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We examine patient gender disparities in survival rates following acute myocardial infarctions (i.e., heart attacks) based on the gender of the treating physician. Using a census of heart attack patients admitted to Florida hospitals between 1991 and 2010, we find higher mortality among female patients who are treated by male physicians. Male patients and female patients experience similar outcomes when treated by female physicians, suggesting that unique challenges arise when male physicians treat female patients. We further find that male physicians with more exposure to female patients and female physicians have more success treating female patients.

Recent studies find that female-led ventures are penalized relative to male-led ventures as a result of role incongruity or a perceived “lack of fit” between female stereotypes and expected personal qualities of business entrepreneurs. We examine whether social impact framing that emphasizes a venture’s social–environmental welfare benefits, which research has shown to elicit stereotypically feminine attributions of warmth, diminishes these penalties. We initially investigate this proposition in a field study of evaluations of early-stage ventures and find evidence of lessened gender penalties for female-led ventures that are presented using a social impact frame. In a second study, we experimentally validate this effect and show that it is mediated by the effect of social impact framing on perceptions of the entrepreneur’s warmth. The effect of social impact frames on venture evaluations did not apply to men, was not a result of perceptions of increased competence, and was not conditional on the gender of evaluators. Taken together, our findings demonstrate that social impact framing increases attributions of warmth for all entrepreneurs but with positive consequences on business evaluation only for female-led ventures, for which increased perceptions of warmth attenuate female entrepreneurs’ gender role incongruity. The online appendix is available at https://doi.org/10.1287/orsc.2017.1172 .

Entrepreneurship is a central path to job creation, economic growth, and prosperity. In the earliest stages of start-up business creation, the matching of entrepreneurial ventures to investors is critically important. The entrepreneur's business proposition and previous experience are regarded as the main criteria for investment decisions. Our research, however, documents other critical criteria that investors use to make these decisions: the gender and physical attractiveness of the entrepreneurs themselves. Across a field setting (three entrepreneurial pitch competitions in the United States) and two experiments, we identify a profound and consistent gender gap in entrepreneur persuasiveness. Investors prefer pitches presented by male entrepreneurs compared with pitches made by female entrepreneurs, even when the content of the pitch is the same. This effect is moderated by male physical attractiveness: attractive males were particularly persuasive, whereas physical attractiveness did not matter among female entrepreneurs.

Understanding sociodemographic factors associated with poor visual outcomes in children with juvenile idiopathic arthritis-associated uveitis may help inform practice patterns. Retrospective cohort study on patients <18 years old who were diagnosed with both juvenile idiopathic arthritis and uveitis based on International Classification of Diseases tenth edition codes in the Intelligent Research in Sight Registry through December 2020. Surgical history was extracted using current procedural terminology codes. The primary outcome was incidence of blindness (20/200 or worse) in at least one eye in association with sociodemographic factors. Secondary outcomes included cataract and glaucoma surgery following uveitis diagnosis. Hazard ratios were calculated using multivariable-adjusted Cox proportional hazards models. Median age of juvenile idiopathic arthritis-associated uveitis diagnosis was 11 (Interquartile Range: 8 to 15). In the Cox models adjusting for sociodemographic and insurance factors, the hazard ratios of best corrected visual acuity 20/200 or worse were higher in males compared to females (HR 2.15; 95% CI: 1.45-3.18), in Black or African American patients compared to White patients (2.54; 1.44-4.48), and in Medicaid-insured patients compared to commercially-insured patients (2.23; 1.48-3.37). Sociodemographic factors and insurance coverage were associated with varying levels of risk for poor visual outcomes in children with juvenile idiopathic arthritis-associated uveitis.

Purpose To evaluate the clinical presentation, course, and outcomes of uveitis in paediatric patients with tubulointerstitial nephritis and uveitis syndrome (TINU). Methods Multicentric Retrospective Cohort Study 110 patients ≤21 years of age diagnosed with TINU from 10 sites across the United States and Canada. Clinical diagnosis of TINU required uveitis diagnosed by an ophthalmologist, elevated serum creatinine (SCr) and elevated urine β2-microglobulin (β2M) or abnormal urinalysis. Renal biopsy and systemic illness were not mandatory. Univariate and multivariate analysis was performed to analyse risk factors and treatment modalities. Results Median age was 13 years (Range (5.9–18.4); 52% male); median follow-up, 1.6 years (IQR 0.98–4.02). Uveitis was symptomatic in 90%, with bilateral anterior uveitis in 94%. Ninety-two (84%) patients required immunomodulatory treatment (IMT). Methotrexate (n = 44) and mycophenolate mofetil (n = 39) were the first agents after oral corticosteroids. 45% required addition of biologic agents (Adalimumab [n = 33], Infliximab [n = 8]). Younger age (p = 0.018), male sex (p = 0.011), and higher uveitis grade at presentation (p = 0.031) were associated with greater IMT ( ≥ 2) requirement. 53% had uveitis recurrence compared to 16% with nephritis recurrence. At the most recent visit, nephritis was controlled in 90%, while uveitis in 74%. Four (4%) patients required glaucoma surgery. Nine (8%) patients had renal complications. Conclusions Most patients with TINU require steroid-sparing IMT for control of uveitis, with nearly half requiring addition of biologic agents. Urinalysis, urine β2M and SCr testing should be considered in children presenting with uveitis, especially when the disease is bilateral and anterior.

As artificial intelligence has begun to write code, pilot vehicles, and even diagnose disease, narratives of machines abruptly replacing humans have taken hold. However, the real story is slower, messier, and far more uneven. Across roles and industries, Al's emergent capabilities form what's often called a \"jagged frontier,\" where it excels at some tasks while struggling with others. As its capabilities progress, Al is racing to fully automate some tasks while slowing to a crawl or stalling entirely for others. Leaders who understand the factors that shape this nuanced reality will be able to guide strategy and talent with clarity and steady their organizations in the process. We've identified key friction factors -- like repetition, regulation, judgment, and human assurance -- that slow Al adoption. Based on those findings, we'll offer a nuanced lens on why most jobs evolve in stages and at different speeds. The future of work won't be defined by Al's capabilities alone. It will also depend on the friction it meets.

Although the quality of weather forecasts in the polar regions is improving, forecast skill there still lags behind lower latitudes. So far there have been relatively few efforts to evaluate processes in numerical weather prediction systems using in situ and remote sensing datasets from meteorological observatories in the terrestrial Arctic and Antarctic compared to the mid-latitudes. Progress has been limited both by the heterogeneous nature of observatory and forecast data and by limited availability of the parameters needed to perform process-oriented evaluation in multi-model forecast archives. The Year of Polar Prediction (YOPP) site Model Inter-comparison Project (YOPPsiteMIP) is addressing this gap by producing merged observatory data files (MODFs) and merged model data files (MMDFs), bringing together observations and forecast data at polar meteorological observatories in a format designed to facilitate process-oriented evaluation.An evaluation of forecast performance was performed at seven Arctic sites, focussing on the first YOPP Special Observing Period in the Northern Hemisphere (NH-SOP1) in February and March 2018. It demonstrated that although the characteristics of forecast skill vary between the different sites and systems, an underestimation in boundary layer temperature variability across models, which goes hand in hand with an inability to capture cold extremes, is a common issue at several sites. It is found that many models tend to underestimate the sensitivity of the 2 m air temperature (T2m) and the surface skin temperature to variations in radiative forcing, and the reasons for this are discussed.

A large and ever-growing body of geophysical information is measured in campaigns and at specialized observatories as a part of scientific expeditions and experiments. These collections of observed data include many essential climate variables (as defined by the Global Climate Observing System) but are often distinguished by a wide range of additional non-routine measurements that are designed to not only document the state of the environment but also the drivers that contribute to that state. These field data are used not only to further understand environmental processes through observation-based studies but also to provide baseline data to test model performance and to codify understanding to improve predictive capabilities. To address the considerable barriers and difficulty in utilizing these diverse and complex data for observation–model research, the Merged Observatory Data File (MODF) concept has been developed. A MODF combines measurements from multiple instruments into a single file that complies with well-established data format and metadata practices and has been designed to parallel the development of corresponding Merged Model Data Files (MMDFs). Using the MODF and MMDF protocols will facilitate the evolution of model intercomparison projects into model intercomparison and improvement projects by putting observation and model data “on the same page” in a timely manner. The MODF concept was developed especially for weather forecast model studies in the Arctic. The surprisingly complex process of implementing MODFs in that context refined the concept itself. Thus, this article explains the concept of MODFs by providing details on the issues that were revealed and resolved during that first specific implementation. Detailed instructions are provided on how to make MODFs, and this article can be considered a MODF creation manual.

Recent work has emphasized the benefits of patient–physician concordance on clinical care outcomes for underrepresented minorities, arguing it can ameliorate outgroup biases, boost communication, and increase trust. We explore concordance in a setting where racial disparities are particularly severe: childbirth. In the United States, Black newborns die at three times the rate of White newborns. Results examining 1.8 million hospital births in the state of Florida between 1992 and 2015 suggest that newborn–physician racial concordance is associated with a significant improvement in mortality for Black infants. Results further suggest that these benefits manifest during more challenging births and in hospitals that deliver more Black babies. We find no significant improvement in maternal mortality when birthing mothers share race with their physician.

Using an inductive theory-development study, a field experiment, and a longitudinal field test, we examine early-stage entrepreneurial investment decision making under conditions of extreme uncertainty. Building on existing literature on decision making and risk in organizations, intuition, and theories of entrepreneurial financing, we test the effectiveness of angel investors' criteria for making investment decisions. We found that angel investors' decisions have several characteristics that have not been adequately captured in existing theory: angel investors have clear objectives—risking small stakes to find extraordinarily profitable investments, fully expecting to lose their entire investment in most cases—and they rely on a combination of expertise-based intuition and formal analysis in which intuition trumps analysis, contrary to reports in other investment contexts. We also found that their reported emphasis on assessments of the entrepreneur accurately predicts extraordinarily profitable venture success four years later. We develop this theory by examining situations in which uncertainty is so extreme that it qualifies as unknowable, using the term \"gut feel\" to describe their dynamic emotion-cognitions in which they blend analysis and intuition in ways that do not impair intuitive processes and that effectively predict extraordinarily profitable investments.