1,582 research outputs found

    Peer Ethnicity and Achievement: a Meta-analysis Into the Compositional Effect

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    This study reports a meta-analysis on the effects of ethnic minority share in school on achievement test scores. Best evidence from the studies that have appeared thus far on this topic shows that these compositional effects appear small in general, but may be larger when the ethnic minority group is African Americans in the USA, than when the minority group consists of immigrants. A high share of students from an ethnic minority group seems to affect the achievement from students belonging to the same ethnic group more, than the achievement of students belonging to the ethnic majority or to other ethnic minority groups. Effects of the share of immigrants on test scores of ethnic majority students even seem to be close to zero. Several robustness checks confirm our results. The review concludes with a discussion of implications for research and policy practice.academic achievement, meta-analysis, racial composition, school segregation, ethnic groups

    The effect of peer socioeconomic status on student achievement: a meta-analysis

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    Previous studies on the effects on students' test scores of their peers' socioeconomic status (SES) reported varying results. A meta-regression analysis including 30 studies on the topic shows that the compositional effect that researchers find is strongly related to how they measure SES and to their model choice. If they measure SES dichotomously (e.g. free lunch eligibility) or include several average SES-variables in one model, they find smaller effects than when using a composite that captures several SES-dimensions. Composition measured at cohort/school level is associated with smaller effects than composition measured at class level. Researchers estimating compositional effects without controlling for prior achievement or not taking into account the potential for omitted variables bias, risk overestimating the effect. Correcting for a large set of not well thought-over covariates may lead to an underestimation of the compositional effect, by artificially explaining away the effect. Little evidence was found that effect sizes differ with sample characteristics such as test type (language vs. math) and country. Estimates for a hypothetical study, making a number of "ideal" choices, suggest that peer SES may be an important determinant of academic achievement.

    Racial discrimination in the sharing economy:Evidence from Airbnb markets across the world

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    Online peer-to-peer platforms aim to reduce anonymity and increase trust by displaying personal information about sellers. However, consumers may also rely on the names and profile photos of sellers to avoid sellers from certain social groups. Here we analyze more than 100,000 Airbnb rentals to test whether consumers discriminate against hosts from racial minorities. If consumers prefer to stay with a White host, then hosts from racial minorities should be able to charger lower prices for similar rentals. In Study 1, we analyzed 96,150 Airbnb listings across 24 cities, 14 countries, and 3 continents and found that non-White hosts charge 2.74% lower prices for qualitatively similar rentals. In Study 2, a preregistered analysis of 12,648 listings across 14 cities in the United States showed that, compared to White hosts, Black hosts charge 7.39% lower prices and Asian hosts charge 5.94% lower prices. Even though the magnitude of the price penalties varied, they emerged consistently across most cities. In sum, the current findings suggest that there is widespread discrimination against Airbnb hosts from racial minorities

    Understanding Alzheimer Disease at the interface between genetics and transcriptomics

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    Over 25 genes are known to affect the risk of developing Alzheimer disease (AD), the most common neurodegenerative dementia. However, mechanistic insights and improved disease management remains limited, due to difficulties in determining the functional consequences of genetic associations. Transcriptomics is increasingly being used to corroborate or enhance interpretation of genetic discoveries. These approaches, which include second and third generation sequencing, single-cell sequencing, and bioinformatics, reveal allele-specific events connecting AD risk genes to expression profiles, and provide converging evidence of pathophysiological pathways underlying AD. Simultaneously, they highlight brain region- and cell-type-specific expression patterns, and alternative splicing events that affect the straightforward relation between a genetic variant and AD, re-emphasizing the need for an integrated approach of genetics and transcriptomics in understanding AD. © 2018 The Author
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