Spillovers from immigrant diversity in cities

Using comprehensive longitudinal matched employer-employee data for the U.S., this paper provides new evidence on the relationship between productivity and immigration-spawned urban diversity. Existing empirical work has uncovered a robust positive correlation between productivity and immigrant diversity, supporting theory suggesting that diversity acts as a local public good that makes workers more productive by enlarging the pool of knowledge available to them, as well as by fostering opportunities for them to recombine ideas to generate novelty. This paper makes several empirical and conceptual contributions. First, it improves on existing empirical work by addressing various sources of potential bias, especially from unobserved heterogeneity among individuals, work establishments, and cities. Second, it augments identification by using longitudinal data that permits examination of how diversity and productivity co-move. Third, the paper seeks to reveal whether diversity acts upon productivity chiefly at the scale of the city or the workplace. Findings confirm that urban immigrant diversity produces positive and nontrivial spillovers for U.S. workers. This social return represents a distinct channel through which immigration generates broad-based economic benefits

Cross validation for the classical model of structured expert judgment

We update the 2008 TU Delft structured expert judgment database with data from 33 professionally contracted Classical Model studies conducted between 2006 and March 2015 to evaluate its performance relative to other expert aggregation models. We briefly review alternative mathematical aggregation schemes, including harmonic weighting, before focusing on linear pooling of expert judgments with equal weights and performance-based weights. Performance weighting outperforms equal weighting in all but 1 of the 33 studies in-sample. True out-of-sample validation is rarely possible for Classical Model studies, and cross validation techniques that split calibration questions into a training and test set are used instead. Performance weighting incurs an “out-of-sample penalty” and its statistical accuracy out-of-sample is lower than that of equal weighting. However, as a function of training set size, the statistical accuracy of performance-based combinations reaches 75% of the equal weight value when the training set includes 80% of calibration variables. At this point the training set is sufficiently powerful to resolve differences in individual expert performance. The information of performance-based combinations is double that of equal weighting when the training set is at least 50% of the set of calibration variables. Previous out-of-sample validation work used a Total Out-of-Sample Validity Index based on all splits of the calibration questions into training and test subsets, which is expensive to compute and includes small training sets of dubious value. As an alternative, we propose an Out-of-Sample Validity Index based on averaging the product of statistical accuracy and information over all training sets sized at 80% of the calibration set. Performance weighting outperforms equal weighting on this Out-of-Sample Validity Index in 26 of the 33 post-2006 studies; the probability of 26 or more successes on 33 trials if there were no difference between performance weighting and equal weighting is 0.001

U.S. wage inequality and low-wage import competition

This article examines the impact of import competition from low-wage countries (LWCs) on wages and wage inequality in the U.S. over the period 1972-2006. During the 1990s, studies appeared to settle this issue, finding that technology, not trade, accounted for the bulk of rising inequality. This paper revisits the link between trade and wages, motivated by two changes in the structure of trade. First, trade today is shaped as much by the exchange of components and tasks as finished goods. Second, import volumes from LWCs into advanced economies like the U.S. have risen dramatically since the early 1990s. The paper pays special attention to the timing of trade impacts. Consistent with prior work, it shows that technological change is the primary driver of inequality before 1990. However, after 1990 wage inequality growth is chiefly a function of rising import competition from low-wage economies. To account for the growing fragmentation of production within economic sectors, we explore trade impacts using a panel model where the focus in on within- rather than between-industry shifts in inequality. Lags of key variables are used as instruments, and our results appear robust to broad concerns with endogeneity and to different measures of skill-biased technological chang

