ABSTRACT
The COVID-19 pandemic placed new teaching demands upon faculty that may have exacerbated existing race and gender disparities in the amount of emotional labor they perform. The present study surveyed 182 full-time tenured and tenure-track faculty from three small private liberal arts colleges to examine the effect of social and professional statuses on emotional labor (i.e., managing the expression of emotions to meet job requirements) during the emergency switch to remote instruction in spring 2020. Ordinary least squares (OLS) regression revealed that white cisgender men performed less emotional labor than Black, Indigenous, and People of Color (BIPOC) cisgender men, BIPOC cisgender women, and white cisgender women and gender non-conforming (GNC) faculty. Student demands for special favors fully mediated the relationship between intersectional race and gender identity and self-directed emotional labor and partially mediated its relationship with student-directed emotional labor. We conclude that the status shield afforded white cisgender men by their race and gender protected them from student demands that would have required them to engage in as much emotional labor as faculty with other intersectional race and gender identities during the pandemic. We discuss considering differences in emotional labor when making personnel decisions. Supplementary Information: The online version contains supplementary material available at 10.1007/s11199-021-01271-0.
ABSTRACT
The relationships among land use patterns, geology, soil, and major solute concentrations in stream water for eight tributaries of the Kayaderosseras Creek watershed in Saratoga County, NY, were investigated using Pearson correlation coefficients and multivariate regression analysis. Sub-watersheds corresponding to each sampling site were delineated, and land use patterns were determined for each of the eight sub-watersheds using GIS. Four land use categories (urban development, agriculture, forests, and wetlands) constituted more than 99 % of the land in the sub-watersheds. Eleven water chemistry parameters were highly and positively correlated with each other and urban development. Multivariate regression models indicated urban development was the most powerful predictor for the same eleven parameters (conductivity, TN, TP, NO[Formula: see text], Cl(-), HCO(-)3, SO9(2-)4, Na(+), K(+), Ca(2+), and Mg(2+)). Adjusted R(2) values, ranging from 19 to 91 %, indicated that these models explained an average of 64 % of the variance in these 11 parameters across the samples and 70 % when Mg(2+) was omitted. The more common R (2), ranging from 29 to 92 %, averaged 68 % for these 11 parameters and 72 % when Mg(2+) was omitted. Water quality improved most with forest coverage in stream watersheds. The strong associations between water quality variables and urban development indicated an urban source for these 11 water quality parameters at all eight sampling sites was likely, suggesting that urban stream syndrome can be detected even on a relatively small scale in a lightly developed area. Possible urban sources of Ca(2+) and HCO(-)3 are suggested.
