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The top list of academic search engines

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1. Google Scholar

4. science.gov, 5. semantic scholar, 6. baidu scholar, get the most out of academic search engines, frequently asked questions about academic search engines, related articles.

Academic search engines have become the number one resource to turn to in order to find research papers and other scholarly sources. While classic academic databases like Web of Science and Scopus are locked behind paywalls, Google Scholar and others can be accessed free of charge. In order to help you get your research done fast, we have compiled the top list of free academic search engines.

Google Scholar is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only lets you find research papers for all academic disciplines for free but also often provides links to full-text PDF files.

  • Coverage: approx. 200 million articles
  • Abstracts: only a snippet of the abstract is available
  • Related articles: ✔
  • References: ✔
  • Cited by: ✔
  • Links to full text: ✔
  • Export formats: APA, MLA, Chicago, Harvard, Vancouver, RIS, BibTeX

Search interface of Google Scholar

BASE is hosted at Bielefeld University in Germany. That is also where its name stems from (Bielefeld Academic Search Engine).

  • Coverage: approx. 136 million articles (contains duplicates)
  • Abstracts: ✔
  • Related articles: ✘
  • References: ✘
  • Cited by: ✘
  • Export formats: RIS, BibTeX

Search interface of Bielefeld Academic Search Engine aka BASE

CORE is an academic search engine dedicated to open-access research papers. For each search result, a link to the full-text PDF or full-text web page is provided.

  • Coverage: approx. 136 million articles
  • Links to full text: ✔ (all articles in CORE are open access)
  • Export formats: BibTeX

Search interface of the CORE academic search engine

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need anymore to query all those resources separately!

  • Coverage: approx. 200 million articles and reports
  • Links to full text: ✔ (available for some databases)
  • Export formats: APA, MLA, RIS, BibTeX (available for some databases)

Search interface of Science.gov

Semantic Scholar is the new kid on the block. Its mission is to provide more relevant and impactful search results using AI-powered algorithms that find hidden connections and links between research topics.

  • Coverage: approx. 40 million articles
  • Export formats: APA, MLA, Chicago, BibTeX

Search interface of Semantic Scholar

Although Baidu Scholar's interface is in Chinese, its index contains research papers in English as well as Chinese.

  • Coverage: no detailed statistics available, approx. 100 million articles
  • Abstracts: only snippets of the abstract are available
  • Export formats: APA, MLA, RIS, BibTeX

Search interface of Baidu Scholar

RefSeek searches more than one billion documents from academic and organizational websites. Its clean interface makes it especially easy to use for students and new researchers.

  • Coverage: no detailed statistics available, approx. 1 billion documents
  • Abstracts: only snippets of the article are available
  • Export formats: not available

Search interface of RefSeek

Consider using a reference manager like Paperpile to save, organize, and cite your references. Paperpile integrates with Google Scholar and many popular databases, so you can save references and PDFs directly to your library using the Paperpile buttons:

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Google Scholar is an academic search engine, and it is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only let's you find research papers for all academic disciplines for free, but also often provides links to full text PDF file.

Semantic Scholar is a free, AI-powered research tool for scientific literature developed at the Allen Institute for AI. Sematic Scholar was publicly released in 2015 and uses advances in natural language processing to provide summaries for scholarly papers.

BASE , as its name suggest is an academic search engine. It is hosted at Bielefeld University in Germany and that's where it name stems from (Bielefeld Academic Search Engine).

CORE is an academic search engine dedicated to open access research papers. For each search result a link to the full text PDF or full text web page is provided.

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need any more to query all those resources separately!

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Oa.mg is a search engine for academic papers, specialising in open access. we have over 250 million papers in our index..

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ScienceOpen provides researchers with a wide range of tools to support their research – all for free. Here is a short checklist to make sure you are getting the most of the technological infrastructure and content that we have to offer. What can a researcher do on ScienceOpen? Continue reading “What can a Researcher do on ScienceOpen?”   

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arXiv is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

arXiv is a free distribution service and an open-access archive for scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

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Stay Connected With Semantic Scholar Sign Up What Is Semantic Scholar? Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI.

🇺🇦    make metadata, not war

A comprehensive bibliographic database of the world’s scholarly literature

The world’s largest collection of open access research papers, machine access to our vast unique full text corpus, core features, indexing the world’s repositories.

We serve the global network of repositories and journals

Comprehensive data coverage

We provide both metadata and full text access to our comprehensive collection through our APIs and Datasets

Powerful services

We create powerful services for researchers, universities, and industry

Cutting-edge solutions

We research and develop innovative data-driven and AI solutions

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Cost-free PIDs for your repository

OAI identifiers are unique identifiers minted cost-free by repositories. Ensure that your repository is correctly configured, enabling the CORE OAI Resolver to redirect your identifiers to your repository landing pages.

OAI IDs provide a cost-free option for assigning Persistent Identifiers (PIDs) to your repository records. Learn more.

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Enabling others to create new tools and innovate using a global comprehensive collection of research papers.

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“ Our partnership with CORE will provide Turnitin with vast amounts of metadata and full texts that we can ... ” Show more

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Making research more discoverable, improving metadata quality, helping to meet and monitor open access compliance.

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“ CORE’s role in providing a unified search of repository content is a great tool for the researcher and ex... ” Show more

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Tools to find, discover and explore the wealth of open access research. Free for everyone, forever.

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Helping funders to analyse, audit and monitor open research and accelerate towards open science.

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Create new and innovative solutions.

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Find relevant research and make your research more visible.

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Manage how your research content is exposed to the world.

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Our partnership with CORE will provide Turnitin with vast amounts of metadata and full texts that we can utilise in our plagiarism detection software.

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Executive Director of the Confederation of Open Access Repositories (COAR)

CORE has significantly assisted the academic institutions participating in our global network with their key mission, which is their scientific content exposure. In addition, CORE has helped our content administrators to showcase the real benefits of repositories via its added value services.

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Aggregation plays an increasingly essential role in maximising the long-term benefits of open access, helping to turn the promise of a 'research commons' into a reality. The aggregation services that CORE provides therefore make a very valuable contribution to the evolving open access environment in the UK.

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About OATD.org

OATD.org aims to be the best possible resource for finding open access graduate theses and dissertations published around the world. Metadata (information about the theses) comes from over 1100 colleges, universities, and research institutions . OATD currently indexes 6,948,050 theses and dissertations.

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We’re happy to present several data visualizations to give an overall sense of the OATD.org collection by county of publication, language, and field of study.

You may also want to consult these sites to search for other theses:

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  • NDLTD , the Networked Digital Library of Theses and Dissertations. NDLTD provides information and a search engine for electronic theses and dissertations (ETDs), whether they are open access or not.
  • Proquest Theses and Dissertations (PQDT), a database of dissertations and theses, whether they were published electronically or in print, and mostly available for purchase. Access to PQDT may be limited; consult your local library for access information.

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The SpringerOpen portfolio has grown tremendously since its launch in 2010, so that we now offer researchers from all areas of science, technology, medicine, the humanities and social sciences a place to publish open access in journals. Publishing with SpringerOpen makes your work freely available online for everyone, immediately upon publication, and our high-level peer-review and production processes guarantee the quality and reliability of the work. Open access books are published by our Springer imprint.

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Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Writing a Research Paper

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Welcome to the Purdue OWL

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Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

The Research Paper

There will come a time in most students' careers when they are assigned a research paper. Such an assignment often creates a great deal of unneeded anxiety in the student, which may result in procrastination and a feeling of confusion and inadequacy. This anxiety frequently stems from the fact that many students are unfamiliar and inexperienced with this genre of writing. Never fear—inexperience and unfamiliarity are situations you can change through practice! Writing a research paper is an essential aspect of academics and should not be avoided on account of one's anxiety. In fact, the process of writing a research paper can be one of the more rewarding experiences one may encounter in academics. What is more, many students will continue to do research throughout their careers, which is one of the reasons this topic is so important.

Becoming an experienced researcher and writer in any field or discipline takes a great deal of practice. There are few individuals for whom this process comes naturally. Remember, even the most seasoned academic veterans have had to learn how to write a research paper at some point in their career. Therefore, with diligence, organization, practice, a willingness to learn (and to make mistakes!), and, perhaps most important of all, patience, students will find that they can achieve great things through their research and writing.

The pages in this section cover the following topic areas related to the process of writing a research paper:

  • Genre - This section will provide an overview for understanding the difference between an analytical and argumentative research paper.
  • Choosing a Topic - This section will guide the student through the process of choosing topics, whether the topic be one that is assigned or one that the student chooses themselves.
  • Identifying an Audience - This section will help the student understand the often times confusing topic of audience by offering some basic guidelines for the process.
  • Where Do I Begin - This section concludes the handout by offering several links to resources at Purdue, and also provides an overview of the final stages of writing a research paper.

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  • Published: 24 June 2024

Bound star clusters observed in a lensed galaxy 460 Myr after the Big Bang

  • Angela Adamo   ORCID: orcid.org/0000-0002-8192-8091 1 ,
  • Larry D. Bradley 2   na1 ,
  • Eros Vanzella   ORCID: orcid.org/0000-0001-5228-9326 3   na1 ,
  • Adélaïde Claeyssens 1 ,
  • Brian Welch 4 , 5 ,
  • Jose M. Diego   ORCID: orcid.org/0000-0001-9065-3926 6 ,
  • Guillaume Mahler 7 , 8 , 9 ,
  • Masamune Oguri   ORCID: orcid.org/0000-0003-3484-399X 10 , 11 ,
  • Keren Sharon   ORCID: orcid.org/0000-0002-7559-0864 12 ,
  • Abdurro’uf 2 , 13 ,
  • Tiger Yu-Yang Hsiao 2 , 13 ,
  • Xinfeng Xu   ORCID: orcid.org/0000-0002-9217-7051 14 , 15 ,
  • Matteo Messa   ORCID: orcid.org/0000-0003-1427-2456 3 ,
  • Augusto E. Lassen   ORCID: orcid.org/0000-0003-3575-8316 1 , 16 ,
  • Erik Zackrisson 17 , 18 ,
  • Gabriel Brammer   ORCID: orcid.org/0000-0003-2680-005X 19 , 20 ,
  • Dan Coe   ORCID: orcid.org/0000-0001-7410-7669 2 , 13 , 21 ,
  • Vasily Kokorev   ORCID: orcid.org/0000-0002-5588-9156 22 ,
  • Massimo Ricotti 4 ,
  • Adi Zitrin   ORCID: orcid.org/0000-0002-0350-4488 23 ,
  • Seiji Fujimoto   ORCID: orcid.org/0000-0001-7201-5066 24 ,
  • Akio K. Inoue   ORCID: orcid.org/0000-0002-7779-8677 25 , 26 ,
  • Tom Resseguier   ORCID: orcid.org/0009-0007-0522-7326 13 ,
  • Jane R. Rigby   ORCID: orcid.org/0000-0002-7627-6551 5 ,
  • Yolanda Jiménez-Teja 27 , 28 ,
  • Rogier A. Windhorst 29 ,
  • Takuya Hashimoto 30 , 31 &
  • Yoichi Tamura   ORCID: orcid.org/0000-0003-4807-8117 32  

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  • Early universe
  • Galaxies and clusters

