Rapid changes in technology are expected to limit the availability of decent work for millions of people worldwide. This particularly disadvantages socially and economically marginalized job seekers who are already being pushed into lower-wage precarious work with increasing levels of job insecurity. While the number of employment support tools that match job seekers to employers has been growing, marginalized job seekers still significantly rely on physical employment centers that have a track record of supporting the specific needs associated with marginalization and economic constraints. We drew from prior HCI and CSCW literature uncovering the employment and technology-related challenges that marginalized job seekers face and from the Psychology of Working Theory to frame our research questions and results. To complement this prior work, we investigated how employment center staff work with marginalized job seekers and moderate factors to securing decent work. We found in an interview of 21 employment center staff-career advisors and business services coordinators-that they performed significant work to prepare and encourage marginalized job seekers in applying to positions, while also training employers to be more inclusive and openminded. Career advisors worked directly with job seekers to connect them with external resources, provide encouragement, strategize long-term goals, and mitigate feelings of stigma. Business services coordinators worked directly with employers to prepare job positions and employee support programs. Drawing from the expertise of employment centers, we contribute a framework for designing employment support tools that better serve the needs of marginalized job seekers, and outline tangible design implications that complement the support these organizations provide.CCS Concepts: • Human-centered computing → Empirical studies in HCI.
Thermospheric density impacts satellite position and lifetime through atmospheric drag.More accurate specification of thermospheric temperature, a key input to current models such as the High Accuracy Satellite Drag Model, can decrease model density errors. This paper improves the model of Burke et al. (2009) to model thermospheric temperatures using the magnetospheric convective electric field as a driver. In better alignment with Air Force satellite tracking operations, we model the arithmetic mean temperature, T 1/2 , defined by the Jacchia (1977) model as the mean of the daytime maximum and nighttime minimum exospheric temperatures occurring in opposite hemispheres at a given time, instead of the exospheric temperature used by Burke et al. (2009). Two methods of treating the solar ultraviolet (UV) contribution to T 1/2 are tested. Two model parameters, the coupling and relaxation constants, are optimized for 38 storms from 2002 to 2008. Observed T 1/2 values are derived from densities and heights measured by the Gravity Recovery and Climate Experiment satellite. The coupling and relaxation constants were found to vary over the solar cycle and are fit as functions of F 10.7a , the 162 day average of the F 10.7 index. Model results show that allowing temporal UV variation decreased model T 1/2 errors for storms with decreasing UV over the storm period but increased T 1/2 errors for storms with increasing UV. Model accuracy was found to be improved by separating storms by type (coronal mass ejection or co-rotating interaction region). The model parameter fits established will be useful for improving satellite drag forecasts.
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