Given the prestige and compensation of science and math-related occupations, the underrepresentation of women and people of color in science, technology, engineering, and mathematics majors (STEM) perpetuates entrenched economic and social inequities. Explanations for this underrepresentation have largely focused on individual characteristics, including uneven academic preparation, as well as institutional factors at the college level. In this article, we focus instead on high schools. We highlight the influence of the intersection between race and gender of female math and science teachers on students' decisions to major in STEM fields. Theoretically, this article extends the political science concept of representative bureaucracy to the issue of women's and disadvantaged minorities' underrepresentation in STEM majors. We analyze longitudinal data from public school students in North Carolina to test whether organizational demography of high school math and science faculty has an association with college major choice and graduation. Using hierarchical probit models with an instrumental-variable approach, we find that young white women are more likely to major in STEM fields and to graduate with STEM degrees when they come from high schools with higher proportions of female math and science teachers, irrespective of the race of the teacher. At the same time, these teachers do not depress young white or African American men's chances of majoring in STEM. Results for African American women are less conclusive, highlighting the limitations of their small sample size.
What factors led to the surprise defeat of the Colombian peace referendum? Initial analyses suggested a link between support for peace and the experience of violence, but economic conditions and political support for incumbent parties also affect electoral outcomes. We use Bayesian hierarchical models to test links between referendum result and previous violence victimization, economic conditions, and support for Centro Democrático (the main party opposed to the peace agreement). There was less support for peace in the Andean region than in other regions, and departments with lower support had higher unemployment and growth in GDP. Support for the opposition was the dominant covariate of decreasing support for the peace accords, while previous violence victimization increased the proportion of votes for peace. In light of these results, regional variation in baseline support for the agreements -a complex variable governed by partisan engagement but also influenced by structural economic factors -will be critical during implementation of the newly revised accords.
Population growth with weak economic development can promote tropical deforestation, but government infrastructure investment can also open new frontiers and thus increase deforestation. In the Andean region of South America, population growth has been a leading explanation for both deforestation and coca cultivation, but coca generates armed conflict and attracts counter-drug measures, obscuring the differences between population-driven and frontier-opening models of deforestation. Using a 15-year panel from Colombia, we model deforestation, coca cultivation, and conflict victims as interrelated responses with a suite of covariates encompassing land cover, land cover changes, population, population changes, counter-drug measures, and government infrastructure spending. Infrastructure spending suppresses coca, coca and eradication by aerial fumigation both increase conflict, and conflict promotes deforestation and is associated with depopulation. But the strongest predictor of deforestation is pasture growth, which covaries with coca. While these models show that infrastructure spending can help reduce coca, and coca's influence on deforestation is indirect and mediated by conflict, the models also reveal the most important challenge to forest conservation is neither coca nor conflict, but an insatiable appetite for land that expresses itself through pasture growth.
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