Women are vastly underrepresented in the fields of computer science and engineering (CS&E). We examined whether women might view the intellectual characteristics of prototypical individuals in CS&E in more stereotype-consistent ways than men might and, consequently, show less interest in CS&E. We asked 269 U.S. college students (187, 69.5% women) to describe the prototypical computer scientist (Study 1) or engineer (Study 2) through open-ended descriptions as well as through a set of trait ratings. Participants also rated themselves on the same set of traits and rated their similarity to the prototype. Finally, participants in both studies were asked to describe their likelihood of pursuing future college courses and careers in computer science (Study 1) or engineering (Study 2). Across both studies, we found that women offered more stereotype-consistent ratings than did men of the intellectual characteristics of prototypes in CS (Study 1) and engineering (Study 2). Women also perceived themselves as less similar to the prototype than men did. Further, the observed gender differences in prototype perceptions mediated the tendency for women to report lower interest in CS&E fields relative to men. Our work highlights the importance of prototype perceptions for understanding the gender gap in CS&E and suggests avenues for interventions that may increase women's representation in these vital fields.
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http://dx.doi.org/10.1007/s11199-017-0763-x | DOI Listing |
Soft Matter
January 2025
School of Environmental, Civil, Agricultural and Mechanical Engineering, College of Engineering, University of Georgia, Athens, GA 30602, USA.
The surface morphology of the developing mammalian brain is crucial for understanding brain function and dysfunction. Computational modeling offers valuable insights into the underlying mechanisms for early brain folding. Recent findings indicate significant regional variations in brain tissue growth, while the role of these variations in cortical development remains unclear.
View Article and Find Full Text PDFCureus
December 2024
Department of Technology and Clinical Trials, Advanced Research, Deerfield Beach, USA.
This paper investigates the potential of artificial intelligence (AI) and machine learning (ML) to enhance the differentiation of cystic lesions in the sellar region, such as pituitary adenomas, Rathke cleft cysts (RCCs) and craniopharyngiomas (CP), through the use of advanced neuroimaging techniques, particularly magnetic resonance imaging (MRI). The goal is to explore how AI-driven models, including convolutional neural networks (CNNs), deep learning, and ensemble methods, can overcome the limitations of traditional diagnostic approaches, providing more accurate and early differentiation of these lesions. The review incorporates findings from critical studies, such as using the Open Access Series of Imaging Studies (OASIS) dataset (Kaggle, San Francisco, USA) for MRI-based brain research, highlighting the significance of statistical rigor and automated segmentation in developing reliable AI models.
View Article and Find Full Text PDFNeurooncol Adv
November 2024
Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, Saint Louis, Missouri, USA.
Background: Alterations in cellular metabolism affect cancer survival and can manifest in metrics of body composition. We investigated the effects of various body composition metrics on survival in patients with glioblastoma (GBM).
Methods: We retrospectively analyzed patients who had an abdominal and pelvic computed tomography (CT) scan performed within 1 month of diagnosis of GBM (178 participants, 102 males, 76 females, median age: 62.
Research (Wash D C)
June 2022
Wuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology (HUST), Luoyu Road 1037, Wuhan 430074, China.
The development of smart wearable electronic devices puts forward higher requirements for future flexible electronics. The design of highly sensitive and high-performance flexible pressure sensors plays an important role in promoting the development of flexible electronic devices. Recently, MXenes with excellent properties have shown great potential in the field of flexible electronics.
View Article and Find Full Text PDFClin Ophthalmol
December 2024
Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece.
Purpose: To identify the minimally required number of distances of visual acuity (VA) measurements for the reliable estimation of the visual acuity curve (VAC) and area of the curve (AoC) in presbyopia correction.
Patients And Methods: The study was divided into a validation and a clinical phase with a total recruitment of 120 participants (120 eyes) who underwent uncomplicated pseudophakic presbyopia surgery with bilateral premium intraocular lenses (IOL) implantation. This study was conducted in the Department of Ophthalmology, University Hospital of Alexandroupolis, Alexandroupolis, Greece.
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