Science / Engineering / Mathematics

Study offers new evidence that scientists are biased against women

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New study offers evidence that scientists -- men and women alike -- assume female students are less competent and less worthy of pay and mentoring than male students.

Study tracks erosion of conservative confidence in science

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Survey tracks long-term erosion in confidence in research -- and suggests that evolution and social issues aren’t the cause.

Cornell and Technion's win in New York competition reflects desire to grow urban ties

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Cornell's victory in New York City competition, and its intense desire to win, show the importance of urban ties for the future of research universities.

Debate over "overload" pay for professors

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Does it make sense for colleges that can't create new faculty lines to pay current professors more money to teach extra sections?

Essay on ways to prevent scientific misconduct

The most recent case of scientific fraud by Dutch social psychologist Diederik Stapel recalls the 2010 case against Harvard University of Marc Hauser, a well-respected researcher in human and animal cognition. In both cases, the focus was on access to and irregularities in handling of data. Stapel retained full control of the raw data, never allowing his students or colleagues to have access to data files.  In the case of Hauser, the scientific misconduct investigation found missing data files and unsupported scientific inference at the center of the accusations against him. Outright data fraud by Stapel and sloppy data management and inappropriate data use by Hauser underscore the critical role data transparency plays in preventing scientific misconduct.    

Recent developments at the National Science Foundation (and earlier this decade at the National Institutes of Health) suggest a solution — data-sharing requirements for all grant-funded projects and by all scientific journals. Such a requirement could prevent this type of fraud by quickly opening up research data to scrutiny by a wider community of scientists.

Stapel’s case is an extreme example and more likely possible in disciplines with substantially limited imperatives for data sharing and secondary data use.  The research traditions of psychology suggest that collecting your own data is the only sound scientific practice.  This tradition, less widely shared in other social sciences, encourages researchers to protect data from outsiders.  The potential for abuse is clear.  

According to published reports about Hauser, there were three instances in which the original data used in published articles could not be found. While Hauser repeated two of those experiments and produced data that supported his papers, his poor handling of data cast a significant shadow of uncertainty and suspicion over his work.

Hauser’s behavior is rare, but not unheard of. In 2008, the latest year for which data are available, the Office of Research Integrity at the U.S. Department of Health and Human Services reported 17 closed institutional cases that included data falsification or fabrication. These cases involved research funded by the federal government, and included the manipulation or misinterpretation of research data rather than the violation of scientific ethics or institutional oversight.

In both Hauser and Stapel's cases, graduate students were the first to alert authorities to irregularities.   Rather than relying on other members of a researcher’s lab to come forward (an action that requires a great deal of personal and professional courage,) the new data sharing requirements at NSF and NIH have the potential to introduce long-term cultural changes in the conduct of science that may reduce the likelihood of misconduct based on data fabrication or falsification. The requirements were given teeth at NSF by the inclusion of new data management plans in the scored portion of the grant application.

NIH has since 2003 required all projects requesting more than $500,000 per year to include a data-sharing plan, and the NSF announced in January 2011 that it would require all grant requests to include data management plans. The NSF has an opportunity to reshape scientists' behavior by ensuring that the data-management plans are part of the peer review process and are evaluated for scientific merit.  Peer review is essential for data-management plans for two reasons. First and foremost, it creates an incentive for scientists to actually share data. The NIH initiatives have offered the carrot for data sharing — the NSF provides the stick. The second reason is that the plans will reflect the traditions, rules, and constraints of the relevant scientific fields. 

Past attempts to force scientists to share data have met with substantial resistance because the legislation did not acknowledge the substantial differences in the structure, use, and nature of data across the social, behavioral and natural sciences, and the costs of preparing data. Data sharing legislation has often been code for, "We don’t like your results," or political cover for previously highly controversial issues such as global warming or the health effects of secondhand smoke. The peer review process, on the other hand, forces consistent standards for data sharing, which are now largely absent, and allow scientists to build and judge those standards.  "Witch hunts" disguised as data sharing would disappear.  

The intent of the data sharing initiatives at the NIH and currently at NSF has very little to do with controlling or policing scientific misconduct. These initiatives are meant to both advance science more rapidly and to make the funding of science more efficient. Nevertheless, there is a very real side benefit of explicit data sharing requirements: reducing the incidence of true fraud and the likelihood that data errors would be misinterpreted as fraud.

The requirement to make one’s data available in a timely and accessible manner will change incentives and behavior. First, of course, if the data sets are made available in a timely manner to researchers outside the immediate research team, other scientists can begin to scrutinize and replicate findings immediately. A community of scientists is the best police force one can possibly imagine. Secondly, those who contemplate fraud will be faced with the prospect of having to create and share fraudulent data as well as fraudulent findings.

As scientists, it is often easier for us to imagine where we want to go than how to get there.  Proponents of data sharing are often viewed as naïve scientific idealists, yet it seems an efficient and elegant solution to the many ongoing struggles to maintain the scientific infrastructure and the public’s trust in federally funded research. Every case of scientific fraud, particularly on such controversial issues such as the biological source of morality (which is part of Hauser’s research) or the sources of racial prejudice (in the case of Stapel) allows those suspicious of science and governments’ commitment to funding science to build a case in the public arena. Advances in technology have allowed the scientific community the opportunity to share data in a broad and scientifically valid manner, and in a way that would effectively counter those critics.

NIH and NSF have led the way toward more open access to scientific data.  It is now imperative that other grant funding agencies and scientific journals redouble their own efforts to force data, the raw materials of science, into the light of day well before problems arise. 

Felicia B. LeClere is a principal research scientist in the Public Health Department of NORC at the University of Chicago, where she works as research coordinator on multiple projects, including the National Immunization Survey and the National Children's Study.

Review of Beth Shapiro, "How to Clone a Mammoth: The Science of De-Extinction"

So it turns out that -- title notwithstanding -- Beth Shapiro’s How to Clone a Mammoth: The Science of De-Extinction (Princeton University Press) is not a do-it-yourself manual. What’s more, cloned mammoths are, in the author’s considered opinion, impossible. Likewise, alas, with regard to the dodo.

But How Not to Clone a Dodo would never cut it in the marketplace. Besides, the de-extinction of either creature seems possible (and in case of the mammoth, reasonably probable) in the not-too-distant future. The process involved won’t be cloning, per se, but rather one of a variety of forms of bioengineering that Shapiro -- an associate professor of ecology and evolutionary biology at the University of California at Santa Cruz -- explains in moderate detail, and in an amiable manner.

Her approach is to present a step-by-step guide to how an extinct creature could be restored to life given the current state of scientific knowledge and the available (or plausibly foreseeable) advances in technology. There are obstacles. Removing some of them is, by Shapiro’s account, a matter of time and of funding. Whether or not the power to de-exterminate a species is worth pursuing is a question with many parts: ethical and economic, of course, but also ecological. And it grows a little less hypothetical all the time. De-extinction is on the way. (The author allows that the whole topic is hard on the English language, but “resurrection” would probably cause more trouble than it’s worth.)

The subject tickles the public’s curiosity and stirs up powerful emotions. Shapiro says she has received her share of fan and hate mail over the years, including someone’s expressed wish that she be devoured by a flesh-eating mammal of her own making. Perhaps the calmest way into the discussion is by considering why reviving the mammoth or the dodo is possible, but would not be the same thing as cloning one. (And dinosaur cloning is also right out, just to make that part clear without further delay.)

To clone something, in short, requires genetic material from a living cell with an intact genome. “No such cell has ever been recovered from remains of extinct species recovered from the frozen tundra,” writes Shapiro, whose research has involved the search for mammoth remains in Siberia. Flash freezing can preserve the gross anatomy of a mammoth for thousands of years, but nucleases -- the enzymes that fight off pathogens when a cell is alive -- begin breaking down DNA as soon as the cell dies.

What can be recovered, then, is paleogenetic material at some level of dismantling. The challenge is to reconstruct an approximation of the extinct creature’s original genome -- or rather, to integrate the fragments into larger fragments, since rebuilding the whole genetic structure through cut-and-paste efforts is too complex and uncertain a task. The reconstituted strings of genetic data can then be “inserted” at suitable places in the genome of a related creature from our own era. In the case of the woolly mammoth, that would mean genetic material from the Asian elephant; they parted ways on the evolutionary tree a mere 2.5 million years ago. In principle, at least, something similar could be done using DNA from the taxidermy-preserved dodo birds in various collections around the world, punched into the pigeon genome.

