Project description:This study aims to reveal short-run and long-run asymmetries among human capital, educational inequality, and income inequality in China over the period 1975-2020 using a nonlinear autoregressive distributed lag (NARDL) model. The estimated long-run asymmetry parameters reflect that positive shocks to secondary education (SSE) and higher education (HE) are negatively correlated with income Gini coefficient. The adverse shocks of secondary education (SSE) and higher education (HE) stimulate the Gini coefficient of income, but the effect of secondary education (SSE) on the Gini coefficient of income is not significant, while that of higher education (HE) is significant. The results also highlight that, in the long run, there is a significant asymptotic effect of the education Gini coefficient (educational inequality) and economic growth on the income Gini coefficient (income inequality). However, physical capital stock has a significant adverse effect on income inequality in the long run. Higher education significantly promotes educational inequality, while the square of higher education significantly reduces educational inequality, thus verifying the inverted U-shaped Kuznets curve hypothesis between higher education and educational inequality. Strategically, this study suggests higher education as a powerful tool for mitigating income inequality by emphasizing educational equity.
Project description:In spring 2020, governments around the globe shut down schools to mitigate the spread of the novel coronavirus. We argue that low-achieving students may be particularly affected by the lack of educator support during school closures. We collect detailed time-use information on students before and during the school closures in a survey of 1099 parents in Germany. We find that while students on average reduced their daily learning time of 7.4 h by about half, the reduction was significantly larger for low-achievers (4.1 h) than for high-achievers (3.7 h). Low-achievers disproportionately replaced learning time with detrimental activities such as TV or computer games rather than with activities more conducive to child development. The learning gap was not compensated by parents or schools who provided less support for low-achieving students.
Project description:Humans increasingly rely on artificial intelligence (AI) for efficient and objective decision-making, yet there is increasing concern that algorithms used by modern AI systems produce discriminatory outputs, presumably because they are trained on data in which societal biases are embedded. As a consequence, their use by human decision makers may result in the propagation, rather than reduction, of existing disparities. To assess this hypothesis empirically, we tested the relation between societal gender inequality and algorithmic search output and then examined the effect of this output on human decision-making. First, in two multinational samples (n = 37, 52 countries), we found that greater nation-level gender inequality was associated with more male-dominated Google image search results for the gender-neutral keyword "person" (in a nation's dominant language), revealing a link between societal-level disparities and algorithmic output. Next, in a series of experiments with human participants (n = 395), we demonstrated that the gender disparity associated with high- vs. low-inequality algorithmic outputs guided the formation of gender-biased prototypes and influenced hiring decisions in novel scenarios. These findings support the hypothesis that societal-level gender inequality is recapitulated in internet search algorithms, which in turn can influence human decision makers to act in ways that reinforce these disparities.
Project description:The benefits of schools' closure, used as a containment strategy by many European countries, must be carefully considered against the adverse effects of child wellbeing. In this study, we assessed SARS-CoV-2 seroprevalence, which better estimates the real extent of the infection unraveling asymptomatic cases, among schoolchildren aged 3 to 18 in Milan, using dried blood spot, a safe and extremely viable methods for children, and then compared it between September 2020 and January 2021. Secondly, we evaluated the seroconversion rate and compared it between students attending schools in presence and those switched to distance-learning, using a logistic regression model, both as univariate and multivariate, adjusting for age and biological-sex. Among 1109 pupils, we found a seroprevalence of 2.8% in September before school reopening, while in January 2021, the seropositive rate was 12.5%, reflecting the general growth rate of infections during the second pandemic wave. The overall seroconversion rate was 10%, with no differences based on biological-sex and age groups; we observed no seroreversion. When considered age groups, the seroconversion rate was 10.5% (95%Confidence Interval, 2.9-24.8) among children attending preschools, 10.6% (95%Confidence Interval, 8.2-13.4) for primary schools, 9.9% (95%Confidence Interval, 6.8-13.8) for secondary schools, and 7.8% (95%Confidence Interval, 4-13.2) among high-school students. Interestingly, no differences in seroconversion rate were found between students who attended school compared to those who started remote learning in the first days of November. Furthermore, most patients (61%) reported that the contact occurred within the household. We reported a low seroconversion rate among school children in Milan, with no differences between those who attended from September 2020 to January 2021 compared to those who switched to remote learning in the first days of November. Our data suggest that schools do not amplify SARS-CoV-2 transmission, but rather reflect the level of the transmission in the community.
Project description:We study to what extent schools increase or decrease environmental and genetic influences on educational performance. Building on behavioral genetics literature on gene-environment interactions and sociological literature on the compensating and amplifying effects of schools on inequality, we investigate whether the role of genes and the shared environment is larger or smaller in higher-quality school environments. We apply twin models to Dutch administrative data on the educational performance of 18,384 same-sex and 11,050 opposite-sex twin pairs, enriched with data on the quality of primary schools. Our results show that school quality does not moderate genetic and shared-environmental influences on educational performance once the moderation by SES is considered. We find a gene-environment interplay for school SES: genetic variance decreases with increasing school SES. This school SES effect partly reflects parental SES influences. Yet, parental SES does not account for all the school SES moderation, suggesting that school-based processes play a role too.
