Precarious Work Schedules as a Source of Economic Insecurity and Institutional Distrust

Work schedules may fuel precariousness among U.S. workers by undermining perceptions of security, both economic and societal. Volatile hours, limited schedule input, and short advance notice are all dimensions of precarious work schedules. Our analyses suggest that scheduling practices that introduce instability and unpredictability into workers’ lives undermine perceptions of security in unique ways for hourly and salaried workers. Although the data suggest that precarious scheduling practices are widespread in the labor market, workers who are black, young, and without a college degree appear to be at highest risk. The findings highlight the importance of examining constellations of scheduling practices and considering the direction of work-hour fluctuations when investigating the ramifications of today’s scheduling practices for quality of employment and quality of life

DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.Comment: Accepted at JBI under the new name: "Predicting healthcare trajectories from medical records: A deep learning approach

Policy Recommendations for Meeting the Grand Challenge to Reduce Extreme Economic Inequality

This brief was created forSocial Innovation for America’s Renewal, a policy conference organized by the Center for Social Development in collaboration with the American Academy of Social Work & Social Welfare, which is leading theGrand Challenges for Social Work initiative to champion social progress. The conference site includes links to speeches, presentations, and a full list of the policy briefs

Toward a client-centered benchmark for self-sufficiency: Evaluating the ‘process’ of becoming job ready.

The purpose of this study is to evaluate how service providers, clients, and graduates of a job training program define the term self-sufficiency (SS). This community-engaged, mixed method study qualitatively analyzes focus group data from each group and quantitatively examines survey data obtained from participants of the program. Findings reveal that psychological transformation as a ‘process’ represents the emic definition of SS—psychological SS—but each dimension of the concept is reflected in varying degrees by group. Provider and participant views are vastly different from the outcome-driven policy and funder definitions. Implications for benchmarking psychological SS as an empowerment-based ‘process’ measure of job readiness in workforce development evaluation are discussed

Online clinical reasoning assessment with the Script Concordance test: a feasibility study

BACKGROUND: The script concordance (SC) test is an assessment tool that measures capacity to solve ill-defined problems, that is, reasoning in context of uncertainty. This tool has been used up to now mainly in medicine. The purpose of this pilot study is to assess the feasibility of the test delivered on the Web to French urologists. METHODS: The principle of SC test construction and the development of the Web site are described. A secure Web site was created with two sequential modules: (a) The first one for the reference panel (n = 26) with two sub-tasks: to validate the content of the test and to elaborate the scoring system; (b) The second for candidates with different levels of experience in Urology: Board certified urologists, residents, medical students (5 or 6(th )year). Minimum expected number of participants is 150 for urologists, 100 for residents and 50 for medical students. Each candidate is provided with an individual access code to this Web site. He/she may complete the Script Concordance test several times during his/her curriculum. RESULTS: The Web site has been operational since April 2004. The reference panel validated the test in June of the same year during the annual seminar of the French Society of Urology. The Web site is available for the candidates since September 2004. In six months, 80% of the target figure for the urologists, 68% of the target figure for the residents and 20% of the target figure for the student passed the test online. During these six months, no technical problem was encountered. CONCLUSION: The feasibility of the web-based SC test is successful as two-thirds of the expected number of participants was included within six months. Psychometric properties (validity, reliability) of the test will be evaluated on a large scale (N = 300). If positive, educational impact of this assessment tool will be useful to help urologists during their curriculum for the acquisition of clinical reasoning skills, which is crucial for professional competence

Delivering Sustained, Coordinated, and Integrated Observations of the Southern Ocean for Global Impact

The Southern Ocean is disproportionately important in its effect on the Earth system, impacting climatic, biogeochemical, and ecological systems, which makes recent observed changes to this system cause for global concern. The enhanced understanding and improvements in predictive skill needed for understanding and projecting future states of the Southern Ocean require sustained observations. Over the last decade, the Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities. These networks support delivery of the SOOS 20-year vision, which is to develop a circumpolar system that ensures time series of key variables, and delivers the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress toward sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40°S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables, and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths \u3e2000 m, the air-ocean-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology, two-way platform interrogation and data-transmission technologies, modeling frameworks, intercalibration experiments, and development of internationally agreed sampling standards and requirements of key variables. This paper presents a community statement on the major scientific and observational progress of the last decade, and importantly, an assessment of key priorities for the coming decade, toward achieving the SOOS vision and delivering essential data to all end-users