaluating the effectiveness of a digital game-based learning (DGBL) tool for beginning readers of Dutch, employing active (math game) and passive (no game) control conditions. This classroom-level randomized controlled trial included 247 first graders from 16 classrooms in the Netherlands and the Dutch-speaking part of Belgium. The intervention consisted of 10 to 15 min of daily playing during school time for a period of up to 7 weeks. Our outcome measures included reading fluency, phonological skills, as well as purpose built in-game proficiency levels to measure written lexical decision and letter speech sound association. After an average of 28 playing sessions, the literacy game improved letter knowledge at a scale generalizable for all children in the classroom compared to the two control conditions. In addition to a small classroom wide benefit in terms of reading fluency, we furthermore discovered that children who scored high on phonological awareness prior to training were more fluent readers after extensive exposure to the reading game. This study is among the first to exploit game generated data for the evaluation of DGBL for literacy interventions

Growth phase of orally administered Lactobacillus strains differentially affects IgG1/IgG2a ratio for soluble antigens: Implications for vaccine development

Lactobacillus strains with probiotic activity are major constituents of numerous common food products. Due to their 'generally regarded as safe'-status (GRAS-status), Lactobacillus strains can also be genetically engineered for use in oral immunotherapeutic applications, such as vaccination and T lymphocyte tolerance induction in autoimmune disease. In the current study, we demonstrate that the growth phase of orally administered individual Lactobacillus strains can differentially affect antigen-specific antibody subclasses IgG1 and IgG2a, which might reflect skewing of systemic activity of T helper cell type 2 (Th2) and T helper cell type 1 (Th1) pathways, respectively. Mice were orally fed different wild type Lactobacillus strains in log phase or stationary phase and immunized intraperitoneally with a T-cell dependent protein antigen. Sera were evaluated for the ratio of antigen-specific IgG1 and IgG2a antibodies. Stationary Lactobacillus murines and Lactobacillus casei cultures, but not two other Lactobacillus strains, evoked significantly higher IgG1/IgG2a ratios than log phase cultures, possibly relating to increased activity of the Th2-pathway. Despite normal variation in antibody responses against TNP-CGG among individual mice, a high correlation was found between the IgG1 and IgG2a responses of mice within experimental groups. This differential antibody response is likely due to growth phase-dependent differences in bacterial cell composition. Since Lactobacillus growth phase dependent skewing of antibody responses possibly reflecting T-cell pathways can inadvertently affect allergic and (auto)-immune responses, the current findings strongly caution against unidimensional views on the oral administration of individual Lactobacillus strains for probiotic or immunotherapeutic purposes, but also suggest additional possibilities for immune modulation

The Peruvian teacher in-service training program and its effects on student achievement

This paper assesses the impact of the Peruvian Ministry of Education teacher in-service training program (henceforth the program) on student achievement. Given the importance the Ministry attaches to interventions to strengthen teaching practices since 2008, it is relevant to know whether its impact supports a wider application to public schools nationwide. Using annual data from the Student Evaluation Census-ECE- and from other official datasets for 2014, and a matching technique (Propensity Score Matching) to control for differences between beneficiaries, we estimate the impact of the program on students Math & Reading comprehension both for full-grade and multigrade schools. Results show that there is a positive and significant effect of the teacher training program on both Math and Reading achievement, but the magnitude of the effect differs. We find larger effects on Reading comprehension than on Math and in both topics larger effects for full-grade schools than for multigrade ones (the last are mostly found in rural areas). This might be related to the characteristics of the training in Reading comprehension: it is focused on learning pedagogical techniques (e.g. how to develop the curriculum within the classroom, how to motivate students, etc) instead of content knowledge, more focused on explaining mathematical problems. A sensitivity analysis complements and supports the results. This paper also assesses whether the program is cost-effective. Comparisons with different programs, all of them related with the educational sector in Peru make us believe that it is worth implementing the program at a national level

Measuring Diversity in Higher Education Institutions: A Review of Literature and Empirical Approaches

This paper reviews studies on diversity in higher education institutions and suggests empirical approaches to measure diversity. “Diversity” in this paper refers to the internal and external differences among academic programs and institutions. As the empirical literature is relatively salient about how to measure diversity in higher education, the study suggests and compares the use of the Herfindhal index, Gini coefficient, Theil entropy index and the Birnbaum (1983) measure. Applying the indices to data on Dutch higher education, the results indicate limited diversity between institutions, disciplines, and bachelor’s programs. The diversity at the master’s program and first year bachelor’s program levels increased between 2008 and 2013