“Key to the success of genome editing,” writes Shapiro, “has been the discovery and development of different types of programmable molecular scissors. Programmability allows specificity, which means we can make the cuts we want to make where we want to make them, and we can avoid making cuts that kill the cell.”

Cells containing the retrofitted genome could then be used to spawn a “new” creature that reproduces aspects of the extinct one -- pending the solution of various technical obstacles. For that matter, scraping together enough raw material from millennia past presents its own problems: “In order to recover DNA from specimens that have very little preserved DNA in them, one needs a very sensitive and powerful method for recovering the DNA. But the more sensitive and powerful method is, the more likely it is to produce spurious results.”

Also a factor is the problem of contamination, whether found in the sample (DNA from long-dead mold and bacteria) or brought into the lab in spite of all precautions. Shapiro leaves the reader aware of both the huge barriers to be overcome before some species is brought back from extinction and the strides being made in that direction. She predicts the successful laboratory creation of mammoth cells, if not of viable embryos, within the next few years.

It will be hailed as the cloning of an extinct animal -- headlines that Shapiro (whose experiences with the media do not sound especially happy) regards as wrong but inevitable. The reader comes to suspect one motive for writing the book was to encourage reporters to ask her informed questions when that news breaks, as opposed to trying to get her to speculate about the dangers of Tyrannosaurus rex 2.0.

Besides its explanations of the genetics and technology involved, How to Clone a Mammoth insists on the need to think about what de-extinction would mean for the environment. Returning the closest bioengineerable approximation of a long-lost species to the landscape it once inhabited will not necessarily mean a happy reunion. The niche that animal occupied in the ecosystem might no longer exist. Indeed, the ecosystem could have developed in ways that doom the creature to re-extinction.

Shapiro is dismissive of the idea that being able to revive a species would make us careless about biodiversity (or more careless, perhaps), and she comes close to suggesting that de-extinction techniques will be necessary for preserving existing species. But those things are by no means incompatible. The author herself admits that some species are more charismatic than others: we're more likely to see the passenger pigeon revived than, say, desert rats, even though the latter play an ecological role. The argument may prove harder to take for the humbler species once members of Congress decide to freeze-dry them for eventual relaunching, should that prove necessary.

By now we should know better than to underestimate the human potential for creating a technology that goes from great promise to self-inflicted disaster in under one generation. My guess is that it will take about that long for the horrible consequences of the neo-dodo pet ownership craze of the late 2020s to makes themselves fully felt.

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Essay argues that public universities, not privates, are key to engineering education

A colleague at the University of Illinois at Urbana-Champaign (where I am dean of the College of Engineering) recently emailed me Bloomberg’s interview with Harry Lewis, interim dean of Harvard University's Paulson School of Engineering and Applied Science. Lewis talked about the school’s plans for the $400 million gift it received in early June. My colleague highlighted Lewis’ description of an ascendant engineering program at Harvard and a cultural shift at the school in which “making things, doing useful things is no longer … considered the sort of thing that gentlemen and gentlewomen don’t do.”

My colleague added, “Welcome, Harvard, to the work that public research universities with great engineering schools have been doing for 150 years.” Sarcasm, apparently, isn’t the exclusive province of the Ivies. We heard it all over the place after the announcement of the Paulson gift. But, in my opinion, it’s misguided.

I’ll paraphrase venture capitalist (and University of Illinois alum) Marc Andreessen’s tweet on the topic. This gift and Harvard’s vision for what it wants to accomplish are “moral virtues, full stop.”

Harvard has set the standard for the liberal arts and sciences. Public institutions like the Universities of Illinois, California at Berkeley, and Michigan have done the same for world-class engineering education for the masses. That combination is extremely powerful, and it has made America the most innovative and prosperous country in the world.

Lewis made it clear that Harvard intends to redefine what a well-rounded education means in the 21st century. And John Paulson's investment allows the university to develop an engineering and applied science program to match Harvard’s reputation.

Harvard and similar private research universities lack one major virtue, however: excellence at scale.

Private institutions simply cannot satisfy the demands of 21st-century engineering alone. And turning away top talent is in no one’s interest.

It limits our nation’s economic growth, our ability to make the engineering profession more diverse, and our ability to help students find their true calling regardless of their socioeconomic background. However, growth in student numbers and innovations in how we educate them require more resources.

Given this fact, and the fact that state funding for public universities has declined precipitously in the last two decades, philanthropic support has become just as important to Illinois as it is to the Harvards of the world. Without new levels of philanthropy and new investment models, the American public research university, the world's golden goose, will not be able to deliver on its goal to ensure there are enough top-flight problem solvers available to advance our civilization and to look after our future.

Consider some of the very best engineering universities in the world, public and private. According to U.S. News and World Report, the schools with the most top-five-ranked undergraduate engineering specialties are the University of California at Berkeley, Massachusetts Institute of Technology, Stanford University, the University of Illinois, Georgia Tech and the University of Michigan. Meanwhile, Illinois, Berkeley and the University of Texas at Austin rank right alongside Stanford and MIT in the top five of the Academic Ranking of World Universities in Engineering/Technology and Computer Science from Shanghai Jiao Tong University.

But here’s the difference: Illinois and Georgia Tech each produce more world-class undergraduate engineers than Stanford, MIT and Caltech combined. And Berkeley, Michigan and Texas are each twice the size of Stanford.

Undergraduate Engineering Degrees Awarded, 2014

University Undergraduate Engineering Degrees
Georgia Tech 1,977
U of Illinois 1,782
U of Michigan 1,492
U of California at Berkeley 1,195
U of Texas at Austin 1,140
MIT 675
Stanford 545
California Institute of Technology 104

That isn’t to say that elite and exclusionary is still a universal condition at Harvard and other small, private institutions. As Lewis points out, Harvard’s demographics are changing with more rural and first-generation students. Students from these backgrounds tend to gravitate to engineering because it leads to a secure career. An engineering degree is rarely an opportunity to go into the family business. Instead, it’s a way for those from low-income backgrounds -- bright, marginalized and ambitious -- to invent the family business.

Thus, the art of engineering appeals to an ever-broader swath of students, from those interested in entrepreneurship to those creating solutions for the engineering challenges that underpin the modern world. For example, more than 3,100 students applied for about 200 slots in the Illinois computer science program this year. Carnegie Mellon receives twice that many applications for about 30 percent fewer seats.

With demand like that, we are all in an unparalleled position to serve a broad spectrum of students in ways we haven’t before. That’s not only a moral virtue for Harvard. It’s a moral virtue for all of us.

Students are driven by a desire to solve problems with real and lasting societal impact. Today, “making and doing” extend far beyond the disciplinary confines of engineering and the fine arts. With the Paulson gift, Harvard is in a unique position to bring down disciplinary boundaries, to inspire new curricula and experiential learning, and to transform the very concept of a university education.

I have no doubt that Harvard’s engineering and applied sciences program will catalyze such a transformational change. But will all that effort and all those resources transform Harvard’s educational model or the world’s?

Harvard has to take full advantage of this incredible opportunity, and so do the engineering powerhouses. Globally, more and more students recognize the sheer impact they can have by studying engineering. How do we support and serve them?

Even more students seek an education founded on disciplinary depth and enriched through cross-disciplinary experiences. How do we embrace their interests and turn them into the idea creators, the problem solvers and the makers of the new and the better?

How do we inspire them and empower them as they put ever more pervasive digital technology and ever more important engineering principles to work? What does that well-rounded and well-educated student of the 21st century look like?

These are questions for us to answer together, taking full advantage of our variety and our diverse strengths.

So welcome, Harvard, to the conversation.

Andreas Cangellaris is dean of the University of Illinois at Urbana-Champaign’s College of Engineering and the M. E. Van Valkenburg Professor of Electrical and Computer Engineering.

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2016 2nd International Conference on Knowledge Engineering

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Mon, 01/04/2016 to Wed, 01/06/2016

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Los Angeles
United States

Essay on how new Ph.D.s can ace informal interviews

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There may not be an opening, but there is opportunity, and you always need a strategy, writes Stephanie K. Eberle.

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