Beyond resilience: Moving from self-care to collective care

During the 2020-2021 academic year, which occurred during the COVID-19 pandemic, library and information science (LIS) faculty, scholars, practitioners, and students were all forced into new ways of being, learning, and working with communities who were also unsure and at risk. The abruptness and uncertainties of the global crisis, compounded by racial unrest and economic decline, shone the harshest of lights on many pre-existing societal inequities and conditions in libraries (e.g., racism, the digital divide, and staffing hierarchies), and sharply exacerbated them. This new reality produced inordinate amounts of stress and introduced new mental health challenges for many in the LIS profession. There are countless stories and anecdotes of LIS professionals being encouraged to practice self-care in an effort to cope with these challenging circumstances and times; do yoga, take a bubble bath, take a nap, etc. These practices are not inherently bad; however, they have become commodified, they place the onus on the individuals who are suffering, and they do nothing to address or rectify the systemic professional barriers and inequities that are part and parcel of the stressors being experienced. Instead of expecting individuals to “buck up,” demonstrate “grit,” and correct the larger systemic environmental issues themselves, the onus should be on the profession and its organizations to engage in collective care. “Collective care refers to seeing members’ well-being – particularly their emotional health – as a shared responsibility of the group rather than the lone task of an individual” (Mehreen & Gray-Donald, 2018). LIS and its entities should be focused on healing and improving themselves holistically and rectifying the issues that symptomatically affect its constituents. The solution is not to demand that people be resilient; the solution is to create healthy environments and demonstrate empathy and compassion towards the people who keep the organizations running. To this end, The Skillset Podcast (a production of The University of South Carolina and Publishers Weekly) dedicated its Spring 2021 episodes to the topic of Collective Care (as opposed to self-care). Collective care references the idea of caring for each other in addition to the self-care that we need to engage in for ourselves. Guests were asked: How, if at all, does collective care show up in the work that you do in your libraries and organizations? What became clear in all of the episodes is that self-care is not enough; in fact, relying solely on self-care can be damaging because it doesn’t fully address individuals’ stressors and because it does not address underlying issues, the problems remain. And when the problems remain, individuals banking on the wonders of self-care are left disappointed, frustrated, and feeling as though they continue to fail themselves and their organizations. Additionally, many are unaware of collective care and therefore don’t know to expect it from their organizations or how to ask for, or work towards, this kind of environment. Collective care can be expressed in a variety of community specific ways, and its beneficial effects extend to the larger communities being served by said organizations and staff. This panel session will feature the podcast host and three of the season’s guests who will discuss their opinions of self-care and collective care and share their thoughts about how they believe the LIS profession can improve in this regard and take better care of its most important assets - the people in the profession. Panelists: Nicole Cooke is the Augusta Baker Endowed Chair and an Associate Professor at the University of South Carolina. Her research and teaching interests include human information behavior, critical cultural information studies, and diversity and social justice in librarianship. She was the 2019 ALISE Excellence in Teaching Award recipient, and she is a cohost of The Skillset Podcast. Abigail Phillips is an Assistant Professor in the School of Information Studies at the University of Wisconsin-Milwaukee, where her research interests include cyberbullying, youth, social media, empathy, librarianship, libraries, making, critical librarianship, neurodiversity, and mental health advocacy. Abigail is a member of the #LISMentalHealth team. The #LISMentalHealth initiative aims to raise awareness of mental health among library and archives workers through online discussions, blog posts, resource-sharing, and the “Reserve and Renew Zine” series. Cory Eckert is a private school librarian in Houston, TX. She received her MLIS from the University of Arizona and has worked in college, public, and public school libraries over the course of her career. She founded Storytime Underground. Kaetrena Davis Kendrick is Dean of Ida Jane Dacus Library and Louise Pettus Archives & Special Collections at Winthrop University (SC). Her research interests include professionalism, ethics, racial and ethnic diversity in the LIS field, and the role of communities of practice in practical academic librarianship. In 2019 she was named the Association of College & Research Libraries’ (ACRL) Academic/Research Librarian of the Year for her research into the phenomenon of low morale which quantifies the experiences of many academic librarians who are not getting the support that they need for success in the field. Taking a deeper dive into the subject, Kendrick has now documented behavior and cultures that specifically enable the low morale experiences of racial and ethnic minority academic librarians. Mehreen, R., & Gray-Donald, D. (2018, August 18). Be careful with each other. Retrieved March 10, 2021, from https://briarpatchmagazine.com/articles/view/be-careful-with-each-othe

Expert elicitation : using the classical model to validate experts' judgments

The inclusion of expert judgments along with other forms of data in science, engineering, and decision making is inevitable. Expert elicitation refers to formal procedures for obtaining and combining expert judgments. Expert elicitation is required when existing data and models cannot provide needed information. This makes validating expert judgements a challenge because they are used when other data do not exist, and thus measuring their accuracy is difficult. This article examines the Classical Model of structured expert judgment, which is an elicitation method that includes validation of the experts' assessments against empirical data. In the Classical Model, experts assess both the unknown target questions and a set of calibration questions, which are items from the experts’ field that have observed true values. The Classical Model scores experts on their performance in assessing the calibration questions and then produces performance-weighted combinations of the experts. From 2006 through March 2015, the Classical Model has been used in thirty-three unique applications. Less than one-third of the individual experts in these studies were statistically accurate, highlighting the need for validation. Overall, the performance-based combination of experts produced in the Classical Model is more statistically accurate and more informative than an equal weighting of experts

Reply to comment on "Suburban watershed nitrogen retention: Estimating the effectiveness of stormwater management structures" by Koch et al. (Elem Sci Anth 3:000063, July 2015)

We reply to a comment on our recent structured expert judgment analysis of stormwater nitrogen retention in suburban watersheds. Low relief, permeable soils, a dynamic stream channel, and subsurface flows characterize many lowland Coastal Plain watersheds. These features result in unique catchment hydrology, limit the precision of streamflow measurements, and challenge the assumptions for calculating runoff from rainfall and catchment area. We reiterate that the paucity of high-resolution nitrogen loading data for Chesapeake Bay watersheds warrants greater investment in long-term empirical studies of suburban watershed nutrient budgets for this region

Suburban watershed nitrogen retention : estimating the effectiveness of stormwater management structures

Excess nitrogen (N) is a primary driver of freshwater and coastal eutrophication globally, and urban stormwater is a rapidly growing source of N pollution. Stormwater best management practices (BMPs) are used widely to remove excess N from runoff in urban and suburban areas, and are expected to perform under a wide variety of environmental conditions. Yet the capacity of BMPs to retain excess N varies; and both the variation and the drivers thereof are largely unknown, hindering the ability of water resource managers to meet water quality targets in a cost-effective way. Here, we use structured expert judgment (SEJ), a performance-weighted method of expert elicitation, to quantify the uncertainty in BMP performance under a range of site-specific environmental conditions and to estimate the extent to which key environmental factors influence variation in BMP performance. We hypothesized that rain event frequency and magnitude, BMP type and size, and physiographic province would significantly influence the experts’ estimates of N retention by BMPs common to suburban Piedmont and Coastal Plain watersheds of the Chesapeake Bay region. Expert knowledge indicated wide uncertainty in BMP performance, with N removal efficiencies ranging from 40%. Experts believed that the amount of rain was the primary identifiable source of variability in BMP efficiency, which is relevant given climate projections of more frequent heavy rain events in the mid-Atlantic. To assess the extent to which those projected changes might alter N export from suburban BMPs and watersheds, we combined downscaled estimates of rainfall with distributions of N loads for different-sized rain events derived from our elicitation. The model predicted higher and more variable N loads under a projected future climate regime, suggesting that current BMP regulations for reducing nutrients may be inadequate in the future

Designing a global assessment of climate change on inland fishes and fisheries: knowns and needs

© 2017, Springer International Publishing Switzerland (outside the USA). To date, there are few comprehensive assessments of how climate change affects inland finfish, fisheries, and aquaculture at a global scale, but one is necessary to identify research needs and commonalities across regions and to help guide decision making and funding priorities. Broadly, the consequences of climate change on inland fishes will impact global food security, the livelihoods of people who depend on inland capture and recreational fisheries. However, understanding how climate change will affect inland fishes and fisheries has lagged behind marine assessments. Building from a North American inland fisheries assessment, we convened an expert panel from seven countries to provide a first-step to a framework for determining how to approach an assessment of how climate change may affect inland fishes, capture fisheries, and aquaculture globally. Starting with the small group helped frame the key questions (e.g., who is the audience? What is the best approach and spatial scale?). Data gaps identified by the group include: the tolerances of inland fisheries to changes in temperature, stream flows, salinity, and other environmental factors linked to climate change, and the adaptive capacity of fishes and fisheries to adjust to these changes. These questions are difficult to address, but long-term and large-scale datasets are becoming more readily available as a means to test hypotheses related to climate change. We hope this perspective will help researchers and decision makers identify research priorities and provide a framework to help sustain inland fish populations and fisheries for the diversity of users around the globe