Project description:Previous research linking social capital to child nutritional status primarily constitutes cross-sectional studies. To investigate whether a longitudinal relationship exists, by conducting fixed-effects analyses with 16,977 repeatedly measured observations of 6193 children from the 2012, 2014, 2016, and 2018 China Family Panel Studies, this study explored the longitudinal effects of neighborhood participation, bonding trust, and bridging trust on the BMI-for-age z-score (BAZ) and BMI categories of school-aged children, differentiating between urban and rural residence. We found an increasing average BAZ, a decreasing prevalence of underweight, an increasing prevalence of overweight/obesity, and a reducing urban/rural gap in nutritional status. The levels of social capital components descended faster in the urban area. Bonding trust was predictive of a lower BAZ, a higher likelihood of being underweight, and a lower likelihood of being overweight/obese. Bridging trust was predictive of a higher BAZ. The longitudinal effects of bonding trust were significant among only the rural children. Our findings indicate that neighborhood social capital may impose causal impacts on the nutritional status of children. To effectively improve child nutritional status, a more empathetic governmental approach that promotes a more supportive distal social environment is needed.
Project description:BackgroundThousands of school systems have struggled with the decisions about how to deliver education safely and effectively amid the COVID19 pandemic. This study evaluates the public health impact of various school reopening scenarios (when, and how to return to in-person instruction) on the spread of COVID19.MethodsAn agent-based simulation model was adapted and used to project the impact of various school reopening strategies on the number of infections, hospitalizations, and deaths in the state of Georgia during the study period, i.e., February 18th-November 24th, 2020. The tested strategies include (i) schools closed, i.e., all students receive online instruction, (ii) alternating school day, i.e., half of the students receive in-person instruction on Mondays and Wednesdays and the other half on Tuesdays and Thursdays, (iii) alternating school day for children, i.e., half of the children (ages 0-9) receive in-person instruction on Mondays and Wednesdays and the other half on Tuesdays and Thursdays, (iv) children only, i.e., only children receive in-person instruction, (v) regular, i.e., all students return to in-person instruction. We also tested the impact of universal masking in schools.ResultsAcross all scenarios, the number of COVID19-related deaths ranged from approximately 8.8 to 9.9 thousand, the number of cumulative infections ranged from 1.76 to 1.96 million for adults and 625 to 771 thousand for children and youth, and the number of COVID19-related hospitalizations ranged from approximately 71 to 80 thousand during the study period. Compared to schools reopening August 10 with a regular reopening strategy, the percentage of the population infected reduced by 13%, 11%, 9%, and 6% in the schools closed, alternating school day for children, children only, and alternating school day reopening strategies, respectively. Universal masking in schools for all students further reduced outcome measures.ConclusionsReopening schools following a regular reopening strategy would lead to higher deaths, hospitalizations, and infections. Hybrid in-person and online reopening strategies, especially if offered as an option to families and teachers who prefer to opt-in, provide a good balance in reducing the infection spread compared to the regular reopening strategy, while ensuring access to in-person education.
Project description:Hundreds of thousands of students drop out of school each year in the United States, despite billions of dollars of funding and myriad educational reforms. Existing research tends to look at the effect of easily measurable student characteristics. However, a vast number of harder-to-measure student traits, skills, and resources affect educational success. We present a conceptual framework for the cumulative effect of all factors, which we call student capital. We develop a method for estimating student capital in groups of students and find that student capital is distributed exponentially in each of 140 cohorts of community college students. Students' ability to be successful does not behave like standard tests of intelligence. Instead, it acts like a limited resource, distributed unequally. The results suggest that rather than removing barriers related to easily measured characteristics, interventions should be focused on building up the skills and resources needed to be successful in school.
Project description:The use of Internet-based systems for infectious disease surveillance has been increasingly explored in recent years. However, few studies have used Internet search query or social media data to monitor spatial and temporal trends of avian influenza in China. This study investigated the potential of using search query and social media data in detecting and monitoring avian influenza A (H7N9) cases in humans in China. We collected weekly data on laboratory-confirmed H7N9 cases in humans, as well as H7N9-related Baidu Search Index (BSI) and Weibo Posting Index (WPI) data in China from 2013 to 2017, to explore the spatial and temporal trends of H7N9 cases and H7N9-related Internet search queries. Our findings showed a positive relationship of H7N9 cases with BSI and WPI search queries spatially and temporally. The outbreak threshold time and peak time of H7N9-related BSI and WPI searches preceded H7N9 cases in most years. Seasonal autoregressive integrated moving average (SARIMA) models with BSI (β = 0.008, p < 0.001) and WPI (β = 0.002, p = 0.036) were used to predict the number of H7N9 cases. Regression tree model analysis showed that the average H7N9 cases increased by over 2.4-fold (26.8/11) when BSI for H7N9 was > = 11524. Both BSI and WPI data could be used as indicators to develop an early warning system for H7N9 outbreaks in the future.
Project description:Despite growing attention to Internet activity as a social determinant of depression in adolescents, few studies have focused on its diverse effects on depressive symptoms. Using data from the 2020 China Family Panel Study, this study employed logistic regression analysis to examine how Internet activity affects depressive symptoms in adolescents in China. The results indicated that adolescents with longer online duration using mobile phones tended to have higher levels of depression. Adolescents who engaged in online activities related to games, shopping, and entertainment had more severe depressive symptoms, but their time spent on online learning was not significantly associated with their level of depression. These findings suggest a dynamic link between Internet activity and adolescent depression and offer policy implications for addressing depressive symptoms in adolescents. Specifically, Internet and youth development policies and public health programs during the COVID-19 pandemic should be designed based on a comprehensive account of all aspects of Internet activity.