Historically, elite schools have selected students in ways that reproduce advantages for dominant groups and exclude groups deemed undesirable. The specific outgroup in question has changed over time, but the underlying logic used to exclude these groups is often related to disability. Yet, disability as a social category has received minimal attention in discussions of elite reproduction. In this article, we draw on qualitative data collected from elite independent pre-K–12 schools to show that disability is indeed a salient basis of selection into elite educational environments, one that begins at the earliest moments of educational sorting: admission to elite early childhood programs. Through interviews with admissions personnel, we show that elite independent schools explicitly structure their admissions processes to identify—and exclude—children who are perceived as having or being at risk of developing any type of disability, regardless of impairment type or support needs. We argue that admissions practices at elite independent schools (1) serve as a form of social closure intended to restrict enrollment to young children perceived as able-bodied and neurotypical, and (2) represent a case of essentializing merit, in which elite gatekeepers construct merit as an intrinsic, rather than achieved, property of individuals.

Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they and the composite variable PROD=√CAPE×SRH can be used as indicators of severe thunderstorm activity. Their extremal spatial dependence exhibits temporal non-stationarity due to seasonality and large-scale atmospheric signals such as El Niño-Southern Oscillation (ENSO). In order to investigate this, we introduce a space-time model based on a max-stable, Brown–Resnick, field whose range depends on ENSO and on time through a tensor product spline. We also propose a max-stability test based on empirical likelihood and the bootstrap. The marginal and dependence parameters must be estimated separately owing to the complexity of the model, and we develop a bootstrap-based model selection criterion that accounts for the marginal uncertainty when choosing the dependence model. In the case study, the out-sample performance of our model is good. We find that extremes of PROD, CAPE, and SRH are generally more localized in summer and, in some regions, less localized during El Niño and La Niña events, and give meteorological interpretations of these phenomena. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.