Trends in Gender Segregation in the Choice of Science and Engineering Majors

Numerous theories have been put forward for the high and continuing levels of gender segregation, but research has not systematically examined the extent to which these theories for the gender gap are consistent with actual trends. Using both administrative data and three education panel datasets, we evaluate several prominent explanations for the persisting gender gap in STEM fields, and find that none of them are empirically satisfactory. Instead, the persisting gender gap in STEM fields is plausibly attributable to a females' greater preference relative to males for elite occupational careers that are less "vocationally oriented" in the undergraduate years and that permit greater flexibility in undergraduate. This hypothesis is supported by an analysis of gendered pathways to medical and law school

Beyond Medicalization: Explaining the Increased Prevalence of Attention Deficit-Hyperactivity Disorder

Attention Deficit-Hyperactivity Disorder diagnoses have been rising steadily since the early 1990s. Today, about 10 percent of the school-aged population has been diagnosed with the disorder, and prevalence is increasing steadily among preschool children and adults. Most of the individuals diagnosed with the disorder use stimulant medications to treat the symptoms. Both the rapidly rising number of diagnoses and the substantial variation in prevalence and treatment utilization -- across states, regions, gender, race, ethnicity, and socioeconomic status -- have attracted attention and raised concerns about under and over recognition and treatment. The implicit justification for the increasing awareness and recognition of the disorder is that it is a valid clinical object that matches medically-proven treatments with those reliably expected to benefit from them. From this perspective, the uptake in prevalence results from changes in environmental determinants or scientific advances in neurology, psychiatry, diagnostic protocols, or pharmaceutical research. But a widespread argument among teachers, parents, policy makers, the general public, and academic researchers -- including sociologists -- is that the development and success of the disorder results from a medicalization process. Medicalization encompasses a social construction critique that contradicts the environmental/scientific advance claims, but medicalization research also emphasizes macro-level actors that forcibly advance the medical label and treatment. Traditionally, medicalization studies focused on the disproportionate power of the medical profession vis-a-vis patients, but more recently they have begun to emphasize a broader range of actors pursuing a medical label -- pharmaceutical companies and even consumers influenced by new forms of advertising. Those arguments assume that educational institutions act in concert with those pushing the medical label. The goal of this dissertation is to provide an account of diagnostic prevalence and treatment utilization (and their uneven distribution) that debunks explanations based solely in science but that also demonstrates the insufficiency of the medicalization account. Together, the chapters show that there is no correlation in timing between the surge in diagnoses and the processes implied by either medicalization or scientific progress arguments, there is little support in the micro-level data for a strictly medicalization account, and there is substantial evidence that macro-level educational institutions and the school context play a significant role in reshaping the category. The chapters emphasize that the success of the category lies in the confluence of technoscientific innovation, social control of troublesome behaviors, the increased activism of parents along with direct-to-consumer pharmaceutical advertising, encroachments of the law into student discipline and into the health care industry, the institutional needs of schools, a cultural emphasis on high academic achievement, and the influence of parallel and predecessor classifications, among other factors. The category -- a result of multiple institutions working to recraft expertise – is a school-specific medical disorder that includes a heterogeneous symptom complex, one that is understood differently within school and medical milieu. Although the chapters do not disprove medicalization, they suggest that the medicalization framework overstates the importance of medical professionals and medicine broadly defined for the success of the category

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts