Undocumented Educations: Everyday Educational Practices of Recently Immigrated Youth Beyond Inclusion/exclusion

Undocumented educations are those educational practices falling outside of legitimated educational institutions or appearing only in marginalized, liminal ways. Through resisting, conflicting with, or simply not fitting into the grammar of school they do not “count” as education. Those educations, and thus the everyday lives of those who practice them, are routinely placed “at-risk.” Often, policymakers and educators propose reforms to this issue, aiming to more effectively include or ensure stronger academic outcomes for populations of students whose educational lives have been marked in precarious ways. Working with 9 recently immigrated youth in New York City, this project explores such undocumented educations in youth’s everyday lives in order to open new understandings of what counts, who counts, and in what ways, in educational discourses. Rather than joining the chorus of reform efforts, I listen to the rigorous, wild, and ethereal educational practices already present in youth’s lives. This project takes up entangled methods of an affective ethnography and a history of the present. Historical work explores prevalent discourses around the education of “newcomer” youth to interrogate how this educational truth came to flourish as an intervention for newcomer youth. Affective ethnography, meanwhile, moves through many places exploring sensations, intensities, and encountering everyday educations and their relationship to the educational life of the school. An affective ethnography opens space to work with youth in exploring educations largely illegible to dominant discourses without submitting these educational practices to new forms of control. Results suggest that linguistically and culturally affirmative schools emerge from understandings of how to better include and improve outcomes for newcomer youth. At the same time, political shifts require schools to constantly evolve to continue pursuing these ideas. Youths’ educational practices change and move through spaces like school or afterschool programs but also connect and flow in a borderless curriculum that challenges the supremacy of educational projects built dominantly on inclusion and success. Failure, daydreaming, and experimentation all play critical roles in youth’s everyday lives. The project ultimately concludes that listening to the already-present everyday educational practices of immigrant youth makes a radically different, ungoverned educational otherwise possible

Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations

Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent observations from other sites to inform focal sites. In this paper, we evaluate two different DL model structures, a long short-term memory neural network (LSTM) and a recurrent graph convolutional neural network (RGCN), both with and without data assimilation for forecasting daily maximum stream temperature 7 days into the future at monitored and unmonitored locations in a 70-segment stream network. All our DL models performed well when forecasting stream temperature as the root mean squared error (RMSE) across all models ranged from 2.03 to 2.11°C for 1-day lead times in the validation period, with substantially better performance at gaged locations (RMSE = 1.45–1.52°C) compared to ungaged locations (RMSE = 3.18–3.27°C). Forecast uncertainty characterization was near-perfect for gaged locations but all DL models were overconfident (i.e., uncertainty bounds too narrow) for ungaged locations. Our results show that the RGCN with data assimilation performed best for ungaged locations and especially at higher temperatures (>18°C) which is important for management decisions in our study location. This indicates that the networked model structure and data assimilation techniques may help borrow information from nearby monitored sites to improve forecasts at unmonitored locations. Results from this study can help guide DL modeling decisions when forecasting other important environmental variables

Sushi in the United States, 1945-1970

Sushi first achieved widespread popularity in the United States in the mid-1960s. Many accounts of sushi’s US establishment foreground the role of a small number of key actors, yet underplay the role of a complex web of large-scale factors that provided the context in which sushi was able to flourish. This article critically reviews existing literature, arguing that sushi’s US popularity arose from contingent, long-term, and gradual processes. It examines US newspaper accounts of sushi during 1945–1970, which suggest the discursive context for US acceptance of sushi was considerably more propitious than generally acknowledged. Using California as a case study, the analysis also explains conducive social and material factors, and directs attention to the interplay of supply- and demand-side forces in the favorable positioning of this “new” food. The article argues that the US establishment of sushi can be understood as part of broader public acceptance of Japanese cuisine

Professional interventions for general practitioners on the management of musculoskeletal conditions

BACKGROUND: Musculoskeletal conditions require particular management skills. Identification of interventions which are effective in equipping general practitioners (GPs) with such necessary skills could translate to improved health outcomes for patients and reduced healthcare and societal costs. OBJECTIVES: To determine the effectiveness of professional interventions for GPs that aim to improve the management of musculoskeletal conditions in primary care. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), 2010, Issue 2; MEDLINE, Ovid (1950 - October 2013); EMBASE, Ovid (1980 - Ocotber 2013); CINAHL, EbscoHost (1980 - November 2013), and the EPOC Specialised Register. We conducted cited reference searches using ISI Web of Knowledge and Google Scholar; and handsearched selected issues of Arthritis and Rheumatism and Primary Care-Clinics in Office Practice. The latest search was conducted in November 2013. SELECTION CRITERIA: We included randomised controlled trials (RCTs), non-randomised controlled trials (NRCTs), controlled before-and-after studies (CBAs) and interrupted time series (ITS) studies of professional interventions for GPs, taking place in a community setting, aiming to improve the management (including diagnosis and treatment) of musculoskeletal conditions and reporting any objective measure of GP behaviour, patient or economic outcomes. We considered professional interventions of any length, duration, intensity and complexity compared with active or inactive controls. DATA COLLECTION AND ANALYSIS: Two review authors independently abstracted all data. We calculated the risk difference (RD) and risk ratio (RR) of compliance with desired practice for dichotomous outcomes, and the mean difference (MD) and standardised mean difference (SMD) for continuous outcomes. We investigated whether the direction of the targeted behavioural change affects the effectiveness of interventions. MAIN RESULTS: Thirty studies met our inclusion criteria.From 11 studies on osteoporosis, meta-analysis of five studies (high-certainty evidence) showed that a combination of a GP alerting system on a patient's increased risk of osteoporosis and a patient-directed intervention (including patient education and a reminder to see their GP) improves GP behaviour with regard to diagnostic bone mineral density (BMD) testing and osteoporosis medication prescribing (RR 4.44; (95% confidence interval (CI) 3.54 to 5.55; 3 studies; 3,386 participants)) for BMD and RR 1.71 (95% CI 1.50 to 1.94; 5 studies; 4,223 participants) for osteoporosis medication. Meta-analysis of two studies showed that GP alerting on its own also probably improves osteoporosis guideline-consistent GP behaviour (RR 4.75 (95% CI 3.62 to 6.24; 3,047 participants)) for BMD and RR 1.52 (95% CI 1.26 to 1.84; 3.047 participants) for osteoporosis medication) and that adding the patient-directed component probably does not lead to a greater effect (RR 0.94 (95% CI 0.81 to 1.09; 2,995 participants)) for BMD and RR 0.93 (95% CI 0.79 to 1.10; 2,995 participants) for osteoporosis medication.Of the 10 studies on low back pain, seven showed that guideline dissemination and educational opportunities for GPs may lead to little or no improvement with regard to guideline-consistent GP behaviour. Two studies showed that the combination of guidelines and GP feedback on the total number of investigations requested may have an effect on GP behaviour and result in a slight reduction in the number of tests, while one of these studies showed that the combination of guidelines and GP reminders attached to radiology reports may result in a small but sustained reduction in the number of investigation requests.Of the four studies on osteoarthritis, one study showed that using educationally influential physicians may result in improvement in guideline-consistent GP behaviour. Another study showed slight improvements in patient outcomes (pain control) after training GPs on pain management.Of three studies on shoulder pain, one study reported that there may be little or no improvement in patient outcomes (functional capacity) after GP education on shoulder pain and injection training.Of two studies on other musculoskeletal conditions, one study on pain management showed that there may be worse patient outcomes (pain control) after GP training on the use of validated assessment scales.The 12 remaining studies across all musculoskeletal conditions showed little or no improvement in GP behaviour and patient outcomes.The direction of the targeted behaviour (i.e. increasing or decreasing a behaviour) does not seem to affect the effectiveness of an intervention. The majority of the studies did not investigate the potential adverse effects of the interventions and only three studies included a cost-effectiveness analysis.Overall, there were important methodological limitations in the body of evidence, with just a third of the studies reporting adequate allocation concealment and blinded outcome assessments. While our confidence in the pooled effect estimate of interventions for improving diagnostic testing and medication prescribing in osteoporosis is high, our confidence in the reported effect estimates in the remaining studies is low. AUTHORS' CONCLUSIONS: There is good-quality evidence that a GP alerting system with or without patient-directed education on osteoporosis improves guideline-consistent GP behaviour, resulting in better diagnosis and treatment rates.Interventions such as GP reminder messages and GP feedback on performance combined with guideline dissemination may lead to small improvements in guideline-consistent GP behaviour with regard to low back pain, while GP education on osteoarthritis pain and the use of educationally influential physicians may lead to slight improvement in patient outcomes and guideline-consistent behaviour respectively. However, further studies are needed to ascertain the effectiveness of such interventions in improving GP behaviour and patient outcomes

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Schools of the Walking Dead: Schools, Societies, Smartness, and Educational Sanctuary

Through a close reading of a moment of schooling in The Walking Dead, this paper explores the relationship between school and society. It engages with shifting notions of smartness and raises questions of why schools both change and stay the same. Ultimately, the paper turns to see the possibilities that emerge from school as a place of refuge