A Macro Economic Approach to Gender Disparities in Hiring at the CEO Level

More men named John run S&P 1500 companies than all women combined, causing many to wonder what factors are limiting women’s career advancement. While many studies have been written about the topic of women’s success in the business world, most focus on individual firms or positions and therefore miss macroeconomic factors such as women’s completion of master’s degree programs and labor force participation rates. This research examines the disparity of gender in CEO positions through the examination of macroeconomic data which captures women’s career trajectory and qualifications. This research specifically examines trends in women’s obtainment of master’s degrees in business administration to see how their completion relates to the number of female CEOs of S&P 500 companies. Obtainment of master’s degrees by women helps to examine how qualified women are to become CEOs. To assess career trajectory I examine labor force participation over time to see how women’s participation may affect their ability to become CEOs. The use of the master’s degree data as well as the labor force participation data allows for a more thorough examination of the disparity and its causes

The Grizzly, March 31, 2016

Investment Club Back in Business • Politics Class Goes to NY for Model UN • UCSG to Hold Executive Elections • Q&A with President and VP Candidates • New Platform for Student Expression • Leaving Behind a Legacy • Opinions: This Election is About You ; Advocacy on Issues You Care About • Acing the Competition • Neff Strives in Nethttps://digitalcommons.ursinus.edu/grizzlynews/1687/thumbnail.jp

Consortium for the Study of Pregnancy Treatments (Co-OPT): An international birth cohort to study the effects of antenatal corticosteroids

BACKGROUND: Antenatal corticosteroids (ACS) are widely prescribed to improve outcomes following preterm birth. Significant knowledge gaps surround their safety, long-term effects, optimal timing and dosage. Almost half of women given ACS give birth outside the "therapeutic window" and have not delivered over 7 days later. Overtreatment with ACS is a concern, as evidence accumulates of risks of unnecessary ACS exposure. METHODS: The Consortium for the Study of Pregnancy Treatments (Co-OPT) was established to address research questions surrounding safety of medications in pregnancy. We created an international birth cohort containing information on ACS exposure and pregnancy and neonatal outcomes by combining data from four national/provincial birth registers and one hospital database, and follow-up through linked population-level data from death registers and electronic health records. RESULTS AND DISCUSSION: The Co-OPT ACS cohort contains 2.28 million pregnancies and babies, born in Finland, Iceland, Israel, Canada and Scotland, between 1990 and 2019. Births from 22 to 45 weeks' gestation were included; 92.9% were at term (≥ 37 completed weeks). 3.6% of babies were exposed to ACS (67.0% and 77.9% of singleton and multiple births before 34 weeks, respectively). Rates of ACS exposure increased across the study period. Of all ACS-exposed babies, 26.8% were born at term. Longitudinal childhood data were available for 1.64 million live births. Follow-up includes diagnoses of a range of physical and mental disorders from the Finnish Hospital Register, diagnoses of mental, behavioural, and neurodevelopmental disorders from the Icelandic Patient Registers, and preschool reviews from the Scottish Child Health Surveillance Programme. The Co-OPT ACS cohort is the largest international birth cohort to date with data on ACS exposure and maternal, perinatal and childhood outcomes. Its large scale will enable assessment of important rare outcomes such as perinatal mortality, and comprehensive evaluation of the short- and long-term safety and efficacy of ACS

Consortium for the Study of Pregnancy Treatments (Co-OPT) : An international birth cohort to study the effects of antenatal corticosteroids

Acknowledgments We are grateful to the Co-OPT collaborators from Finland, Iceland, Israel, Nova Scotia, and Scotland, who have provided high-quality patient data, without which the Co-OPT ACS cohort would not have been possible. We acknowledge Public Health Scotland for providing us with a secure data analytical platform in which to undertake this research and are particularly grateful to Anna Schneider who has been the data controller for this project. Co-OPT collaborators: Karel Allegaert (Belgium), Jasper Been (Netherlands), David Burgner (Australia), Sohinee Bhattacharya (UK), Kate Duhig (UK), Kristjana Einarsdóttir (Iceland), John Fahey (Canada), Lani Florian (UK), Abigail Fraser (UK), Mika Gissler (Finland), Cynthia Gyamfi-Bannerman (USA), Bo Jacobsson (Sweden), Eyal Krispin (Israel), Stefan Kuhle (Canada), Marius Lahti-Pulkkinen (Finland), Jessica Miller (Australia), Ben Mol (Australia), Sarah Murray (UK), Jane Norman (UK), Lars Henning Pedersen (Denmark), Richard Riley (UK), Devender Roberts (UK), Ewoud Schuit (Netherlands), Aziz Sheikh (UK), Ting Shi (UK), Joshua Vogel (Australia), Rachael Wood (UK), John Wright (UK), Helga Zoega (Australia). Funding Information: The Co-OPT ACS study is funded through a Wellcome Trust Clinical Career Development Fellowship grant (Funding Reference number 209560/Z/17) awarded to Sarah J Stock. The funders had no role in study design, data collection, data analysis, decision to publish, or preparation of the manuscript. The Sponsor of the study is the University of Edinburgh (www.ed.ac. uk), Sponsor reference AC19119. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.Peer reviewedPublisher PD

The ChatGPT Artificial Intelligence Chatbot: How Well Does It Answer Accounting Assessment Questions?

ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research

Державне регулювання системи факторів оцінки та мінімізації ризиків легалізації коштів, одержаних злочинним шляхом в процесі фінансового моніторингу комерційних банків України

Основною ціллю данної статті є формулювання важливості впливу чітко визначених факторів, які впливають на процеси фінансового моніторингу в комерційних банків України. Виходячи з поставлених цілей, завданнями даної статті є розроблення моделі оцінки ризиків банківської установи щодо протидії легалізації коштів одержаних злочинним шляхом в системі внутрішньобанківського фінансового моніторингу, та використання в подальшому запропонованих стратегій управління наслідками даних ризиків

STROBE-X: A probe-class mission for x-ray spectroscopy and timing on timescales from microseconds to years

We describe the Spectroscopic Time-Resolving Observatory for Broadband Energy X-rays (STROBE-X), a probeclass mission concept that will provide an unprecedented view of the X-ray sky, performing timing and spectroscopy over both a broad energy band (0.2-30 keV) and a wide range of timescales from microseconds to years. STROBE-X comprises two narrow-field instruments and a wide field monitor. The soft or low-energy band (0.2-12 keV) is covered by an array of lightweight optics (3-m focal length) that concentrate incident photons onto small solid-state detectors with CCD-level (85-175 eV) energy resolution, 100 ns time resolution, and low background rates. This technology has been fully developed for NICER and will be scaled up to take advantage of the longer focal length of STROBE-X. The higher-energy band (2-30 keV) is covered by large-area, collimated silicon drift detectors that were developed for the European LOFT mission concept. Each instrument will provide an order of magnitude improvement in effective area over its predecessor (NICER in the soft band and RXTE in the hard band). Finally, STROBE-X offers a sensitive wide-field monitor (WFM), both to act as a trigger for pointed observations of X-ray transients and also to provide high duty-cycle, high time-resolution, and high spectral-resolution monitoring of the variable X-ray sky. The WFM will boast approximately 20 times the sensitivity of the RXTE All-Sky Monitor, enabling multi-wavelength and multi-messenger investigations with a large instantaneous field of view. This mission concept will be presented to the 2020 Decadal Survey for consideration

Genetic variability and ontogeny predict microbiome structure in a disease-challenged montane amphibian

Amphibian populations worldwide are at risk of extinction from infectious diseases, including chytridiomycosis caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd). Amphibian cutaneous microbiomes interact with Bd and can confer protective benefits to the host. The composition of the microbiome itself is influenced by many environment- and host-related factors. However, little is known about the interacting effects of host population structure, genetic variation and developmental stage on microbiome composition and Bd prevalence across multiple sites. Here we explore these questions in Amietia hymenopus, a disease-affected frog in southern Africa. We use microsatellite genotyping and 16S amplicon sequencing to show that the microbiome associated with tadpole mouthparts is structured spatially, and is influenced by host genotype and developmental stage. We observed strong genetic structure in host populations based on rivers and geographic distances, but this did not correspond to spatial patterns in microbiome composition. These results indicate that demographic and host genetic factors affect microbiome composition within sites, but different factors are responsible for host population structure and microbiome structure at the between-site level. Our results help to elucidate complex within- and among- population drivers of microbiome structure in amphibian populations. That there is a genetic basis to microbiome composition in amphibians could help to inform amphibian conservation efforts against infectious diseases

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment