Researchers are more likely to write scientific papers with co-authors of the same gender, a pattern that can鈥檛 be explained by varying gender representations across scientific disciplines and time.

A new study from the 91探花 and Cornell University, recently published in , finds consistent gender homophily 鈥� the tendency of authors to collaborate with others who share their gender 鈥� in a digital collection of 560,000 published research articles over a 50-year period. While this observation is not new, researchers also used novel methods to rule out seemingly logical explanations for the pattern, such as a field鈥檚 gender balance or authorship norms for writing research papers.

The findings suggest a behavioral component is in play when scientists seek out collaborators.

鈥淩esearchers use social discretion when choosing their collaborators,鈥� said , co-author and associate professor of philosophy at the UW.听鈥淒o they express this by choosing same-gender co-authorship teams? How can we study this at a scale that includes multiple fields while also respecting听the diversity of authorship demographics and practices at finer-grained levels?”

The research team, comprised of scholars in statistics, information science, biology and philosophy, mined articles published between 1960 and 2011 from the online repository JSTOR. To help link genders to more than 800,000 author names, the team relied on social security records and crowdsourced data. Because of limitations in the data, this research was restricted to those who identify as men and women and didn鈥檛 include nonbinary and intersex identities.

The team then grouped authors from the same fields and eras, creating 50,000 hypothetical reconfigurations of authors.

鈥淲e re-simulated hypothetical datasets. Our thinking was: How different is what we actually observed versus these hypothetical scenarios that we constructed,鈥� said听, co-author and assistant professor at Cornell who was a doctoral student in statistics at the 91探花when he started this research. 鈥淰ery different, it turns out. This suggests that some other source of homophily is occurring in the data we observed.鈥�

The team can鈥檛 say definitively why researchers tend to collaborate with those of the same gender. Data science methods can鈥檛 measure intent, but Wang said the findings suggest consideration of gender may be a factor.

Other co-authors from the 91探花were , associate professor in the 91探花Information School; , professor of biology; and , professor of statistics and of social work. This research was supported by the National Science Foundation and the 91探花Royalty Research Fund.听

Adapted from a Cornell University press release.

For more information, contact Lee at c3@uw.edu and Erosheva at erosheva@uw.edu.

Three separate 91探花 research teams have been awarded $750,000 each by the National Science Foundation to advance studies in misinformation and the ocean economy.

The for phase 1 of the Convergence Accelerator program鈥檚 2021 cohort. The federal agency hopes to build upon basic research and discovery to accelerate solutions in two critical areas: the 鈥溾�� and 鈥�.鈥�

One team, from the 91探花Applied Physics Laboratory, was selected for the 鈥淣etworked Blue Economy鈥� track topic, and two 91探花teams 鈥� one from the 91探花Information School and another from the APL 鈥� were selected for the 鈥淭rust and Authenticity in Communications Systems鈥� track.

Designed to transition basic research and discovery into practice, the Convergence Accelerator uses innovation processes like human-centered design, user discovery, team science, and integration of multidisciplinary research and partnerships. The Convergence Accelerator, now in its third year, aims to solve high-risk societal challenges through use-inspired convergence research, according to NSF.

The three projects that teams from the 91探花will lead include:

• The 鈥溾�� project, from the APL and industry partners, will produce a flexible proof-of-concept technology to help people evaluate the source of information and its reliability. Drawing on the fields of technology development, law, business, policy, curriculum development, community management, interdisciplinary research and finance, the team will develop tools and components to generate and communicate digital 鈥渢rust signals鈥� in various settings. The result will be a proof-of-concept for a verified information exchange that would support tools that users can deploy to assess the trustworthiness and authenticity of digital information. Workstreams are anticipated to include food system safety and security, bank and financial information systems, public health information systems, academic publication and supply chains. , a principal research scientist at the APL, is the lead investigator.
• The 鈥溾�� project team, composed of a multidisciplinary set of researchers from the UW, the University of Texas at Austin, Washington State University, Seattle Central College and Black Brilliance Research, will plan, facilitate and assess a series of seven workshops focusing on critical reasoning skills, the psychological and emotional aspects of information, and broader sociocultural dimensions of trust in information ecosystems. The workshop series will be hosted in collaboration with a diverse group of local stakeholders in Washington state and Texas, including urban and rural libraries, news outlets, civic organizations, and underrepresented communities. , an Information School associate professor and 91探花 co-founder, is the principal investigator on the project.
• In the 鈥溾�� project, three new community-run ocean sensors will provide Indigenous coastal communities with real-time data on the changing ocean environment. The floating systems, anchored to the seafloor, will be deployed in collaboration with coastal communities in Alaska, the Pacific Northwest and the Pacific Islands. Sofar Ocean鈥檚 existing buoy systems 鈥� designed to be affordable and convenient 鈥� can measure waves, sea surface temperature, cloudiness of the water, and water depth, and come equipped with solar power, satellite communication and potential for expansion. The project housed under will be done through the UW-based as well as its counterparts in Alaska and the Pacific Islands, which have long-standing, trusted relationships with Indigenous and coastal communities. , an oceanographer at the APL and the director of NANOOS, is the lead investigator.

Additionally, Assistant Professor and Associate Professor , both in the 91探花Paul G. Allen School of Computer Science & Engineering, are co-principal investigators on a team, led by the international grassroots community . That team aims to develop practical interventions to help individuals and community moderators analyze information quality, including misinformation, to build trust and address vaccine hesitancy. Zhang also is on another , based at the University of Michigan, that will help media platforms determine how to flag articles that contain misinformation.

During phase 1, each 91探花team will engage with the other members of their cohort in a fast-paced, nine-month hands-on journey, which includes the program鈥檚 innovation curriculum, formal pitch and phase 2 proposal evaluation. The program鈥檚 team-based approach creates a 鈥渃o-opetition鈥� environment, stimulating the sharing of innovative ideas toward solving complex challenges together, while in a competitive environment to try and progress to phase 2.

At the end of phase 1, each team participates in a formal pitch and proposal evaluation. Selected teams from phase 1 will proceed to phase 2, with potential funding up to $5 million for 24 months. Phase 2 teams will continue to apply Convergence Accelerator fundamentals to develop solution prototypes and to build a sustainability model to continue impact beyond NSF support.听 By the end of phase 2, teams are expected to provide high-impact solutions that address societal needs at scale.

Launched in 2019, the NSF Convergence Accelerator program builds upon basic research and discovery to accelerate solutions toward societal impact. Using convergence research fundamentals and integration of innovation processes, it brings together multiple disciplines, expertise and cross-cutting partnerships to solve national-scale societal challenges.

When people think of misinformation, they often focus on popular and social media. But in a published April 12 in the Proceedings of the National Academy of Sciences, 91探花 faculty members Jevin West and Carl Bergstrom write that scientific communication 鈥� both scientific papers and news articles written about papers 鈥� also has the potential to spread misinformation.

The researchers note that this doesn’t mean that science is broken. “Far from it,” write , an associate professor at the 91探花Information School and the inaugural director, and , a 91探花biology professor and a CIP faculty member. “Science is the greatest of human inventions for understanding our world, and it functions remarkably well despite these challenges. Still, scientists compete for eyeballs just as journalists do.鈥�

91探花News asked West and Bergstrom to discuss misinformation in and about science. Their emailed responses are below:

91探花News: Many of us are familiar with the idea of fake news or misinformation on social media. Can you explain how some of these same concepts 鈥� such as hype and hyperbole, bias, filter bubbles and echo chambers and data distortion 鈥� also pop up in science and science communication? Why does this happen?

Science is run by humans, and humans respond to incentives. Scientists have strong incentives to be first to a result and to have their work noticed. Attention is a scarce resource. This creates an environment where scientists, universities, funders and journalists often hype their work more often than their results warrant. One example is an eye-catching paper title or a headline from a science journalist: 鈥淢uons upend all of physics.鈥�

Researchers used to visit libraries and browse printed journals to keep up on the latest scientific research, but this is largely a thing of the past. Today most researchers access the literature through search engines, recommender systems and, to some degree, social media platforms. That creates the same kind of filter bubble problems that we see in society more broadly. Platforms optimize engagement, and the best way to engage a person is to deliver content that grabs their attention. Although the effects are less pronounced in science, it is still an issue that is not well understood and requires more attention.

How does a crisis like COVID-19 further fuel these issues?

The COVID-19 crisis, like any major crisis, involves high levels of uncertainty especially at first. As we tried to understand what was happening with SARS-CoV-2 early in 2020, we were looking at a virus about which we had very little prior knowledge 鈥� it had never been in humans until just a few months before. In uncertain environments, people are especially eager for answers. This creates an uncertainty vacuum into which all sorts of nonsense flows.

While scientists take their time to understand the origin of the virus, conspiracy theorists provide ready-made answers. Those with specific agendas cherry-pick from the range of research results. Scientists strive to accelerate research by sharing work prior to peer review, but reporters and others do not always treat that work with due caution. Journals try to hasten the peer review process, but sometimes this results in low quality work slipping through.

Despite all these challenges, science has come through remarkably well. Within 15 months, 10 vaccines already have been developed, with more on the way. Scientists sequenced the genome in a matter of days, worked out the structure of the virus and its proteins in exquisite detail, and are using sequence data from around the globe to track the spread and evolution of the virus and its many variants. Despite the challenges noted in our article, science remains among the greatest human inventions for understanding our world.

The term “significant” has a unique meaning to the scientific community. Can you describe that difference? How does the push for significance affect scientific results and papers?

In the science community, 鈥渟ignificant鈥� generally refers to statistical significance 鈥� the idea that a research result is statistically unlikely under some null hypothesis. This is a tricky concept, not only for the public, but also for scientists. Statistical significance does not necessarily mean that the effect is of a meaningfully important size. The cutoffs for deciding statistical significance differ based on the type of data and the discipline. And once a threshold level of statistical significance becomes entrenched, humans find ways to game the system to reach it 鈥� trying different methods until something works, for example. These are major topics of discussion in science today, and researchers look for better ways to report the degree of statistical support that their results carry. Again, as with the other topics discussed in this article, it doesn鈥檛 mean science is broken. It just means that science is in an ongoing process of refinement and improvement.

Can you talk about what happens when scientists find negative or non-significant results? Why could this be a problem?

Negative results tend to be boring: This drug doesn鈥檛 cure a disease, this sensor does not detect its target, this chemical reaction fails to proceed, this explanation for a phenomenon is unfounded. As a result, people are less interested in reading them, journals are less interested in publishing them and consequently scientists often cut their losses and don鈥檛 bother submitting negative results for publication. But this creates problems of its own. If scientists preferentially publish positive results, the scientific record is not an unbiased picture of scientific discovery. The positive results are in journals for everyone to read, while the negative results are hidden away in file cabinets or, more recently, on file systems. Indeed false claims can even become established as fact. Bergstrom and colleagues in 2016.

Fortunately, science has recognized this problem over the last decade and has proposed some solutions . For example, some publishers encourage the publication of negative results. Some fields have adopted a system known as “registered reports,” where researchers submit their experiment for peer review before the results are available, and publishers agree before the work is done to publish the results regardless of whether the results end up positive or negative.

What are some interventions that can help reduce misinformation both in science and in communications about science?

The most important intervention is teaching the public what science is and what is not. This includes teaching about the history and philosophy of science. It requires having scientists themselves engaging in the public. It involves calling out predatory journals (non-peer-reviewed journals), being cautious with preprint papers, understanding the tactics of those pushing purposeful and disingenuous doubt about science (e.g., ), and paying special attention to health misinformation that looks like science but is often anything but.

With more people paying attention to science and preprints right now thanks to the COVID-19 pandemic, what are some steps the general public can take when looking at preprints or news stories about science?

The rise of preprints is a good thing for science. Instead of waiting years for results, research findings can be made available immediately. During the pandemic this has been critical. But this shortened time scale comes at a cost. Preprints are not peer-reviewed. Peer review can take months and even years, and it doesn鈥檛 guarantee foolproof results. But it does a reasonably good job at filtering out the crackpot papers and those with obvious problems.

The public and journalists have to be extra careful with preprints. There have been preprints during the pandemic that have spread across the media landscape, even though there have been major problems with the paper and even debunked by more credible experts. If referencing newly deposited pre-prints, readers should invest more time into investigating the author, lab and institution pushing the results. When sharing results from preprints, it is important to tag the paper as non-peer-reviewed.

That said, some of the worst and most damaging papers published during the pandemic have gone through peer review, including a paper at Lancet that led to the cancellation of clinical trials 鈥� and later turned out to be fraudulent 鈥� so we have to be careful not to let up our guard on the peer-reviewed literature as well.

For more information, contact West at jevinw@uw.edu or Bergstrom at cbergst@uw.edu.

The 91探花 today announced a $5 million investment from t to create the 91探花, led by an interdisciplinary group whose mission is to resist strategic misinformation, promote an informed society, and strengthen democratic discourse. The Center is also funded by a $600,000 award from the William and Flora Hewlett Foundation.

The Center brings together existing areas of excellence at the 91探花and builds upon the university鈥檚 ability to better understand how and why fake news, misinformation and disinformation are created. The Center will combat what researchers call the 鈥渕isinformation epidemic.鈥�

鈥淲e really see the Center as a university-wide effort,鈥� said, principal investigator and inaugural director for the Center. 鈥淢isinformation touches everything.鈥�

The 91探花Center is one of five institutions receiving major investments from the Knight Foundation nationally and is the only recipient in the Western United States.听

鈥淎 functioning democracy is an informed democracy,鈥� said Sam Gill, Knight Foundation vice president for communities and impact. 鈥� 91探花is bringing together leading scholars in computer science, sociology and law to equip our democracy with the right tools to navigate the digital age.鈥�

鈥檚 support to the 91探花is part of a $10 million effort announced in 2018 to examine and combat digital disinformation鈥檚 impact on U.S. democracy and elections.

Recent decades have seen a profound shift in the ways people, groups, and organizations produce and consume information and participate in public discourse. While many positive advancements have emerged from new technologies and platforms, the new information environments also have opened the door to misinformation, disinformation and fake news.

鈥淚t鈥檚 one of the most important problems of our time that we as a society need to solve,鈥� West said. 鈥淭his is not a left or right issue. This is an issue that transcends political boundaries. Everyone wants to get this right.鈥�

The principal investigators at the Center are a who鈥檚 who in this field of research, widely recognized for their respective expertise. In addition to West, co-director of DataLab, who is known for his Information School class 鈥淐alling B.S.: Data Reasoning in a Digital World,鈥� there are four researchers who will lead various initiatives for the Center:

• 听 听 , co-director the Social Media Lab, Information School;
• 听 听 , director of the Technology & Social Change Group (TASCHA), Information School;
• 听 听 , co-director of the Tech Policy Lab, School of Law; and,
• 听 听 , director of the Emerging Capacities of Mass Participation Lab (emCOMP), Human Centered Design & Engineering.

The Center will be devoted to educational efforts, research, policy and community outreach around misinformation and disinformation campaigns. Additionally, researchers will establish a network of Community Labs in public libraries and other institutions to co-create and assess research-based interventions.听听

Housed within the Information School, the Center for an Informed Public is scheduled to officially open in fall 2019.

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About the John S. and James L. Knight Foundation

Knight Foundation is a national foundation with strong local roots. We invest in journalism, in the arts, and in the success of cities where brothers John S. and James L. Knight once published newspapers. Our goal is to foster informed and engaged communities, which we believe are essential for a healthy democracy. For more, visit.

About the UW

The 91探花 was founded in 1861 and is one of the pre-eminent public higher education and research institutions in the world. The 91探花has more than 100 members of the National Academies, elite programs in many fields, and annual standing since 1974 among the top five universities in receipt of federal research funding. Learn more at uw.edu.

The will bring 91探花researchers from many fields together with public officials, corporate practitioners and others to discuss how the rise in exponential technologies such as artificial intelligence, machine learning, big data and Blockchain help build a healthy and ethical society.

The event will be from 8:30 a.m. to 6:30 p.m. at the Global Innovation Exchange (GIX), in the Steve Ballmer Building, 12280 NE District Way in Bellevue.

The event is co-hosted by the and GIX. Several Evans School听 faculty will attend and discuss their research, including , , and . of the Information School, co-creator of the iSchool’s popular “Calling BS” class and website, also will speak.

Giving an opening keynote will be , professor in the Department of Electrical & Computer Engineering and the , as well as co-executive director of GIX. , also of the Allen School, the eScience Institute and director of the Taskar Center for Accessible Technology, will speak as well.

Badshah of the Evans School, who is organizing the event, said the summit is already over capacity with 280 expected attendees. He said while other universities have convened such conversations among academics, companies or policyholders, this is the first such dialogue across multiple sectors.

The summit will feature sessions on social justice and equity, exponential technology and entrepreneurship and financial services, data mapping, health and societal transformation and more.

Also attending will be U.S. Rep. Susan DelBene, D-Wash., State Senator Manka Dhingra and members of the Bellevue City Council.

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For more information or for press access, contact Badshah at akhtarb@uw.edu.

On March 19, the iSchool will welcome more than 200 Seattle-area high school students for “,” a daylong workshop on how to navigate the misinformation landscape from and , the faculty duo who created the “Calling BS in the Age of Big Data” class and .

“MisInfo Day,” will be from 9:30 a.m. to 2:30 p.m. in the Husky Union Building’s North Ballroom.

West is an iSchool assistant professor, Bergstrom a professor of biology. Their most recent creation is , a website that helps users learn to tell real from fake images online.

The students 鈥� many of whom are studying government 鈥� will come from Nathan Hale, Franklin, Bellevue and Toledo high schools. Discussions will include defining misinformation and why we find it so compelling as well as “tips and tricks” for determining if news reports and social media posts are legitimate

The afternoon session will be an “Ask the Experts” panel, where the students will hear professionals from the Seattle Public Library, Snopes.com and the 91探花about their work. The students are asked to “come with questions about misinformation, fact-checking, confirmation bias and more.”

Other faculty and staff involved are:

• , iSchool assistant professor
• , 91探花librarian who manages the Information Science collection
• , assistant professor in the Department
• , assistant professor in the
• Liz Crouse, one of several students involved from the iSchool’s Masters of Library Science program, who assisted West in coordinating the event and will conduct pre- and post-program surveys of students for an ongoing research project. Other MLIS students will lead breakout sessions during the event.

Bergstrom and West’s “Calling BS” work has drawn wide attention from press as well as other institutions, some of whom have already expressed interest in holding events modeled on “MisInfo Day.”

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For more information, contact Maggie Foote, iSchool communications director, at 206-250-5992 or m2foote@uw.edu

Go ahead, give it a try. Look closely, study the context and click your answer, choosing which of two realistic headshots is actually a real photograph 鈥� and which is complete fakery.

How did you do? Don’t worry 鈥� read the site, and try again.

is the new website from of the 91探花 Information School and of the biology department, the duo who drew wide attention since 2017 for their innovative Information School class, “Calling Bullshit in the Age of Big Data.”

As with their Calling BS class, Bergstrom and West seek to address 鈥� and help people navigate 鈥� the increasing amount of misinformation and deception they see online. When the two saw the artificial intelligence-powered website 鈥� which renders extremely realistic portraits of utterly nonexistent people 鈥� they wanted to spread the word that the ability to generate believable, lifelike faces was now possible and proliferating online.

“We did not create the technology,” Bergstrom stressed. “We wanted to get the word out that this is now possible. Generally up to this point, we have trusted faces in photos: If it’s a photo, it’s a real person 鈥� at least up to this point.”

As Bergstrom and West explain on WhichFaceisReal, the “phenomenal” algorithm used to create realistic fake faces was developed by software engineers at NVIDIA Corporation and uses what is called a General Adversarial Network, where two neural networks “play a game of cat and mouse,” each trying to create artificial images and the other trying to tell the difference. “The two networks train one another,” they write. “After a few weeks, the image-creating network can produce images like the fakes on this website.”

And as with their Calling BS work, the website was immediately popular, with about 4 million “plays” of the game in about two weeks.

Are people guessing well? Mostly, yes, West said. Overall, so far, about 70 percent of players choose correctly when trying to distinguish fake from real 鈥� and the site may be helping them learn to do better.

“In our initial analysis this appears to be the case, but we need to verify this with more rigorous analysis,” West said. “We鈥檙e also looking into what kinds of images are the most difficult to discern. For example, are fake images of younger or older people more difficult to identify?”

There are a few hints and “tells,” however, that help one choose more wisely. Bergstrom and West offer advice in a tab on their site labeled “learn.” Look for inconsistencies in the background of the photo, or how the hair or eyeglasses are rendered.

And there is what they call the “silver bullet” to know fakes online: The algorithm used, called , is unable to generate multiple fake images from different perspectives of the same faux-person. So their advice is, to verify, look for a second photo of the same person.

Or as Bergstrom said, “How do you know if your next Tinder match is real? See if he has a nice headshot as well as a nice shot of himself petting a tiger. Always look for that tiger photo.”

West and Bergstrom plan to continue adding features to their site to add to the challenge of choosing between real and fake 鈥� they may remove backgrounds (which are among the “tells”) to make the choice harder, and will be asking users to view a single photo and say whether it’s real or generated.

“We want to bring public awareness to this technology,” said West. “Just like when people started to realize that you could Photoshop images, we want the public to know that AI can replicate human faces.

“That will hopefully make people start to question things they see in different ways. It will hopefully force us all to corroborate evidence even when we see a photo that looks human.”

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For more information, contact West at jevinw@uw.edu or Bergstrom at cbergst@uw.edu.

The class was conceived and is taught by iSchool assistant professor with biology professor . It’s a one-credit course offered through the iSchool as INFO 198 but listed also in the biology department, as BIOL 106B. The class will meet on Wednesday afternoons, with its first session on March 29.

When registration opened, the class reached its 160-student ceiling within one minute, like a rock concert selling out.

Each session will take up a different topic related to, well, BS. As the online shows, West and Bergstrom will start with definitions and “spotting BS,” followed by a session on “the natural ecology of BS.” Subsequent topics include causality, statistical traps, big data, publication bias and predatory publishing, fake news, and the ethics of calling and refuting BS.

In a lengthy online , the instructors say the class is not about any one party or politician 鈥� despite being “particularly timely today” 鈥� and will not seek to comment on the current political situation in the country or the world.

“This class is about how to spot bullshit and how to call it. It’s not about cataloguing all the bullshit out there, telling students what we think is bullshit in contemporary science and society, or calling bullshit on the most egregious cases,” said Bergstrom.

Examples to be used in class, he said, are those “that serve a pedagogical purpose” by showing ways BS is spread and demonstrating effective ways to refute it. Basically, they say, the course is about how numbers, statistics, data visualization models and algorithms are increasingly used for propagating BS, and how people can detect and it and avoid being taken in.

West and Bergstrom plan to hold a three-credit version of the class in fall quarter.

And though the class is for 91探花students, Bergstrom and West plan to edit their lectures into video clips and make them publicly available on the UW’s YouTube channel.

“We don鈥檛 care whether our students agree with our world views,” Bergstrom said, “but we do want them to have the skills to see through nonsense, form well-founded beliefs based on evidence and make their best arguments for those beliefs.”

West added, “Now, we need to make sure it as fun as a rock concert.”

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For more information, contact West at 206-543-2646 or jevinw@uw.edu, or Bergstrom at 206-685-3487 or cbergst@uw.edu.

The class was proposed by Information School assistant professor and biology professor , and has been approved as a one-credit special topics seminar for about 150 students in spring quarter, which starts on March 27.

“The response has been overwhelming. It seems to have struck a chord across the world,” said West. “We had tens of thousands of users to the class in just a few days of releasing the course.”

West told the Seattle Times the course webpage went live at midnight on Jan. 11. “We woke up the next morning and it was all over the whole planet. I’ve never seen anything like it 鈥� the response has been insane.”

Bergstrom and West say they hope to expand to a 3- or 4-credit class in the 2017-2018 school year. Those not enrolled will be able to watch as well; the two say they will have the lectures videotaped and made freely available on the internet.

West said, “It has clearly struck a chord with hundreds of thousands of people around the world.”

The course’s brief description, atop the online, is as blunt and compelling as its title: “Our world is saturated with bullshit,” it says. “Learn to detect and defuse it.”

Read recent coverage:

Seattle Times:

The Chronicle of Higher Education:

NPR Morning Edition:

KOMO radio:

KING 5: