Search

States' annual testing data for spring 2021 showed that unfinished learning in the wake of COVID-19 is most pronounced--and most troubling--in math. In Texas, nearly 40 percent of students failed the state's math exam in 2021. In Indiana, only 37 percent were proficient in math, down from 48 percent in 2019. Many states saw similar results. What makes the results such a cause for alarm is the sequential nature of math learning. Math skills build like a staircase. Should math teachers deliver grade-level content to students, knowing they lack the prerequisite skills and concepts to thrive? Or should she remediate by teaching the entire class fourth-grade material, which potentially robs students of the chance to outperform expectations? These questions plagued educators long before COVID-19. But given what test results say about unfinished learning, particularly in math, the need for answers is even more urgent.

This article explores how the concept of emotional labour has moved from sociological into lay discourse as a case study of the double hermeneutic and concept creep, demonstrating the effect sociological concepts can have on lay actors' understanding of their everyday lives. From an analysis of 41 news and magazine articles about emotional labour, we identify the various meanings the term carries as well as the ideologies and logics that underpin them. The concept has become a tool used to frame discussions around gender inequalities in unpaid work, including housework, emotion work, and providing support. However, the Marxist underpinnings of the original concept have been subverted within a lay discourse that is largely reflective of a liberal feminist and neoliberal ethos. [ABSTRACT FROM AUTHOR]

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physico-chemical properties, which far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth System Models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy as invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work, we introduce an explicit mineralogy representation within the state-of-the-art atmosphere-chemistry model MONARCH. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modelling, and provide an evaluation of multi-annual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on Brittle Fragmentation Theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions, independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semiarid regions worldwide. For the least abundant or more difficult to determine minerals, such as the iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes a ∼10 % of the emitted dust mass at the global scale, and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single scattering albedo at solar wavelengths, or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high quality spaceborne hyperspectral measurements, such as those arising from the NASA EMIT mission. [ABSTRACT FROM AUTHOR]