The relationship between appetite and food preferences in British and Australian children

Background: Appetitive traits and food preferences are key determinants of children’s eating patterns but it is unclear how these behaviours relate to one another. This study explores relationships between appetitive traits and preferences for fruits and vegetables, and energy dense, nutrient poor (noncore) foods in two distinct samples of Australian and British preschool children. Methods: This study reports secondary analyses of data from families participating in the British GEMINI cohort study (n = 1044) and the control arm of the Australian NOURISH RCT (n = 167). Food preferences were assessed by parent-completed questionnaire when children were aged 3–4 years and grouped into three categories; vegetables, fruits and noncore foods. Appetitive traits; enjoyment of food, food responsiveness, satiety responsiveness, slowness in eating, and food fussiness were measured using the Children’s Eating Behaviour Questionnaire when children were 16 months (GEMINI) or 3–4 years (NOURISH). Relationships between appetitive traits and food preferences were explored using adjusted linear regression analyses that controlled for demographic and anthropometric covariates. Results: Vegetable liking was positively associated with enjoyment of food (GEMINI; β = 0.20 ± 0.03, p < 0.001, NOURISH; β = 0.43 ± 0.07, p < 0.001) and negatively related to satiety responsiveness (GEMINI; β = -0.19 ± 0.03, p < 0.001, NOURISH; β = -0.34 ± 0.08, p < 0.001), slowness in eating (GEMINI; β = -0.10 ± 0.03, p = 0.002, NOURISH; β = -0.30 ± 0.08, p < 0.001) and food fussiness (GEMINI; β = −0.30 ± 0.03, p < 0.001, NOURISH; β = -0.60 ± 0.06, p < 0.001). Fruit liking was positively associated with enjoyment of food (GEMINI; β = 0.18 ± 0.03, p < 0.001, NOURISH; β = 0.36 ± 0.08, p < 0.001), and negatively associated with satiety responsiveness (GEMINI; β = −0.13 ± 0.03, p < 0.001, NOURISH; β = −0.24 ± 0.08, p = 0.003), food fussiness (GEMINI; β = -0.26 ± 0.03, p < 0.001, NOURISH; β = −0.51 ± 0.07, p < 0.001) and slowness in eating (GEMINI only; β = -0.09 ± 0.03, p = 0.005). Food responsiveness was unrelated to liking for fruits or vegetables in either sample but was positively associated with noncore food preference (GEMINI; β = 0.10 ± 0.03, p = 0.001, NOURISH; β = 0.21 ± 0.08, p = 0.010). Conclusion: Appetitive traits linked with lower obesity risk were related to lower liking for fruits and vegetables, while food responsiveness, a trait linked with greater risk of overweight, was uniquely associated with higher liking for noncore foods

Chronic Sleep Restriction in Developing Male Mice Results in Long Lasting Behavior Impairments

Sleep abnormalities are prevalent in autism spectrum disorders (ASD). Moreover, the severity of ASD symptoms are correlated with the degree of disturbed sleep. We asked if disturbed sleep during brain development itself could lead to ASD-like symptoms, particularly behavioral manifestations. We reasoned that sleep is known to be important for normal brain development and plasticity, so disrupted sleep during development might result in changes that contribute to behavioral impairments associated with ASD. We sleep-restricted C57BL/6J male mice [beginning at postnatal day 5 (P5) and continuing through P52] 3 h per day by means of gentle handling and compared the data with a stress group (handled every 15 min during the 3-h period) and a control group (no additional handling). From P42–P52, we assessed the behavioral effects of sleep-restriction in this pre-recovery phase. Then, we allowed the mice to recover for 4 weeks and tested behavior once again. Compared to the control group, we found that sleep restricted-mice had long-lasting hypoactivity, and impaired social behavior; repetitive behavior was unaffected. These behavior changes were accompanied by an increase in the downstream signaling products of the mammalian target of rapamycin pathway. These data affirm the importance of undisturbed sleep during development and show that, at least in this model, sleep-restriction can play a causative role in the development of behavioral abnormalities. Assessing and treating sleep abnormalities in ASD may be important in alleviating some of the symptoms