The Cosmic Gems arc is among the brightest and highly magnified galaxies observed at redshift z ∼ 10.2 1 . However, it is an intrinsically UV faint galaxy, in the range of those now thought to drive the reionization of the universe 2–4 . Hitherto the smallest features resolved in a galaxy at a comparable redshift are between a few hundreds and a few tens of parsecs 5,6 . Here we report JWST observations of the Cosmic Gems. The light of the galaxy is resolved into five star clusters located in a region smaller than 70 parsec. They exhibit minimal dust attenuation and low metallicity, ages younger than 50 Myr and intrinsic masses of ∼ 10 6 M ⊙ . Their lensing-corrected sizes are approximately 1 pc, resulting in stellar surface densities near 10 5 M ⊙ /pc 2 , three orders of magnitude higher than typical young star clusters in the local universe 7 . Despite the uncertainties inherent to the lensing model, they are consistent with being gravitationally bound stellar systems, i.e., proto-globular clusters (proto-GCs). We conclude that star cluster formation and feedback likely contributed to 3 shape the properties of galaxies during the epoch of reionization.

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Author information.

These authors contributed equally: Larry D. Bradley, Eros Vanzella

Authors and Affiliations

Astronomy Department, Stockholm University & Oskar Klein Centre, Roslagstullsbacken 21, Stockholm, Sweden

Angela Adamo, Adélaïde Claeyssens & Augusto E. Lassen

Space Telescope Science Institute (STScI), 3700 San Martin Drive, Baltimore, MD, USA

Larry D. Bradley,  Abdurro’uf, Tiger Yu-Yang Hsiao & Dan Coe

Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, INAF, via Gobetti 93/3, Bologna, Italy

Eros Vanzella & Matteo Messa

Department of Astronomy, University of Maryland, 4296 Stadium Drive, College Park, USA

Brian Welch & Massimo Ricotti

Astrophysics Science Division, Code 660, NASA Goddard Space Flight Center, 8800 Greenbelt Rd., Greenbelt, MD, USA

Brian Welch & Jane R. Rigby

Instituto de Física de Cantabria, (CSIC-UC), Avda. Los Castros s/n., Santander, Spain

Jose M. Diego

STAR Institute,Quartier Agora - Allée du six Août, 19c, Liège, Belgium

Guillaume Mahler

Centre for Extragalactic Astronomy, Durham University, South Road, Durham, UK

Institute for Computational Cosmology, Durham University, South Road, Durham, UK

Center for Frontier Science, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba, Japan

Masamune Oguri

Department of Physics, Graduate School of Science, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba, Japan

Department of Astronomy, University of Michigan, 1085 S. University Ave, Ann Arbor, MI, USA

Keren Sharon

Center for Astrophysical Sciences, Department of Physics and Astronomy, The Johns Hopkins University, 3400 N Charles St., Baltimore, MD, USA

Abdurro’uf, Tiger Yu-Yang Hsiao, Dan Coe & Tom Resseguier

Department of Physics and Astronomy, Northwestern University, 2145 Sheridan Road, Evanston, IL, USA

Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA), Northwestern University, 1800 Sherman Avenue, Evanston, IL, USA

Instituto de Física, Departamento de Astronomia, Universe Federal do Rio Grande do Sul, Avenida Bento Gonçalves, Porto Alegre, Brazil

Augusto E. Lassen

Observational Astrophysics, Department of Physics and Astronomy, Uppsala University, Box 516, Uppsala, Sweden

Erik Zackrisson

Swedish Collegium for Advanced Study, Linneanum, Thunbergsvägen 2, Uppsala, Uppsala, Sweden

Cosmic Dawn Center (DAWN), Copenhagen, Denmark

Gabriel Brammer

Niels Bohr Institute, University of Copenhagen, Jagtvej 128, Copenhagen, Denmark

Association of Universities for Research in Astronomy (AURA) for the European Space Agency (ESA), STScI, Baltimore, MD, USA

Kapteyn Astronomical Institute, University of Groningen, Landleven 12, Groningen, Netherlands

Vasily Kokorev

Department of Physics, Ben-Gurion University of the Negev, P.O. Box 653, Be’er-Sheva, Israel

Department of Astronomy, The University of Texas at Austin, Austin, TX, USA

Seiji Fujimoto

Department of Physics, School of Advanced Science and Engineering, Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo, Japan

Akio K. Inoue

Waseda Research Institute for Science and Engineering, Faculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo, Japan

Instituto de Astrofísica de Andalucía, (CSIC), Glorieta de la Astronomía s/n., Granada, Spain

Yolanda Jiménez-Teja

Observatório Nacional, (MCTI), Rua Gal. José Cristino 77, São Cristóvão, Rio de Janeiro, Brazil

School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA

Rogier A. Windhorst

Division of Physics, Faculty of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, Japan

Takuya Hashimoto

Tomonaga Center for the History of the Universe (TCHoU), University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, Japan

Department of Physics, Graduate School of Science, Nagoya University, Furo, Chikusa, Nagoya, Japan

Yoichi Tamura

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Angela Adamo .

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Adamo, A., Bradley, L.D., Vanzella, E. et al. Bound star clusters observed in a lensed galaxy 460 Myr after the Big Bang. Nature (2024). https://doi.org/10.1038/s41586-024-07703-7

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  • Introduction
  • Article Information

The dotted vertical line indicates the Dobbs v Jackson Women’s Health Organization decision.

eTable. Diagnosis and Billing Codes Used to Identify Tubal Ligation, Vasectomy, and Encounters for Evaluation and Management (E&M)

Data Sharing Statement

  • Permanent Procedures to Prevent Pregnancy in US Jumped After Dobbs JAMA Medical News in Brief June 4, 2024 Emily Harris
  • Error in Figure JAMA Health Forum Correction May 10, 2024

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Ellison JE , Brown-Podgorski BL , Morgan JR. Changes in Permanent Contraception Procedures Among Young Adults Following the Dobbs Decision. JAMA Health Forum. 2024;5(4):e240424. doi:10.1001/jamahealthforum.2024.0424

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Changes in Permanent Contraception Procedures Among Young Adults Following the Dobbs Decision

  • 1 Department of Health Policy and Management, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
  • 2 Center for Innovative Research on Gender Health Equity, Department of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
  • 3 Department of Health Law, Policy, & Management, Boston University School of Public Health, Boston, Massachusetts
  • Medical News in Brief Permanent Procedures to Prevent Pregnancy in US Jumped After Dobbs Emily Harris JAMA
  • Correction Error in Figure JAMA Health Forum

On June 24, 2022, the US Supreme Court’s decision in Dobbs v Jackson Women’s Health Organization overturned the constitutional right to abortion, permitting states to further restrict or ban abortion care. As of January 2024, 21 states have done so. 1 This structural barrier to exercising control over pregnancy and childbearing will indirectly affect contraceptive decision-making.

Early research has documented increased demand for permanent contraception in the months following Dobbs , including tubal sterilization and vasectomy. 2 , 3 This change may reflect fears of restricted access to abortion and/or contraception. However, no research, to our knowledge, has evaluated the differential effect of Dobbs on permanent contraception among men relative to women or among younger adults who are more likely to have an abortion and to experience sterilization regret. 4 , 5 We therefore evaluated changes in tubal ligation and vasectomy following Dobbs among younger adults.

We used data from the TriNetX platform for this cross-sectional study. These continuously updated medical record data are largely from academic medical centers and affiliated clinics in all 4 US census regions. We used an interrupted time series study design, fitting seasonally adjusted segmented autoregressive models to assess level and slope changes in procedure rates before (January 1, 2019, to May 31, 2022) and after (June 1, 2022, to September 30, 2023) Dobbs . Sensitivity analyses with a truncated pre- Dobbs observation window (April 1, 2021, to May 31, 2022) were conducted using Stata, version 17.1 (StataCorp LLC). This research was deemed exempt from review and the need for informed consent by the Boston University Institutional Review Board owing to the use of deidentifed patient data. We followed the ( STROBE ) reporting guideline.

Using monthly aggregate counts of tubal ligations and vasectomies, we calculated rates per 100 000 person-months among female and male patients aged 18 to 30 years. Individuals with an encounter for evaluation and management each month and no permanent contraception documented previously were included in the denominator. Visits for evaluation and management, tubal sterilization, and vasectomy procedures were identified using Current Procedural Terminology and International Statistical Classification of Diseases, Tenth Revision codes (eTable in Supplement 1 ). Two-sided P < .05 indicated statistical significance.

Observed permanent contraception procedure rates, estimates, and seasonally adjusted models for 22 063 348 person-months (36.9% male and 63.1% female) are presented in the Figure . Prior to Dobbs , the monthly permanent contraception rate increased by 2.84 and 1.03 procedures per 100 000 person-months among female and male patients, respectively ( Table ). Dobbs was associated with an immediate level increase of 58.02 procedures and 5.31 procedures per month among female patients. Among male patients, it was associated with a level increase of 26.99 procedures and no significant change in the number of procedures per month. Findings were robust to sensitivity analyses.

We observed an abrupt increase in permanent contraception procedures among adults aged 18 to 30 years following Dobbs . The increase in procedures for female patients was double that for male patients. These patterns offer insights into the gendered dynamics of permanent contraceptive use and may reflect the disproportionate health, social, and economic consequences of compulsory pregnancy on women and people with the capacity to become pregnant.

This study has several limitations. The TriNetX platform does not capture state or health care organization identifiers. We were therefore unable to assess the potential outcomes of state abortion policy or account for changes in the sample attributable to fluctuations in the organizations contributing data over the study period. Additionally, our findings do not provide insight into the differential experiences of Black, Indigenous, Hispanic, disabled, immigrant, and low-income women, who disproportionately encounter interference and coercion in their contraceptive decision-making. 6

The abrupt increase in permanent contraception rates may indicate a policy-induced change in contraceptive preferences. Dobbs may have also increased a sense of urgency among individuals who were interested in permanent contraception before the decision. Changes in contraceptive decision-making must be considered to understand the short- and long-term implications of Dobbs on reproductive autonomy.

Accepted for Publication: February 7, 2024.

Published: April 12, 2024. doi:10.1001/jamahealthforum.2024.0424

Correction: This article was corrected on May 10, 2024, to correct the y-axis label in the Figure.

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Ellison JE et al. JAMA Health Forum .

Corresponding Author: Jacqueline E. Ellison, PhD, 130 De Soto St, Pittsburgh, PA 15261 ( [email protected] ).

Author Contributions: Dr Ellison had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ellison, Morgan.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Ellison, Brown-Podgorski.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Ellison, Morgan.

Administrative, technical, or material support: Ellison, Morgan.

Supervision: Ellison.

Conflict of Interest Disclosures: None reported.

Data Sharing Statement: See Supplement 2 .

The Lasting Impacts of Middle School Principals

Using rich Texas administrative data, we estimate the impact of middle school principals on post-secondary schooling, employment, and criminal justice outcomes. The results highlight the importance of school leadership, though striking differences emerge in the relative importance of different skill dimensions to different outcomes. The estimates reveal large and highly significant effects of principal value-added to cognitive skills on the productive activities of schooling and work but much weaker effects of value-added to noncognitive skills on these outcomes. In contrast, there is little or no evidence that middle school principals affect the probability a male is arrested and has a guilty disposition by raising cognitive skills but strong evidence that they affect these outcomes through their impacts on noncognitive skills, especially those related to the probability of an out-of-school suspension. In addition, the principal effects on the probability of engagement in the criminal justice system are much larger for Black than for nonBlack males, corresponding to race differences in engagement with the criminal justice system.

This research has been supported by the Laura and John Arnold Foundation, the Smith Richardson Foundation, and CALDER The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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MIT researchers introduce generative AI for databases

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A new tool makes it easier for database users to perform complicated statistical analyses of tabular data without the need to know what is going on behind the scenes.

GenSQL, a generative AI system for databases, could help users make predictions, detect anomalies, guess missing values, fix errors, or generate synthetic data with just a few keystrokes.

For instance, if the system were used to analyze medical data from a patient who has always had high blood pressure, it could catch a blood pressure reading that is low for that particular patient but would otherwise be in the normal range.

GenSQL automatically integrates a tabular dataset and a generative probabilistic AI model, which can account for uncertainty and adjust their decision-making based on new data.

Moreover, GenSQL can be used to produce and analyze synthetic data that mimic the real data in a database. This could be especially useful in situations where sensitive data cannot be shared, such as patient health records, or when real data are sparse.

This new tool is built on top of SQL, a programming language for database creation and manipulation that was introduced in the late 1970s and is used by millions of developers worldwide.

“Historically, SQL taught the business world what a computer could do. They didn’t have to write custom programs, they just had to ask questions of a database in high-level language. We think that, when we move from just querying data to asking questions of models and data, we are going to need an analogous language that teaches people the coherent questions you can ask a computer that has a probabilistic model of the data,” says Vikash Mansinghka ’05, MEng ’09, PhD ’09, senior author of a paper introducing GenSQL and a principal research scientist and leader of the Probabilistic Computing Project in the MIT Department of Brain and Cognitive Sciences.

When the researchers compared GenSQL to popular, AI-based approaches for data analysis, they found that it was not only faster but also produced more accurate results. Importantly, the probabilistic models used by GenSQL are explainable, so users can read and edit them.

“Looking at the data and trying to find some meaningful patterns by just using some simple statistical rules might miss important interactions. You really want to capture the correlations and the dependencies of the variables, which can be quite complicated, in a model. With GenSQL, we want to enable a large set of users to query their data and their model without having to know all the details,” adds lead author Mathieu Huot, a research scientist in the Department of Brain and Cognitive Sciences and member of the Probabilistic Computing Project.

They are joined on the paper by Matin Ghavami and Alexander Lew, MIT graduate students; Cameron Freer, a research scientist; Ulrich Schaechtle and Zane Shelby of Digital Garage; Martin Rinard, an MIT professor in the Department of Electrical Engineering and Computer Science and member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Feras Saad ’15, MEng ’16, PhD ’22, an assistant professor at Carnegie Mellon University. The research was recently presented at the ACM Conference on Programming Language Design and Implementation.

Combining models and databases

SQL, which stands for structured query language, is a programming language for storing and manipulating information in a database. In SQL, people can ask questions about data using keywords, such as by summing, filtering, or grouping database records.

However, querying a model can provide deeper insights, since models can capture what data imply for an individual. For instance, a female developer who wonders if she is underpaid is likely more interested in what salary data mean for her individually than in trends from database records.

The researchers noticed that SQL didn’t provide an effective way to incorporate probabilistic AI models, but at the same time, approaches that use probabilistic models to make inferences didn’t support complex database queries.

They built GenSQL to fill this gap, enabling someone to query both a dataset and a probabilistic model using a straightforward yet powerful formal programming language.

A GenSQL user uploads their data and probabilistic model, which the system automatically integrates. Then, she can run queries on data that also get input from the probabilistic model running behind the scenes. This not only enables more complex queries but can also provide more accurate answers.

For instance, a query in GenSQL might be something like, “How likely is it that a developer from Seattle knows the programming language Rust?” Just looking at a correlation between columns in a database might miss subtle dependencies. Incorporating a probabilistic model can capture more complex interactions.   

Plus, the probabilistic models GenSQL utilizes are auditable, so people can see which data the model uses for decision-making. In addition, these models provide measures of calibrated uncertainty along with each answer.

For instance, with this calibrated uncertainty, if one queries the model for predicted outcomes of different cancer treatments for a patient from a minority group that is underrepresented in the dataset, GenSQL would tell the user that it is uncertain, and how uncertain it is, rather than overconfidently advocating for the wrong treatment.

Faster and more accurate results

To evaluate GenSQL, the researchers compared their system to popular baseline methods that use neural networks. GenSQL was between 1.7 and 6.8 times faster than these approaches, executing most queries in a few milliseconds while providing more accurate results.

They also applied GenSQL in two case studies: one in which the system identified mislabeled clinical trial data and the other in which it generated accurate synthetic data that captured complex relationships in genomics.

Next, the researchers want to apply GenSQL more broadly to conduct largescale modeling of human populations. With GenSQL, they can generate synthetic data to draw inferences about things like health and salary while controlling what information is used in the analysis.

They also want to make GenSQL easier to use and more powerful by adding new optimizations and automation to the system. In the long run, the researchers want to enable users to make natural language queries in GenSQL. Their goal is to eventually develop a ChatGPT-like AI expert one could talk to about any database, which grounds its answers using GenSQL queries.   

This research is funded, in part, by the Defense Advanced Research Projects Agency (DARPA), Google, and the Siegel Family Foundation.

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How Pew Research Center Uses Its National Public Opinion Reference Survey (NPORS)

In 2020, Pew Research Center launched a new project called the  National Public Opinion Reference Survey (NPORS) . NPORS is an annual, cross-sectional survey of U.S. adults. Respondents can answer by paper, online or over the phone, and they are selected using address-based sampling from the United States Postal Service’s Computerized Delivery Sequence File. The response rate to the latest NPORS was 32%, and previous years’ surveys were designed with a similarly rigorous approach. 

NPORS estimates are separate from the  American Trends Panel  (ATP) – the Center’s national online survey platform. Pew Research Center launched NPORS to address a limitation that researchers observed in the ATP. While the ATP was well-suited for the vast majority of the Center’s U.S. survey work, estimates for a few outcomes were not in line with other high-quality surveys, even after weighting to demographics like age, education, race and ethnicity, and gender.

For example, in 2018, roughly one-quarter of U.S. adults were religiously unaffiliated (i.e., atheist, agnostic or “nothing in particular”), according to the General Social Survey (GSS) and the Center’s own telephone-based polling . The ATP, however,  estimated the religiously unaffiliated rate at about 32%. The Center did not feel comfortable publishing that ATP estimate because there was too much evidence that the rate was too high, likely because the types of people willing to participate in an online panel skew less religious than the population as a whole. Similarly, the ATP estimate for the share of U.S. adults identifying as a Democrat or leaning to the Democratic Party was somewhat higher than the rate indicated by the GSS and our own telephone surveys .

From 2014 to late 2020, the Center approached these outcomes slightly differently. We addressed the political partisanship issue by weighting every ATP survey to an external benchmark for the share of Americans identifying as a Republican, Democrat or independent. For the benchmark, we used the average of the results from our three most recent national cellphone and landline random-digit-dial (RDD) surveys. 

During this time period, ATP surveys were not weighted to an external benchmark for Americans’ religious affiliation. The ATP was used for some research on religious beliefs and behaviors, but it was not used to estimate the overall share of Americans identifying as religiously affiliated or unaffiliated, nor was it used to estimate the size of particular faith groups, such as Catholics, Protestants or the Church of Jesus Christ of Latter-day Saints. NPORS allows us to improve and harmonize our approach to both these outcomes (Americans’ political and religious affiliations). 

Design and estimates

Read our fact sheet to find the latest NPORS estimates as well as methodological details. Data collection for NPORS was performed by Ipsos from 2020 through 2023 and is now performed by SSRS. 

Why is the NPORS response rate higher than most opinion polls?

Several features of NPORS set it apart from a typical public opinion poll. 

  • People can respond offline or online.  NPORS offers three different ways to respond: by paper (through the mail), online, or by telephone (by calling a provided phone number and speaking to a live interviewer). The paper and telephone options bring in more conservative, more religious adults who are less inclined to take surveys online.
  • Monetary incentives.  When sampled adults are first asked to respond to NPORS online, the mailing contains a $2 incentive payment (cash visible from the outside of the envelope) and offers a $10 incentive payment contingent on the participant completing the survey. When nonrespondents to that first stage are sent the paper version of the survey, the mailing contains a visible $5 bill. These incentives give people a reason to respond, even if they might not be interested in the questions or inclined to take surveys in general. 
  • Priority mailing.  The paper version of the survey is mailed in a USPS Priority Mail envelope, which is more expensive than a normal envelope, signaling that the contents are important and that the mailing is not haphazard. It helps people distinguish the survey from junk mail, increasing the likelihood that they open and read what is inside. 
  • Low burden.  The NPORS questionnaire is intentionally kept short. It’s about 40 questions long, including demographics such as age, gender and education. This means that NPORS takes about seven minutes to finish, while many polls take 10 minutes or longer. 
  • Bilingual materials.  In parts of the country with sizable shares of Hispanic Americans, the materials are sent in both English and Spanish. 
  • No requirement to join a panel.  NPORS respondents are not required to join a survey panel, which for some people would be a reason to decline the request. 

These features are not possible in most public polls for a host of reasons. But NPORS is designed to produce estimates of high enough quality that they can be used as weighting benchmarks for other polls, and so these features are critical.

Why a ‘reference’ survey for public opinion?

The “R” in NPORS stands for “reference.” In this context, the term comes from  studies  in which researchers calibrate a small sample survey to a large, high-quality survey with greater precision and accuracy. Examples of reference surveys used by researchers include the Census Bureau’s American Community Survey (ACS) and the Current Population Survey (CPS). NPORS is not on the scale of the ACS or CPS, nor does it feature face-to-face data collection. But it does have something that those studies lack: timely estimates of key public opinion outcomes. Other studies like the American National Election Survey (ANES) and the General Social Survey collect key public opinion measures, but their data is released months, if not years, after data collection. The ANES, while invaluable to academic researchers, also excludes noncitizens who constitute about 7% of adults living in the U.S. and are included in the Center’s surveys.

NPORS is truly a reference survey for Pew Research Center because researchers weight each American Trends Panel wave to several NPORS estimates. In other words, ATP surveys refer to NPORS in order to represent groups like Republicans, Democrats, religiously affiliated adults and religiously unaffiliated adults proportional to their share of the U.S. population. The ATP weighting protocol also calibrates to other benchmarks, such as ACS demographic figures and CPS benchmarks for voter registration status and volunteerism.

Pew Research Center is weighting on political party affiliation, but isn’t that an attitude?

It’s correct that whether someone considers themselves a Republican or a Democrat is an attitude, not a fixed characteristic, such as year of birth. But there is a way to weight on political party affiliation even though it is an attitude and without forcing the poll’s partisan distribution to align with a benchmark. 

Pew Research Center started implementing this approach in 2021. It begins with measuring the survey panelists’ political party affiliation at a certain point in time (typically, each summer). Ideally, the reference survey will measure the same construct at the same point in time. We launched NPORS because we control its timing as well as the American Trends Panel’s timing, allowing us to achieve this syncing.

NPORS and ATP measurements of political party are collected at approximately the same time each summer. We may then conduct roughly 25 surveys on the ATP over the next year. For each of those 25 surveys, we append the panelists’ party affiliation answers from the summer  to the current survey. To illustrate, let’s say that a survey was conducted in December. When researchers weight the December ATP survey, they take the measurement of party taken in the summer and weight that to the NPORS estimates for the partisan distribution of U.S. adults during the summer time frame. If, for example, Democrats were more likely than Republicans to respond to the December survey, the weighting to the NPORS target would help reduce the differential partisan nonresponse bias. 

Critically, if the hypothetical December poll featured a fresh measurement of political party affiliation (typically asked about three times a year on the ATP), the new December answers do  not  get forced to any target. The new partisan distribution is allowed to vary. In this way, we can both address the threat from differential partisan nonresponse and measure an attitude that changes over time (without dictating the outcome). Each summer, the process starts anew by measuring political party on the ATP at basically the same time as the NPORS data collection. 

Is the NPORS design connected to the American Trends Panel?

A key feature of NPORS is that respondents are not members of a survey panel. It is a fresh, random sample of U.S. adults. This matters because some people are willing to take a onetime survey like NPORS but are not interested in taking surveys on an ongoing basis as part of a panel. That said, in certain years, NPORS serves as a recruitment survey for the ATP. After the NPORS questions, we ask respondents if they would be willing to take future surveys. People who accept and those who decline are both part of the NPORS survey. But only those who consent to future surveys are eventually invited to join the ATP.

Can other survey researchers use NPORS?

Yes. As a nonprofit organization, we seek to make our research as useful to policymakers, survey practitioners and scholars as possible. As with the Center’s other survey work, the estimates and data are freely available. 

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Federalist Papers: Primary Documents in American History

Full text of the federalist papers.

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The Federalist , commonly referred to as the Federalist Papers, is a series of 85 essays written by Alexander Hamilton, John Jay, and James Madison between October 1787 and May 1788. The essays were published anonymously, under the pen name "Publius," in various New York state newspapers of the time.

The Federalist Papers were written and published to urge New Yorkers to ratify the proposed United States Constitution, which was drafted in Philadelphia in the summer of 1787. In lobbying for adoption of the Constitution over the existing Articles of Confederation, the essays explain particular provisions of the Constitution in detail. For this reason, and because Hamilton and Madison were each members of the Constitutional Convention, the Federalist Papers are often used today to help interpret the intentions of those drafting the Constitution.

The Federalist Papers were published primarily in two New York state newspapers: The New York Packet and The Independent Journal . They were reprinted in other newspapers in New York state and in several cities in other states. A bound edition, with revisions and corrections by Hamilton, was published in 1788 by printers J. and A. McLean. An edition published by printer Jacob Gideon in 1818, with revisions and corrections by Madison, was the first to identify each essay by its author's name. Because of its publishing history, the assignment of authorship, numbering, and exact wording may vary with different editions of The Federalist .

The electronic text of The Federalist used here was compiled for Project Gutenberg by scholars who drew on many available versions of the papers.

One printed edition of the text is The Federalist , edited by Jacob E. Cooke (Middletown, Conn., Wesleyan University Press, 1961). Cooke's introduction provides background information on the printing history of The Federalist; the information provided above comes in part from his work.

This web-friendly presentation of the original text of the Federalist Papers (also known as The Federalist) was obtained from the e-text archives of Project Gutenberg. Any irregularities with regard to grammar, syntax, spelling, or punctuation are as they exist in the original e-text archives.

Table of Contents

No. Title Author Publication Date
1. Hamilton For the --
2. Jay For the --
3. Jay For the --
4. Jay For the --
5. Jay For the --
6. Hamilton For the --
7. Hamilton For the --
8. Hamilton From the Tuesday, November 20, 1787
9. Hamilton For the --
10. Madison Frm the Friday, November 27, 1787
11. Hamilton For the --
12. Hamilton From the Tuesday, November 27, 1787
13. Hamilton For the --
14. Madison From the Friday, November 30, 1787
15.  Hamilton For the --
16. Hamilton From the Tuesday, December 4, 1787
17.  Hamilton For the --
18. Hamilton and Madison For the --
19. Hamilton and Madison For the --
20. Hamilton and Madison From the Tuesday, December 11, 1787
21. Hamilton For the --
22. Hamilton From the Friday, December 14, 1787
23. Hamilton From the Tuesday, December 17, 1787
24. Hamilton For the --
25. Hamilton From the Friday, December 21, 1787
26. Hamilton For the --
27. Hamilton From the Tuesday, December 25, 1787
28.  Hamilton For the --
29. Hamilton From the Thursday, January 10, 1788
30. Hamilton From the Friday, December 28, 1787
31. Hamilton From the Tuesday, January 1, 1788
32. Hamilton From the Thursday, January 3, 1788
33. Hamilton From the Thursday, January 3, 1788
34. Hamilton From the Friday, January 4, 1788
35. Hamilton For the --
36. Hamilton From the Tuesday, January 8, 1788
37. Madison From the Friday, January 11, 1788
38.  Madison From the Tuesday, January 15, 1788
39.  Madison For the --
40. Madison From the Friday, January 18, 1788
41. Madison For the --
42. Madison From the Tuesday, January 22, 1788
43. Madison For the --
44. Madison From the Friday, January 25, 1788
45. Madison For the --
46.  Madison From the Tuesday, January 29, 1788
47. Madison From the Friday, February 1, 1788
48. Madison From the Friday, February 1, 1788
49. Hamilton or Madison From the Tuesday, February 5, 1788
50. Hamilton or Madison From the Tuesday, February 5, 1788
51. Hamilton or Madison From the Friday, February 8, 1788
52.  Hamilton or Madison From the Friday, February 8, 1788
53. Hamilton or Madison From the Tuesday, February 12, 1788
54. Hamilton or Madison From the Tuesday, February 12, 1788
55.  Hamilton or Madison From the Friday, February 15, 1788
56. Hamilton or Madison From the Tuesday, February 19, 1788
57. Hamilton or Madison From the Tuesday, February 19, 1788
58. Madison -- --
59. Hamilton From the Friday, February 22, 1788
60. Hamilton From the Tuesday, February 26, 1788
61. Hamilton From the Tuesday, February 26, 1788
62.  Hamilton or Madison For the --
63. Hamilton or Madison For the --
64. Jay From the Friday, March 7, 1788
65. Hamilton From the Friday, March 7, 1788
66.  Hamilton From the Tuesday, March 11, 1788
67.  Hamilton From the Tuesday, March 11, 1788
68. Hamilton From the Friday, March 14, 1788
69.  Hamilton From the Friday, March 14, 1788
70.  Hamilton From the Friday, March 14, 1788
71. Hamilton From the Tuesday, March 18, 1788
72.  Hamilton From the Friday, March 21, 1788
73.  Hamilton From the Friday, March 21, 1788
74.  Hamilton From the Tuesday, March 25, 1788
75. Hamilton For the --
76. Hamilton From the Tuesday, April 1, 1788
77. Hamilton From the Friday, April 4, 1788
78. Hamilton From McLEAN's Edition, New York --
79. Hamilton From McLEAN's Edition, New York --
80. Hamilton From McLEAN's Edition, New York --
81. Hamilton From McLEAN's Edition --
82. Hamilton From McLEAN's Edition --
83. Hamilton From McLEAN's Edition --
84. Hamilton From McLEAN's Edition --
85. Hamilton From McLEAN's Edition --
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  • Last Updated: Apr 25, 2024 10:16 AM
  • URL: https://guides.loc.gov/federalist-papers

Staff Recognized for Outstanding Papers

July 5, 2024 , by Julian Cantella, M.A.

headshots of the recipients of Outstanding Paper awards.

Wen-Yi Huang, Jung Kim, Tongwu Zhang, Batel Blechter, Vicky Chang, Wayne Lawrence, Olivia Lee, Nina Rao, Nicole Rossi

Winners of DCEG's Outstanding Paper Award are selected based on research papers that have demonstrated impact, innovation, and clarity of thought and language. The following staff won this award for their 2023 publications, listed below.

Outstanding Paper by a Staff Scientist

Wen-Yi Huang, Ph.D., M.S.P.H. , Metabolic Epidemiology Branch (MEB) " GWAS Explorer, an open-source tool to explore, visualize, and access GWAS summary statistics in the PLCO Atlas ," published in  Science Data .

Jung Kim, Ph.D. , Clinical Genetics Branch " Germline pathogenic variants in neuroblastoma patients are enriched in BARD1 and predict worse survival ," published in the  Journal of the National Cancer Institute .

Tongwu Zhang, Ph.D. , Biostatistics Branch " Distinct Genomic Landscape of Lung Adenocarcinoma from Household Use of Smoky Coal ," published in the  American Journal of Respiratory and Critical Care Medicine .

Outstanding Paper by a Fellow

Batel Blechter, Ph.D., M.A. – Postdoctoral Fellow, Occupational and Environmental Epidemiology Branch (OEEB) " Polygenic Risk Score, Environmental Tobacco Smoke, and Risk of Lung Adenocarcinoma in Never-Smoking Women in Taiwan ," published in  JAMA Network Open .

Vicky Chang, Ph.D., M.P.H. – Research Fellow, OEEB " Glyphosate exposure and urinary oxidative stress biomarkers in the Agricultural Health Study ," published in the  Journal of the National Cancer Institute .

Wayne Lawrence, Dr.P.H., M.P.H. – Research Fellow, MEB " Trends in Mortality from Poisonings, Firearms, and All Other Injuries by Intent in the US, 1999-2020 ," published in  JAMA Internal Medicine .

Olivia Lee, Ph.D. – Predoctoral Fellow, Integrative Tumor Epidemiology Branch " Targeted long-read sequencing of the Ewing sarcoma 6p25.1 susceptibility locus identifies germline-somatic interactions with EWSR1-FLI1 binding ," published in the  American Journal of Human Genetics .

Nina Rao, Ph.D. – Postdoctoral Fellow, Laboratory of Translational Genomics (LTG) " Analysis of several common APOBEC-type mutations in bladder tumors suggests links to viral infection ," published in  Cancer Prevention Research .

Nicole Rossi, M.S. – Postbaccalaureate Fellow, LTG " Extrachromosomal Amplification of Human Papillomavirus Episomes as a Mechanism of Cervical Carcinogenesis ," published in  Cancer Research.

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  29. Research Guides: Federalist Papers: Primary Documents in American

    The Federalist, commonly referred to as the Federalist Papers, is a series of 85 essays written by Alexander Hamilton, John Jay, and James Madison between October 1787 and May 1788.The essays were published anonymously, under the pen name "Publius," in various New York state newspapers of the time. The Federalist Papers were written and published to urge New Yorkers to ratify the proposed ...

  30. Staff Recognized for Outstanding Papers

    Winners of DCEG's Outstanding Paper Award are selected based on research papers that have demonstrated impact, innovation, and clarity of thought and language. The following staff won this award for their 2023 publications, listed below. Outstanding Paper by a Staff Scientist. Wen-Yi Huang, Ph.D., M.S.P.H., Metabolic Epidemiology Branch (MEB)