It’s tempting to imagine a day when a politician is expected to explain to Parliament why some policy failed to produce the predicted outcomes. There is no way to get to this day without helping our scientists.
India’s political landscape is currently marred by widespread protests against laws the government recently passed, regarding citizenship and immigration. Internet shutdowns and the arbitrary application of Section 144 (which prohibits the assembly of more than four people in an area) have become the government’s go-to-strategies whenever it has anticipated dissent on these fronts, casually snuffing civil freedoms at will.
Against this volatile socio-political background, what must scientists do? To some of us, this seems like a time when engaging in research seems unfulfilling, if not entirely pointless. Is quitting science to become an activist the way to go?
Many people would argue that every individual, irrespective of their profession, should do what they can to protect the rights of their fellow citizens to express dissent, that everything else can wait. But it is at this time that scientists need to remember we play two major roles in society: researchers that advance and improve our understanding of the world, and educators that help create graduates who are proficient in their craft as well as are better citizens.
Science has little to do with the ability to remember (formulae, constants, theorems or diagrams) but sadly such expectations form the bulk of school-level science education. Research is all about curiosity founded on a fascination with the natural universe. If you’re curious about something, compelled to understand it down to its first principles and undertake systematic investigations, you’re a scientist. You don’t need a PhD to undertake research.
Your responsibilities as a professional scientist aren’t going to be very different, although you will have to deal with more sophisticated complications. Pick a problem, devise a solution you think might work, try different ways to solve the problem (often as a team), and finally convince a body of your peers that your solution actually works. There’s no shortage of problems to work on: air pollution, water shortage and climate change come swiftly to mind.
Some scientists, especially a majority of those whose careers peaked in the 1980s and 1990s, might contend that to solve these problems, we need the people working on them to be completely isolated from extra-scientific matters, including civilian engagement, and maintain single-minded focus.
At the end of the second decade of the 21st century, it’s safe to say that the expectations of scientists have changed somewhat. There is a greater acknowledgment that scientists are embedded in and work as part of a society, have an immutable stake in its overall wellbeing and, as a result, are expected to not wall themselves off. This is not unexpected. Democracy and research are intricately linked. The citizen’s ability to meaningfully question the government’s decisions influences the success of official policies, and scientists are citizens better equipped to ask some questions.
However, to hold the government accountable, citizens need to ask the right questions of their elected representatives; think critically about the government’s response, if one is provided; conclude whether the people’s representatives are holding up their end of the bargain based on the facts. The development of this will and ability to question, analyse arguments and assimilate information from multiple sources is what scientists need to inculcate in their – our – students, and right away.
There is currently a shortfall of such consultative and evidence-based policymaking when in fact there should be more. Some administrative factions might contend that centralising power and decision-making authority allows the government to act quickly, but consultations are a must when – for example – we’re faced with a problem with as many technical aspects as socio-political nuances like the climate emergency.
Public policy design in India could also learn from science’s (idealised) attitudes towards negative results – as in the saying “negative results are also results” – and feedback loops. A large swath of policymaking is not data-driven at the moment, instead being guided by ideological or electoral ambitions. The state governments and the Centre are also reluctant to track performance indicators to allow for dynamic alterations, often leaving stakeholders with no way to tell if a policy has actually been effective before its time is up or in fact much later.
Scientific research is best done as part of a community, with different subsets of people coming together to solve different problems. Many fields of study in India still don’t have such communities, although the situation has been improving of late. One of our responsibilities as researchers is to help create these groups, comprising students, scientists and other interested stakeholders (such as government officials, industry leaders, etc.). This is a challenging yet fulfilling task that has long-term value and is necessary in the current social context.
It’s tempting to imagine a day when a politician or policymaker is expected to explain to Parliament why this or that policy failed to produce the predicted outcomes, and their audience of lawmakers don’t engage in a blame-game as much as provides constructive criticism. And there is no way to get to this day without helping scientists today to learn more, teach more, and generally listening to them more.
Finally, reimagining scientists’ responsibilities both during and beyond periods of social and political upheaval along these lines must also be accompanied by a commitment to professionalism. Although we have a stake in the overall wellbeing of the community, we get paid to be researchers and educators, and have to make sure we fulfil our commitment to the profession – and not just to our students – before we can fulfil our commitment to society as well.
Manu Awasthi is an associate professor of computer science, Ashoka University, Sonepat. The views expressed here are the author’s own.
The station proves that sustainable living is possible anywhere.
As a scientist investigating climate change, I’m embarrassed by the high carbon footprint I have when I travel to, and work in, Antarctica. Researchers based in the UK regularly take four or five flights to reach the continent and the stations we visit rely on electricity from fossil fuels. Our food is shipped in and our waste is returned by ship to South Africa, South America or New Zealand. When we venture further afield for research and set up a temporary camp, a portable generator is flown in with us, along with our snowmobiles.
Antarctica is the most remote and inhospitable place on Earth, so it’s no surprise that people based there have struggled to break out of convenient habits. It’s cold. There are 24 hours of darkness in winter. Icicles build up on solar panels operating during the summer months and the concrete foundations for wind turbines won’t set in the cold. It’s expensive to ship in renewable energy components and it’s difficult to find warm and dry places to keep large batteries for storing energy.
These challenges are real, and yet, I’ve seen how they can be overcome at Antarctica’s only zero-emission research base, the Princess Elisabeth Antarctica Research Station in East Antarctica. The base is staffed during the summer season from October to March, when the majority of scientists – like me – conduct their research.
Take the tour
Dreamt up by the Belgian explorer Alain Hubert during his transantarctic crossing of the continent by kite ski in 1998, and constructed by the International Polar Foundation and its many partners, the Princess Elisabeth station has welcomed researchers since its first 2008-2009 summer research season.
The glinting silver pod looks like something from a James Bond film. It’s anchored by raised pylons, hovering above the East Antarctic Ice Sheet on a narrow granite ridge. In Antarctica these other-worldly structures are somewhat the norm. Raised, aerodynamic research stations litter the edge of the continent, where researchers from around the world gather to measure ice flows, the atmosphere and natural biomes.
While these stations all have similar traits, the Princess Elisabeth stands out. I have never seen anything like it. Almost every inch is covered in solar panels – on the roof, on the walls, on the side of sleeping containers. They are even screwed to frames anchored to the ground.
Solar panels have to be mounted high above the snow-covered ground to capture the 24 hours of daylight during the austral summer. Wind turbines are drilled into the granite ridge beneath the snow and ice, removing the need for large concrete foundations. Their blades are maintained with carefully designed polar lubricants, but they can shut down production during intense storms. These renewable energy sources melt snow for water, which is filtered and reused on site to reduce waste.
The whirl of nine wind turbines generates the reassuring sound of regular clean electricity on base. While other research stations have to use fossil fuels to keep station staff warm, fed and hydrated, the Princess Elisabeth station uses 100% renewable energy supplied by the sun, the wind, and plentiful frozen water.
There’s no need for conventional heating here either. Nine layers of cladding and insulation keep the biting Antarctic cold out, and the pleasant warmth of the station in. Every piece of electrical equipment runs on renewable energy. Even my hair dryer is powered by the almost constant Antarctic winds and summer daylight.
In order for the base to run as sustainably as possible, there’s a strict hierarchy for energy use on the base. Safety is the priority, so electricity for the doctor’s surgery, the base commander’s office, fire alarms, smoke detectors and satellite connections that can alert the need for outside help are maintained first. Basic human needs like food and water are a close second, while working facilities, like lights, microscopes and laptops come third.
Unnecessary luxuries like showering or laundry are at the bottom of the list for energy need priorities. We shower once or twice a week, using push-button showers to limit how much water we use. Everyone understands and respects these systems. We all come to Antarctica to experience one of the most enchanting natural environments on Earth, we don’t come here to pollute the environment.
When I asked Alain Hubert, the expedition leader, why he wanted to build a zero-emission base in Antarctica, he said that if we can do it here, we can show the world that it can be done anywhere. I hope life and work with no carbon emissions can become a reality for people everywhere. The Princess Elisabeth Antarctica Research Station shows us that these zero-emission lifestyles are within reach.
As the current holder of the prestigious Baillet Latour Antarctica Fellowship, I’ll be able to visit the station once more, in January 2020, to collect samples that will allow us to better understand the global carbon feedback cycle. By then, working there will become even more sustainable with new electric-powered snowmobiles. I can’t wait to try them out.
Kate Winter is a research fellow of Antarctic Science at Northumbria University, Newcastle.
MoS Jitendra Singh, however, said most components of technology demonstration, including the launch, orbital critical manoeuvres, lander separation, de-boost and rough braking phase were successfully accomplished.
New Delhi: Chandrayaan-2’s Vikram lander hard-landed as reduction in velocity during its descent was more than the designed parameters, the government said on Wednesday, throwing more light on the Indian Space Research Organisation’s dashed hopes of making a soft landing on the lunar surface in its maiden attempt.
In a written reply to a question in the Lok Sabha, Jitendra Singh, the minister of state in the Prime Minister’s Office, who looks after the department of space, said the first phase of descent was performed nominally from an altitude of 30 kms to 7.4 kms above the moon’s surface and velocity was reduced from 1,683 metres per second to 146 metres per second.
“During the second phase of descent, the reduction in velocity was more than the designed value. Due to this deviation, the initial conditions at the start of the fine braking phase were beyond the designed parameters. As a result, Vikram hard-landed within 500 metres of the designated landing site,” he said.
Singh, however, said most components of technology demonstration, including the launch, orbital critical manoeuvres, lander separation, de-boost and rough braking phase were successfully accomplished.
With regards to the scientific objectives, all the eight state-of-the-art scientific instruments of the orbiter are performing according to the design and providing valuable scientific data. Due to the precise launch and orbital manoeuvres, the mission life of the orbiter is increased to seven years, he said.
Data received from the orbiter is being provided continuously to the scientific community, he said, adding the same was recently reviewed in an all-India user meet organised in New Delhi.
The indigenously developed Chandrayaan-2 spacecraft comprising of orbiter, lander and rover was successfully launched on-board the indigenous GSLV MK III-M1 Mission on July 22.
After accomplishing four earth bound manoeuvres and trans-lunar injection, the spacecraft was successfully inserted in the lunar orbit on August 20. A series of moon-bound manoeuvres were then carried out to achieve a Lunar orbit of 119 x 127 km.
The Lander ‘Vikram’ was separated, as planned, from the Orbiter on September 2 2019. After two successful de-orbiting manoeuvres, powered descent of the lander was initiated on September 7 to achieve soft landing on the moon surface.
A recent study suggests that after prominent scientists die, their fields see an influx of work from lesser-known researchers.
New ideas advance in science not just because they are true, but because their opponents die, physicist Max Planck wrote in 1948. He was referring to a fundamental theory that, at the time, provoked a nasty feud, yet today is taught in nearly every high school physics classroom. The belief that science advances one funeral at a time is the kind of folk mythology in which any researcher might indulge in a discouraging moment, says Kevin Zollman, a philosopher of science at Carnegie Mellon University.
“It’s very comforting to imagine there’s some evildoer behind the scenes,” Zollman says wryly, “when your paper gets rejected.”
Older scientists aren’t notably worse at accepting revolutionary ideas compared to younger colleagues, research has found. But a paper published in August in the American Economic Review suggests there may be subtler ways in which the top dogs have a discouraging effect on new entrants. According to the paper, which draws on decades of data on more than 12,000 elite biology researchers, when a superstar scientist dies their field sees a small burst of activity in the form of fresh publications. What’s more, the authors of the new papers, which are more likely than usual to be highly cited, are typically newcomers who have never published in this subfield before.
The results imply that the deaths of important scientists may open up opportunities for fresh ideas, reaffirming Planck’s statement. But they also suggest that science is reassuringly robust; instead of fields getting into a rut, or even falling apart when a star dies, they continue to evolve.
The work that led to the new study began around 15 years ago, when the economists Joshua Graff Zivin of the University of California, San Diego and Pierre Azoulay of the Massachusetts Institute of Technology began investigating what happens to people who have published papers with biology superstars after the stars die. The researchers defined these elite scientists by criteria such as how highly they were cited, how well they were funded, how many patents they had been awarded, and whether they were members of the National Academy of Sciences. The researchers expected that after a death, the star’s collaborators might jockey for position in the field. Or they might nominate a particular member of the group as the new leader.
But looking through the subsequent publications of each collaborator, the economists were surprised. “We did not find that,” says Graff Zivin. “We saw that everyone who ever wrote with the star published less and less important work after the star had passed.”
Perhaps the star was the source of the innovative ideas in the group, then. But that left the economists wondering about the state of the star’s subfield as a whole. Did the death kill their little corner of biology as well? Or did other people who’d never worked with the star come in and pick up the slack?
For nearly a decade, the two researchers and their colleague Christian Fons-Rosen, an economist at the University of California, Merced, collected detailed data about scientists’ careers and considered the problem. A crucial breakthrough came when they devised a way to define subfields in biology using keywords in PubMed, the National Library of Medicine’s literature database. Papers using the same keywords represented the community of biologists looking at a particular research problem, whose members nevertheless might not all be collaborating or writing papers together. This allowed the economists to look at stars’ collaborators and other researchers separately. Then, the economists identified 452 stars who died prematurely while they were still active between 1975 and 2003 and asked what happened to the stars’ subfields afterwards.
In the first two years after a star’s death, publications in their subfields increased modestly. But as the years passed, breaking the numbers down by author showed a startling change: Papers by newcomers grew by 8.6 percent annually on average. At the same time, papers published by collaborators took a nosedive, decreasing by about 20 percent a year. After five years, growth from newcomers was so substantial, it made up for the deficit from the collaborators.
In other words, large swaths of these fields had essentially been turned over.
One possible interpretation: The new arrivals could be upending orthodoxy after the death of dogmatic elders. It’s an attractive narrative – who doesn’t like a tale of crusty arrogance defeated by fresh creativity? But Azoulay cautions: “We don’t really know whether they are coming in and turning against the superstar.”
The economists didn’t contact any of the newcomers to ask about their motivations or their timing in entering the field. Instead, the economists tried to get more detail about the nature of these changes indirectly by looking at how the newcomers cited other research in their papers. Intriguingly, newcomers referenced more work outside the subfield than usual, and they were also much less likely to cite work from the star who had died. “It’s still recognisably the same subfield,” says Azoulay, “but they are injecting it with different ideas.” The new papers also tended to be more highly cited than other work the newcomers had done in the past, suggesting scientific peers found the work useful. But Azoulay, Graff Zivin, and Fons-Rosen found no sign that these new papers were particularly disruptive.
In fact, Azoulay thinks these changes are probably not revolutionary – not paradigm shifts, as philosopher of science Thomas Kuhn dubbed transformative discoveries in his landmark 1962 book “The Structure of Scientific Revolutions.” Rather, the newcomers’ work is probably more like what Kuhn called the progress of “normal” science: the gradual morphing of consensus. What the numbers could be showing, then, is a detailed view of a scientific field’s natural evolution, paper by paper, over the course of decades.
Still, changes do come in the wake of a noteworthy death. “It remains significant that even the trajectory of normal science exhibits a dependence on the presence of individual scientist stars,” said Dean Simonton, who studies the psychology of science and scientists at the University of California, Davis. The stars did not seem to be obviously excluding others – only a tiny fraction were on journal boards or decision-making panels for grants, which would make them explicit gatekeepers when it came to scientific funding and publishing of new ideas.
But that would hardly be necessary, points out Aaron Clauset, a physicist and complexity scientist at the University of Colorado Boulder, who has studied the career trajectories of academics. “A superstar scientist doesn’t have to exert power themselves in order to be powerful,” he says. Many members of a scientific community are invested in the success of a star’s ideas, which are accepted because they’ve allowed research to advance. While the star lives, attention will be focused on them; ideas that don’t mesh with theirs are perhaps unlikely to get easy acceptance.
One driver of the pattern may be the exertion needed to get a new idea into a tight-knit field, suggests Zollman, the philosopher of science. “Scientists usually have way more ideas than they have time to work on,” he says. They might ask themselves, he adds, as they decide what to do next: “Is this so controversial that’s it going to take a lot of energy to get traction?” And outsiders may not be sure if their new approaches are useful and worth sharing.
But growing research suggests science benefits when a variety of methods are in play. “It’s really important to a given scientific field that there be more than one methodology available at a time,” Zollman says. The findings in the American Economic Review paper are phrased carefully, he adds, but they suggest “that there’s a danger when you have scientific superstars that they might needlessly reduce the diversity of methodologies in a field in a way that might be hampering scientific progress.”
Numbers from the National Institutes of Health (NIH) show that scientists are older than they used to be when they receive their first big research grants — in 1980 the average age was around 36, while in 2016 it was 42. The age researchers start their own labs has also been rising, as young scientists spend more time in the holding pattern of postdoctoral positions or leave academia for other pursuits.
A 2016 study from the NIH and the National Science Foundation (NSF) asked why older scientists received so much more grant money and found that younger scientists simply applied less often. These younger scientists may not have thought they had a decent enough chance to go for it.
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The new study is silent on exactly what might have been going on in the heads of the scientists, established and otherwise, who created the patterns over the 30-year period covered by the data. It’s impossible to say whether newcomers knew about the death and thought it was a good time to act or had no inkling of the star’s recent passing. It’s also not clear if some of the patterns may have come from journal editors who, dealing with a dearth of papers from the stars and their collaborators, started to admit new voices to fill the space. And the study doesn’t explore the possibility that the impetus might have been indirect, perhaps from a colleague who knew about the death and encouraged others to put forward new ideas.
Without more detail about why these patterns emerge, it’s hard to say what they mean for science. Still, perhaps one takeaway from the new research is that stars, who are often lauded for good reasons, may have more of a restraining effect than they know, says Zollman. The social structure of science, in which those with powerful ideas rise to the top and then stay there, may make a field less of a strict meritocracy than we usually imagine.
“Scientists love to talk about science and the social processes that go along with it because we just feel very viscerally that these social processes do shape the direction and taste and texture of science,” says Clauset. The paper confirms that feeling. Still, he goes on, the fact that fields neither fall to pieces nor experience cataclysmic shifts after a star departs is, in some ways, a testament to science’s ability to evolve slowly in the right direction, with an infusion of new voices gradually changing the status quo.
“In the long run,” Clauset suggests, “science figures it out.”
Veronique Greenwood is a science writer whose work has appeared in The New York Times, The Atlantic, National Geographic, and Aeon, among many others.
The irony is that being critical and argumentative is appropriate, even desirable behaviour, for scientists.
“Yes, sir, we all know you know everything about atoms!” a junior scientist exclaimed from the penultimate row. Some senior scientists sitting in the front row nodded in agreement, as if the setting was a military camp, not a meeting about subatomic physics in Mumbai. The more-senior scientist on the stage was more than pleased with this sentiment. With an approving smile, he replied loudly, “I can only thank god for being able to spread my work.”
Front row seats being reserved for grey-haired scientists, designated with ‘reserved’, ‘distinguished’, ’eminent’ and other pompous adjectives, with their younger counterparts relegated to the back benches in scientific conferences is typically something that plays out only in developing countries. It is obviously in bad taste considering the spirit of scientific temper. One would expect scientists – of all fields – to take themselves a little less seriously knowing we all live and work on a tiny blue dot in the larger scheme of things.
What is really detrimental to the scientific spirit is the attendant culture. In countries like India, there are many senior revered figures who are seldom open to healthy criticism, if at all, especially from younger scientists. They encourage and accommodate only praises and appreciation of their work at scientific events. There is no room for tough questions from research students or junior scientists, and critical comments from scientists of similar seniority and standing are often considered personal insults.
These scenes are in stark contrast to the conference atmosphere in the West. All the antics of seating people according to their experience is beyond question in any scientific conference or meeting of repute. Speakers, whether young or old, encourage critical questions from students and junior scientists (as long as they aren’t personally directed). On many occasions, distinguished scientists working in the West have expressed concern, even irritation, if there are no questions after a talk or if they find someone who agrees with them on everything.
For some senior Indian scientists attending top conferences in Europe or North America, this culture comes as a shock that forces them to exit their bubble, where they are surrounded by sycophants. In addition, bullying or threatening students and interns openly for critical questions is taken very seriously, quite unlike in India, where such behaviour is often a non-issue given the overt hierarchies at play.
In our culture, seniority is taken too seriously in professional environments, and not just in science. This attitude is to be found in all professions and professional environments. However, it would be more reassuring if scientists broke such barriers first, instead of waiting for other professionals to do it for us.
Some of the top autonomous research institutes in India do buck this trend and much of what has been said here does not apply to them. But there are still hundreds of research institutions and universities where this flavour of the colonial hangover persists. Such places are breeding grounds for yes-men researchers that make their way to the top without having ever challenged a senior colleague’s ideas or having had a healthy argument on any scientific matter. Outside India, there are many circles in which such a career would be considered futile.
Vice-chancellors, deans, heads of department and senior academics are treated like royalty when they present talks or results at meetings. Junior academics and students are often too intimidated to ask any questions or make any critical remarks about the speaker’s work. When they do, there is likely to be a repercussion, for example as a badly worded recommendation letter in the future, at least a sharp reprimand later in private.
The irony is that being critical and argumentative is appropriate, even desirable behaviour, for scientists.
Obviously these behaviour patterns are not going to change overnight, and it’s likely to be a few generations before these attitudes evolve socially for the better. Let us remember that scientists often lay claim to leading by example, so there should be no exception on this front as well. At the very least, we shouldn’t take anyone seriously if they can’t take a joke!
Two neuroscientists and a sociologist reflect on the mental health experiences of people in science.
When TheLifeOfScience.com approached us about an article for a series on mental health, I realised that we were in a unique position. Perhaps because of our lab’s scientific interest in psychiatric disorders such as anxiety and depression, discussions about the prevalent cultures in academia are frequent among us.
These are usually informal conversations in the lab, over tea, or on a walk around our lovely campus – personally, I cherish these experiences.
My advisor at TIFR Mumbai, Vidita Vaidya and I decided that it might be worthwhile to share a glimpse of these conversations. We envision that this could inspire more such conversations between the graduate student community, advisors and institutional leadership.
This involves opening ourselves to the uncomfortable debate of whether a PhD in STEM (Science, Technology, Engineering and Math) fosters working environments for graduate students that per se enhance risk for, or unmask, underlying mental health conditions.
My PhD work seeks to understand the neurocircuitry underlying anxiety and depression, something that my lab has been exploring from multiple angles for almost two decades. Since I started four years ago, I find that my perception and understanding of mental health challenges has changed substantially. My experiments have given me a sense that we have to expand our understanding of mental health disorders to incorporate a much bigger role for the environment in both shaping and unmasking underlying psychopathology. Environmental conditions play a critical role in both studies with animal models, and from clinical observations of patients.
The rest of this article documents a recent exchange between Vidita and I, where we spoke about the enhanced risk for mental health disorders amongst the graduate student community in STEM disciplines, and if things have changed over the years. Along the way, we also invited our sociologist friend Gita Chadha, to give us some key perspectives based on her engagement with studying scientific institutions and cultures.
Praachi Tiwari (author) is a PhD student at TIFR Mumbai.
Praachi: Everyone I know in graduate school – in India or abroad – knows at least one person directly impacted by mental health issues. I wonder if my perception of the scale of the crisis is coloured by these conversations, or is it really as bad as it seems?
Vidita: I have asked myself the same thing too, Praachi. We know that the World Health Organisation estimates the risk for psychiatric conditions at about 13% for the general population. And I remember being rather taken aback at a relatively recent study carried out for STEM departments across several institutions that suggested as high a possibility as 40% of graduate students dealing with some form of mental health issues. From my personal experiences as a Principal Investigator, and from conversations with students, I was well aware that there is indeed a problem, but seeing a number of that magnitude in a published survey really drove home further the fact that this is not a perceived crisis – this is a serious issue that does need attention.
Praachi: Then why is there a starkly enhanced risk for STEM graduate students? As a graduate student studying factors that affect vulnerability for psychiatric disorders, I am particularly curious about this.
Vidita: We need to directly address the possibility that stress associated with graduate school in the STEM disciplines may increase vulnerability for psychiatric disorders. Let me ask you this, Praachi, from all the conversations you have been privy to, can you think of particular milestones for a graduate student… time-points when stress is so amplified that they could be precipitating or exacerbating factors?
Praachi: Hmm… I’m not sure if this can be called a milestone, but the first few weeks of grad school can be pretty intimidating. Most of us make it here after having triumphed through substantial academic pressure and highly competitive exams. We may have been the local “stars” at our schools and colleges. But the steep transition from a college environment to that of a graduate programme can sometimes be overwhelming.
Vidita Vaidya is a professor at TIFR Mumbai.
Vidita: Can you elaborate, Praachi?
Praachi: For me, it was the constant feeling of not knowing enough. Right from school, we were consistently rewarded for knowing information. By the time we make it into graduate school, this pattern is so ingrained that we are strongly conditioned to have an inherent discomfort with not knowing something.
When I first came to TIFR, I must say, I felt out of place. Nobody had taught me to say “I don’t know”. It was never an acceptable statement. This can instil an ‘imposter syndrome’ which becomes hard to shed. It would really help if people further ahead in their scientific journey acknowledged openly how they felt during their initial years in graduate school. As someone who left an Indian education system for higher studies abroad, did you ever feel this way too, Vidita?
Vidita: You bet! In my first semester in grad school in the US, I was convinced I knew pretty much nothing about neuroscience, and you’re right – that feeling of ignorance can be rather overwhelming. All of us go through this to different degrees. Unfortunately, not knowing somehow gets equated with failure. Failure, especially for experimentalists, is an essential building block to scientific discovery. We expect graduate students to quickly accept failure as a part of their journey, without ever actively discussing our own engagement with failures.
The impact this can have on self-esteem is underestimated. Advisors would do well to drop this perceived ‘requirement’ of appearing invulnerable. In my personal experience, a willingness to admit to one’s own insecurities serves to open the door for stronger mentor-mentee relationships with grad students.
Praachi: I want to come back to this fish-out-of-water feeling; this gets really highlighted in an environment where you feel there is absolutely no one whom you can relate to. Things like gender, class, caste, sexuality, disability and language barriers can make the impostor syndrome much worse. In fact, before I came to TIFR, I spent a semester in another graduate programme where I experienced an unhealthy working environment. It took courage to extricate myself from that situation. It was because of other support structures – family and friends – that I could take the bold decision to quit. At that time, there were murmurs of disapproval that as a girl I hadn’t been able to handle a tough situation; but in reality, I know it took much more courage to take the decision to leave. I look around and see so many examples of friends who carry the burden of unfairly high expectations; they may even be poster children for their communities. In these situations, worsened by a lack of institutional support, it is no wonder that the stress gets overwhelming.
“When I decided to quit, there were murmurs of disapproval that as a girl I hadn’t been able to handle a tough situation; but in reality, I know it took much more courage to take the decision to leave.”
Praachi Tiwari
Vidita: Do you think having counsellors available on campus, as part of student bodies, on thesis committees that one can share one’s concerns with, helps in such situations?
Praachi: What can help is seeking mentorship from multiple quarters. These can be faculty members other than your advisor, colleagues from your lab or graduate students who are further along in their academic journey. However, few institutions nurture strong graduate community-based programmes or talk openly about student mental health. Institutes can correct this by incorporating students into decision-making bodies dealing with students’ issues. Done well, I have no doubt counsellors will be effective, but I have seen that academic counsellors don’t always respect confidentiality and this vitiates trust. We need counselling offices whose primary focus is on graduate students’ well-being.
But I think that few things can compare to being in an environment where we can have open discussions with other grad students or PIs. Unfortunately, seeking support from the advisor is often extremely difficult because there is a major power imbalance between graduate students and faculty. Do you have any thoughts about this as an advisor yourself?
Vidita: Absolutely. I think acknowledging the role of strained student-advisor relationships is critical in the grad school scenario. Students perceive that their scientific career trajectory is in the hands of the advisor, and this results in a feeling of powerlessness when the student-advisor relationship goes awry. The power equation is very steep in the direction of the advisor, and the onus should be on faculty to work to neutralise this as best as they can.
Yet, simply expecting universal good behaviour from faculty isn’t enough. Institutions have to put in effective checks and balances to run successful graduate programmes, with mentorship being a key valued trait for academic excellence. One way to check for this steep power-imbalance is to ensure that evaluations of faculty factor in 360-degree feedback, with former and current mentees having a chance to opine on the quality of training and mentorship received as a component of the faculty evaluation process. However, this works only if there is actually a consequence, one that the institution can stand by to ensure that the future generation of scientists have a voice that is actually heard.
Praachi: One of the things that benefited me at TIFR was the fact that there were lab rotations in the first year. Thanks to the rotations, I got to experience labs and working styles of PIs before I made my choice. I didn’t have access to this in my previous grad school experience, so there I was focused solely on the project, funding, how long it will take to finish, and so on. I learned the importance of my working environment, the hard way. Choosing a mentor was a key factor in helping me enjoy my experience of grad school. There is almost a feeling of having lucked out if you end up with a positive mentee-mentor equation! This is viewed as the exception and not the norm.
Vidita: I relate very well to this. I often say that I am lucky… that by some stroke of fate, I had amazing mentors in grad school who continue to have my back years later. It matters immeasurably to have this support, and yet we all keep referring to this as ‘good luck’. However, if we look world over there are some institutions, labs, individuals that seem to do this more effectively than others, and have nurtured entire generations of scientists, who then pay it forward. And this brings us to a question that I often find myself struggling with: Is the culture prevalent in STEM today weeding out the very sort of people we should be doing our best to retain? In the headlong rush for rewarding productivity, are we losing individuals who focus on mentorship and nurture of scientific creativity? It helps if advisors and mentors demonstrate healthy work-life balance themselves, and guard against valorising untenably long hours. We rarely open ourselves up to the possibility that the practice and culture of STEM itself could be studied, and to ask if there are corrective measures to better our own academic working environments. We tend to isolate ourselves from the humanities like sociology of science, and unfortunately, this isolation has come at a cost.
Praachi: This seems like a good time to pull in Gita Chadha, who is a feminist sociologist who has worked in the area of critical science studies. Gita, would you say there is something about the culture of STEM academic disciplines that increases the risk for mental health disorders?
Gita Chadha is a sociologist at University of Mumbai.
Gita: The statistics you have cited for STEM indicate that there must be something specific to the cultures of STEM that can be correlated to a compromised sense of well-being in the community. The fact that you are asking this question, Praachi, is a significant shift in the way we look at mental health, and I thank you for making this shift. Conventionally, we tend to think of mental health as predominantly determined by psychological and biological processes. It’s important to also see mental health as a function of social structures and cultures. We require a paradigm shift on how we perceive mental health in our worlds. Counselling and medical services, which need to be instituted, must come with a social understanding of mental health rather than put the entire onus of personal well-being on the individual. We can relate this to the larger cultures of modernity in our worlds where we place an unnatural emphasis on individual achievement and success.
“We require a paradigm shift on how we perceive mental health in our worlds.”
Gita Chadha
Prachi: You’re right, but how do we think this through in the context of STEM cultures, where success is often measured by productivity, through impact factors of journals published in, citation indices and such? Is there a way out of this?
Gita: In academic domains, particularly in the sciences, our cultures reward individual ’genius’ and promote a culture of competition. We assume that ‘healthy’ competition is the only way to promote scientific productivity. So, individuals are rewarded for excellence. This must change, particularly in fields where it is possible to reward groups, laboratories and collaborations. We need to promote a social imagination of science and see it as a human activity that is done in and by groups of people rather than by isolated individuals.
But Praachi, let me push the argument even further, into the domain of the ‘how’ and ