Young Scholars Research Program

• Political Science

• Bioinformatics
• Biomedical Science

• Astronomy & Data Analysis Space Research
• Energy Science
• Environmental Science
• Space Research

• Artificial Intelligence & Data Science
• Machine Learning

• FinTech and Data Security
• Global Economy and Commerce

The program takes place primarily at GMU’s Arlington, Fairfax, and Prince William campuses. Bus transportation is provided. Campus maps are available here.

The program lasts between 4 weeks and 4 months, depending on faculty and program availability.

The program is designed for exceptional high school students in grades 9 through 12.

The Young Scholars Program opens applications annually in the first week of February, with limited seats per program. Fall internships may be available based on faculty availability. Admissions are first-come, first-served, so early applications are encouraged. You may also email ExecEd@gmu.edu and ask to join the notification list.

The program is designed for high school students (grades 9–12) and college freshmen, though age requirements may vary by program.

Faculty review applications to match students with personalized research projects based on their interests, skills, and proficiency levels. Students may work individually or in groups for an engaging research experience.

Yes! The program offers remote, in-person, and hybrid options. While students can complete it entirely online, we encourage attending optional on-site activities for a richer experience. Mentorship and program details will outline format options.

Yes, but some research projects or labs may be restricted to U.S. citizens. Additionally, we cannot sponsor visas.

Unfortunately, we will not be able to arrange dorms/housing.  Admitted students will receive a program guide with recommended hotels.

The program may have specific fees, waivers, or financial assistance details. It is recommended to review the program's official information or contact ExecEd@gmu.edu  for inquiries related to fees and financial considerations.

Submit your resume, research experience, awards, and application as a single file, named with your full name and the program name.

There is no specified limit on the number of times you can apply and participate in the program. Students are welcome to apply for multiple sessions based on their academic interests and availability.

Decisions are typically sent within 2–4 weeks. Seats are limited and offered on a first-come, first-served basis, with most spots filled by late April.

We aim to provide 2 hours of lectures, and students must do 2 - 4 hours of independent/group research weekly. The workload may vary based on research proficiency.

No, students must bring their own lunch. On-site activities have tight schedules, so we recommend packing a meal, though campus dining options are available.

Program Summary

The Young Scholars Research Program is tailored for high-achieving high school and undergraduate students aspiring to delve into the realms of biology or medical science, with a strong focus on advanced data analytics. Participants will have the unique opportunity to collaborate with esteemed faculty members from GMU, forming interdisciplinary teams comprising 3 to 4 individuals encompassing both high school and undergraduate students.

At the outset of the program, students will be assigned to specific team projects based on their indicated preferences. Each team is expected to produce two significant outputs by the program's conclusion. Firstly, a final paper showcasing their research findings will be published on the Center for Biomedical Science & Policy (CBSP) website and the Schar School Young Scholars Journals Webpage. Secondly, teams will present their projects at a conference where students have the chance to compete for prizes.

Throughout the program, participants will engage in hands-on research projects employing a variety of methodologies. This may include but is not limited to, biostatistics utilizing R or Stata, data visualization employing QGIS or ArcGIS, and network visualization using tools like Gephi. The comprehensive nature of the program ensures a rich and immersive experience for students passionate about advancing their understanding and skills in the fields of biology and medical science.

Program Goals

Each participant will lead a project with peers and advanced-level BS and graduate students. Transit students become proficient in research tools and applications and ways to incorporate data analysis into the students’ own biomedical context research projects. The program will provide access for students to work on real data sets and create solutions on real-world issues through professional data science, programming, and statistics apps.

Specifically, the participants will learn:

• How to frame research questions,
• How to access to/collect necessary data,
• How to analyze data to answer the research questions at hand,
• How to structure and prepare professional reports/publication manuscripts based on the data analysis results, and
• How to present your research outputs in a professional setting.

Program Benefit

• Earn experience and share views on the applications of biomedical research with policy researchers, computer scientists, biomedical scientists, and industry representatives during national conferences.
• Gain valuable teamwork experience and explore possible career paths
• Networking with national wide awardees in Biomedical Science and Data Analytics.
• Develop and refine skills for resume

Research Projects Highlights and Features

Our Course Directors Dr. Jim Olds, Dr. Naoru Koizumi, and Project Advisors, Dr. Ali Andalibi, and Dr. Megumi Inoue will lead students to work on the research projects in the areas such as:

• Bibliographic analysis of biology and medical field publications;
• Spatial and statistical analysis to investigate disparities in disease prevalence and access to medical treatment;
• Statistical analysis to infer factors determining medical and environmental policy effectiveness;
• Network analysis to elucidate links among different bacteria, diseases and other agents; and
• Biostatistics to identify optimal treatment regimens for various chronic diseases.

The final paper will be published on the Center for Biomedical Science & Policy (CBSP) website as well as the Schar School Young Scholars Journals Webpage.

Summer 2024 Tentative Research Projects Include:

• Project 1: Health-related quality of life (QOL) linked to the gut microbiome in dialysis patients
• Project 2: Determinants for international human plasma exchanges
• Project 3: Trend for organ supply in the opioid crisis era
• Project 4: Bias in Large Language Model (LLM) for Transplantation Publications 
• Project 5: Drug trafficking analysis using Network analysis and GIS
• Project 6: Bioinformatic analysis of the molecular evolution of protein kinase C in eukaryotes.

Scholarships: Each winning team member from the National Students Data Analytics and BioMedical Conference will receive a $500 scholarship that can be applied to any advanced-level BioInformatics internship programs at the Schar School during the academic years 2024 and 2025.

Program Summary

The Young Scholars NASA Data Science Analysis and Research Paper Program offers students an engaging and authentic professional, cutting-edge research experience in NASA space data science and statistical analysis. This dynamic and immersive virtual summer initiative is tailored for ambitious high school students seeking exciting and challenging opportunities in STEM. Participants will engage in a comprehensive program delving into astronomy and space sciences through a combination of research projects and lectures. Working collaboratively on current NASA mission research, students receive guidance on crafting professional-quality scholarly papers to enhance their research and communication skills.

This year's research projects will first encompass analysis of a subset of the 6000+ current NASA TESS mission exoplanet candidates and second James Webb Space Telescope data analysis.  The TESS candidates have been manually vetted after being identified by the NASA TESS mission automated search algorithms. However, they still require follow-up observations, detailed analysis, and data synthesis to evaluate the statistical probability that they are genuine exoplanets, not false positives such as nearby eclipsing binary star systems. The NASA TESS mission requires a community follow-up program to aid in validating these candidates. The primary instructor is a main contributing Principal Investigator to the official NASA TESS follow-up program and has contributed to the statistical validation and/or confirmation of over fifty of these worlds (confirmation requires mass detection through a second exoplanet detection technique).

Students will be introduced to and then apply professional tools and statistical techniques to perform this professional and cutting-edge follow-up analysis. Each student will contribute to the professional statistical validation of a unique exoplanet candidate by directly collecting, analyzing, and synthesizing novel follow-up observations. This work will be in direct support of the official NASA TESS mission exoplanet candidate follow-up program. Each exoplanet candidate is different –different planetary properties and different probabilities of statistical and astrophysical false-positive signals.  The outcome of the students analysis will aid the NASA TESS mission in determining which of its candidates are the result of genuine orbiting exoplanets. View the Transiting Exoplanet Survey Satellite (TESS) website, and the TESS Follow-Up Observing Program (TFOP) website for more information, and the article, NASA’s TESS, Spitzer Missions Discover a World Orbiting a Unique Young Star, for an example NASA discovery made by the primary instructor.

Second, the James Webb Space Telescope launched two years ago, and one of its primary science applications is the follow-up characterization of NASA TESS mission candidates to attempt to measure the atmospheric properties through spectroscopy of a subset of these worlds – about 50 to date – that we have statistically validated and/or confirmed. NASA mission data has limited or zero proprietary data periods and are available to the public. However, transforming the raw data into usable scientific products is a challenging task. Advanced students will optionally download and analyze these data sets to produce spectral time-series which require advanced modeling to extract the atmospheric spectra.

Noteworthy program highlights include:

• Engaging with experts comprised of astronomy specialists from NASA and across the globe.
• Remote or in-person control and operation of the 32-inch telescope at George Mason University during group observation nights.  This is the second-largest university telescope located on the east coast. You can observe students utilizing the George Mason University Observatory.
• Becoming experts on a chosen exoplanetary system by gathering data on observation nights and from the NASA TESS and JWST missions, analyzing and synthesizing this data during research.  Each student will choose a unique system for which they will explore and analyze.
• Crafting individual professional quality scholarly papers based on the data they collect, with guidance from George Mason faculty.  The aim is to produce papers suitable for student competition submission and in some cases suitable for publication in a professional journal.

Dr. Peter Plavchan will be the primary instructor to lead and work with teams of scientists from around this world to search for other worlds, or exoplanets, including those that are potentially habitable and Earth-like. The National Academies of Science, Engineering and Medicine once a decade survey of astrophysics has recommended a future NASA flagship mission to directly image and characterize the nearest Earth-like worlds to the Sun. This mission is now under development and called the Habitable Worlds Observatory.  It will launch in the 2040s, and the “billion dollar question” is whether or not we will know beforehand which stars host these Earth-like worlds, or if this mission will also have to search for them. Thirty years ago, the existence of other worlds was science fiction, and today over 5500 other worlds are known, many unlike anything in our Solar System. Dr Plavchan will teach you how we find these worlds, what we know about them, and how we will find “Earth 2.0”. Learn more about Peter’s research group and watch students are exploring the Universe from The George Mason University Observatory.

During this program, students will be participating in a guided astronomy-based research project applying some of the following methods, including but not limited to:

• Astronomy data analysis on NASA missions
• Observational astronomy and statistical analysis.
• Quantitative Research  
• Scientific methods of inference
• Observational data collection and management
• Statistical science inference
• The private space revolution and its impact upon astronomy and space policy

By using the following software and data for research:

• Python
• Jupyter notebooks
• Github
• AstroImageJ
• Observational Astronomy Data Analysis
• FITS files (astronomy imaging data format)
• Statistical analyses such as measurement error, time-series analysis, reduced chi-squared, rms, standard deviation and Bayesian statistical analyses.

Project Presentation Conference on August 5th, 2024

On Monday, August 5th, 2024, students will have the exciting opportunity to present their research papers at George Mason University. For those coming from out-of-state, a hybrid option is also available. The conference not only serves as a platform for showcasing research projects but also provides a competitive edge, as teams can vie for awards and scholarships offered through the Experimental NASA Data Analysis and Space Research Scholarly Paper Writing Young Scholars Program. As an added benefit, all program participants will receive two tickets, allowing them to extend invitations to family or friends to attend the conference. The National Space and Data Analysis Board (NSDAB) guarantees an exceptional experience, supporting students in honing their presentation skills and showcasing the knowledge acquired during the Young Scholars program. It's an enriching opportunity for students to shine and share their passion for space and data analysis.

Program Summary

The Machine Learning, ChatGPT, and Bayesian Statistics for Experimental Data Sciences internship program provides students an interactive and insightful research experience and introduction to the modern professional scientists’ data analysis toolbox.  During the program, students will

• Learn how machine learned is broadly applied today in cutting edge research in experimental sciences and other interdisciplinary projects.  In particular, explore applications in astronomy and exoplanet data analysis. View and example of machine learning.
• Learn how to use large language models (LLMs) such as ChatGPT as a personal research assistant, both for writing draft text, code prototyping generation for data analysis, and concept visualization.
• At the end of the program, students can optionally write a scholarly paper resulting from their internship with guidance on scientific writing.

Students participating in the program will have the opportunity to meet space experts from NASA and others in person at George Mason University. We encourage students interested in STEM-related research to join the program. 

Dr. Peter Plavchan will be the primary instructor.  He leads and works with teams of scientists from around this world to search for other worlds, or exoplanets, including those that are potentially habitable and Earth-like. Scientists today including Dr Plavchan are applying traditional analytic scientific methods and statistical methods hybridized with machine-learning based tools to computationally advance our understanding of the natural world and Universe. Learn more about Peter’s research group and watch students are exploring the Universe from The George Mason University Observatory.

During this program, students will be participating in a guided introduction to some of the following methods, including but not limited to:

• Data Science
• Machine Learning
• ChatGPT in data science with case studies
• Quantitative Research and statistical analysis
• Scientific methods of inference
• Data analysis on NASA missions
• Scholarly Paper Writing

Applications and soft wares that students will be learned and used for their research projects are including, but not limited to:

• ChatGPT  and Large Language Models
• Convolution and Deep Neural Networks
• K Means Clustering and  Support Vector Machine Classifiers, Bayesian Statistics and more
• Python, Anaconda
• Github and Gitbash
• Windows Subsystem for Linux, Xcode, and XQuartz
• Google Colab and Jupyter notebooks
• Mulkuski Archive
• NASA Exoplanet Archive
• Discord Server

Program Goals

• Introduce students to higher education experimental research practice
• Introduce students to machine learning, neural nets, large language models and statistics
• Introduce students to the roles of software development applications in experimental sciences
• Support student career paths by providing hands on research experience
• Expand student knowledge on a variety of research tools and applications that are used in research
• Support students to write a high quality scholarly paper

Program Benefit

• Gain confidence and prepare for transition to college life
• Receive instruction on practical research skills
• Gain valuable teamwork experience and explore possible career paths
• Develop and refine skills for resume
• Network with professionals in the field

Program Summary

This Young Scholars Research Program is designed for high school and biomed undergrad students, who are interested in doing biology, medicine, biostatistics/informatics, mathematical modeling and big-data analytics research with university faculties. We aim to work collaboratively on the intersection of biomedicine and artificial intelligence (AI) to generate policy recommendations. Some of these research projects will be supported by extramural research grants from top research funding agencies such as National Institutes of Health (NIH) and National Science Foundation (NSF), as well as other private and public sources including foundations, industry partners, and other governmental agencies.

During this program, students will be participating in a research project applying some of the following methods, including but not limited to:

• Biostatistics including descriptive analysis, regressions and survival analysis using R or Stata
• Network Analysis using Gephi and R
• GIS mapping and spatial analysis using QGIS
• Machine Learning (ML) algorithms with R or Python coding

Program Goals

• Introduce students to interdisciplinary research in the area of bio and medical science
• Support student career paths by providing hands-on research experience
• Expand student knowledge on a variety of research tools and applications that are used in research in the biomedical context 

Program Benefit

• Gain confidence and prepare for transition to college life
• Receive instruction on practical research skills
• Gain valuable teamwork experience and explore possible career paths
• Develop and refine skills for resume
• Network with professionals in the field

Research Projects Highlights and Features

Dr. Olds and Dr. Koizumi will lead students to experience blended research projects and course work from multiple disciplines such as bioethics and human subject studies, epidemiology and geospatial studies, chronic disease management and prevention, surgery outcomes and disparity in access to care, and gut microbiome analysis.

Students’ research projects will have the opportunity to be published on The Center for Biomedical Science & Policy website. In contrast to our summer program, the primary objective of this program is to produce a solid research paper in 4 months which ideally be published in professional conference proceedings and peer-reviewed journals within a year. For this reason, we limit the number of students involved in each project to 3 at maximum.

Research Projects include:

• Project 1. Comparative study of gut microbiome dysbiosis between healthy individuals and chronic kidney disease and end-stage kidney disease patients. (Skills acquired: Network analysis, R programing and basic statistics)
• Project 2. Graft and patient outcomes of transplants with donors from a different mechanical cause of death. (Skills acquired: Descriptive and some biostatistical analysis)
• Project 3. Illicit kidney transplantation: Costs, Locations, and Seller characteristics. (Skills acquired: Basic python coding, Mapping and spatial analysis)
• Project 4. Longitudinal study of racial, sex and training profiles of transplant surgeons in the United States (Skills acquired: Descriptive statistics and regressions).
• Project 5. Longitudinal shift of immunosuppressive regimen among pediatric transplant recipients. (Skills acquired: Descriptive statistics and some advanced biostatistical analysis).
• Project 6. Bibliometric insights into the changing landscape of diet and gut microbiome research (Skills acquired: Network analysis and R programing)

Program Summary

This Young Scholars Research Program is designed for Elite High School Students and Undergrad Students, who are interested in pursue their study and/or career in the fields of biology or medical science with emphasis on advanced data analytics. You will work with our esteemed GMU faculty members on a specific team project. The team will consist of about 3 to four members of both high school and undergraduate students. The project will be assigned to the students at the beginning of the program based on the preference indicated by the students prior to the program. Two outputs will be expected from each team at the end of the programs: i) a final paper which will be published on the Center for Biomedical Science and Policy website as well as a special issue of the World Medical & Health Policy journal; and ii) Team presentation at a symposium at which students compete for prizes.

During this program, students will be participating in a research project applying some of the following methods, including but not limited to biostatistics using R or Stata, data visualization using QGIS or ArcGIS, and network visualization using Gephi.

Program Goals

Each participant will lead a project with peers and advanced-level BS and graduate students. Transit students become proficient in research tools and applications and ways to incorporate data analysis into the students’ own biomedical context research projects. The program will provide access for students to work on real data sets and create solutions on real-world issues through professional data science, programming, and statistics apps.

Specifically, the participants will learn:

• How to frame research questions,
• How to access to/collect necessary data,
• How to analyze data to answer the research questions at hand,
• How to structure and prepare professional reports/publication manuscripts based on the data analysis results, and
• How to present your research outputs in a professional setting.

Program Benefit

• Earn experience and share views on the applications of biomedical research with policy researchers, computer scientists, biomedical scientists, and industry representatives during national conferences.
• Gain valuable teamwork experience and explore possible career paths
• Networking with national wide awardees in Biomedical Science and Data Analytics.
• Develop and refine skills for resume

Research Projects Highlights and Features

Our Course Directors Dr. Jim Olds, Dr. Naoru Koizumi, and Project Advisors, Dr. Ali Andalibi, Dr. Megumi Inoue, and Dr. Nadine Kabbani and will lead students to work on the research projects, include but are not limited to:

• Spatial variations of cyanotoxins exposure and related hospitalization
• Effect of vaping on youth health
• Geriatric /Palliative care research projects –TBA
• Transplant-related research projects - TBA

The final paper will be published on the Center for Biomedical Science and Policy
website as well as a special issue of the World Medical & Health Policy journal after the Scholarly Peer Review process.

Scholarships: Each winning team member from the National Students Data Analytics and BioMedical Conference will receive a $500 scholarship that can be applied to any advanced-level BioInformatics internship programs at the Schar School during the academic years 2023 and 2024.

Program Summary

This interactive High School Astronomy Data Analysis on NASA missions internship program combines science, technology, engineering, and mathematics learning experience. We encourage students interested in STEM-related research to join us this summer. Students who participate in the program will study astronomy and space sciences research projects and course work and have the opportunity to explore the universe by remotely controlling the telescope from George Mason University Observatory.   We will provide several evening space observation sessions during the internship program.  Besides virtual tours of GMU Department of Physics and Astronomy and George Mason University Observatory, students will also have the opportunity to participate in panels with exoplanet and astronomy experts from NASA and around the world.

Dr. Peter Plavchan will be the primary instructor to lead and work with teams of scientists from around this world to search for other worlds, or exoplanets, including those that are potentially habitable and Earth-like. The National Academies of Science, Engineering and Medicine once a decade survey of astrophysics has recommended a future NASA flagship mission to directly image and characterize the nearest Earth-like worlds to the Sun. This mission will launch in the 2040s, nd the “billion dollar question” is whether or not we will know beforehand which stars host these Earth-like worlds, or if this mission will also have to search for them. Thirty years ago, the existence of other worlds was science fiction, and today over 5000 other worlds are known, many unlike anything in our Solar System. Dr Plavchan will teach you how we find these worlds, what we know about them, and how we will find “Earth 2.0”. Learn more about Dr. Peter Plavchan's research group and watch students are exploring the Universe from The George Mason University Observatory.

During this program, students will be participating in a guided astronomy-based research project applying some of the following methods, including but not limited to:

• Astronomy data analysis on NASA missions
• Observational astronomy and statistical analysis.
• Quantitative Research  
• Scientific methods of inference
• Observational data collection and management
• Statistical science inference
• The private space revolution and its impact upon astronomy and space policy

By using the following software and data for research:

• Python
• Jupyter notebooks
• Github
• AstroImageJ
• Observational Astronomy Data Analysis
• FITS files (astronomy imaging data format)
• Statistical analyses such as measurement error, time-series analysis, reduced chi-squared, rms and standard deviation.

Program Goals

• Introduce students to higher education lab research practice
• Support student career paths by providing hands on research experience
• Expand student knowledge on a variety of research tools and applications that are used in research in the biomedical context 
• Explore connections between science and policy in space

Program Benefit

• Gain confidence and prepare for transition to college life
• Receive instruction on practical research skills
• Gain valuable teamwork experience and explore possible career paths
• Develop and refine skills for resume
• Network with professionals in the field

Program Summary

This Young Scholars Research Program is designed for high school and biomed undergrad students, who are interested in doing biology, medicine, biostatistics/informatics, mathematical modeling and big-data analytics research with university faculties.  In particular, we aim to work collaboratively on the intersection of biomedicine and artificial intelligence (AI) to generate policy recommendations. We aim that some of these research projects will be supported by extramural research grants from top research funding agencies such as National Institutes of Health (NIH) and National Science Foundation (NSF), as well as other private and public sources including foundations, industry partners and other governmental agencies.

During this program, students will be participating in a research project applying some of the following methods, including but not limited to:

• Biostatistics
• System dynamics modeling
• Network Analysis
• Discrete event simulation
• Markov modeling

 Program Goals

• Introduce students to higher education biolab and medical research practice
• Support student career paths by providing hands-on research experience
• Expand student knowledge on a variety of research tools and applications that are used in research in the biomedical context 

Program Benefit

• Gain confidence and prepare for transition to college life
• Receive instruction on practical research skills
• Gain valuable teamwork experience and explore possible career paths
• Develop and refine skills for resume
• Network with professionals in the field

Research Projects Highlights and Features

Dr. Olds and Dr. Koizumi will lead students to experience blended research projects and course work from multiple disciplines such as; bioethics and human subject studies, epidemiology and infectious disease by CDC experts, molecular biology case studies by Mason experts, health equity policy by Veterans Health Administration, chronic diseases and the prevention, etc.

Students’ research projects will have the opportunity to be published on The Center for Biomedical Science & Policy website and Multidisciplinary Digital Publishing Institute (MDPI ) Special Issue page -Health and Medical Policy in the Era of Big Data Analytics.

Research Projects include but are not limited to:

National Science Foundation (NSF – ENG: SCH: / 2123683)
2021 - 2025
Title: Collaborative Research: SCH: Optimal Desensitization Protocol in Support of a Kidney Paired Donation (KPD) System – The research team develops a mathematical model to optimize kidney donor swapping among transplant donor-patient pairs.

Bill & Melinda Gates Foundation: Round 12 Grand Challenges Explorations
2014 - 2016
Title: Integrating ICT-based Tuberculosis Treatment Innovations – The research team examined the ICT-based incentive mechanism to promote medication adherence among tuberculosis patients living in slums of India.

National Institutes of Health (NIH-R21 DK088368-01)
2010 - 2013
Title: Using GIS and Simulation for Analyzing Optimal Geographical Boundaries and Organ Allocation Mechanism for Liver Transplantation – The research team looked into redesigning the organ/liver allocation polities for transplants in the United States.

On-site laboratory Research Activities are based on availability from:

• National Science Foundation (NSF) Headquarter
• Meeting with National Institutes of Health (NIH) scientists
• Veterans Health Administration (VHA)
• George Mason University -  The Biomedical Research Lab (BRL) -  A Biosafety Level 3 (BSL-3) laboratory
• GMU Center for Applied Proteomics and Molecular Medicine
• GMU Institute for Digital Innovation (IDIA)
• George Washington Hospital (Ron Paul Kidney Center)
• Capital Care Inc. (Hospice Organization)

 Program Summary

The Gender and Policy Center’s High School Student Internship Program: Policy Research and Data Analysis provides authentic research and immersive internship experience to high school students who are looking to advance their studies and pursue higher education research at an R1 Research University.   

During this program, students will be participating in a research project applying some of the following methods, including but not limited to:

• Qualitative Research
• Content Analysis
• Application of Theoretical Frames
• Qualitative Data Analysis
• Data collection and management
• Coding of Data

 Program Goals

• Introduce students to higher education research practice and techniques
• Support student career paths by providing hands on research experience
• Expand student knowledge on a variety of research tools and applications that are used in research in the policy context 

Program Benefit

• Gain confidence and prepare for transition to college life
• Receive instruction on practical research skills
• Gain valuable teamwork experience and explore possible career paths
• Develop and refine skills for resume
• Network with professionals in the field

Research Program Highlights and Features

Gender, Power, and Politics:  This project will examine portrayals of women candidates and officeholders in the media and consider the implications for their ability to attain, hold and operate in positions of public authority, as well as related policy implications. 

• Dr. Bonnie Stabile will lead student interns in assisting with the conduct of research for this project, which is part of the larger research agenda of the Schar School’s Gender and Policy Center, which she founded and directs (genderandpolicy.gmu.edu). 
• Dr. Laurie A. Schintler will guide students on some analysis aspects of the research, including data visualization. 
• Dr. Heidi Lawrence will guide students through research methods for the project, including coding, content analysis, and assuring intercoder reliability. 
• Research paper and Article publishing: Each student who successfully completes their assigned research tasks will be acknowledged as a research assistant for the published article that is planned based on the findings of this analysis.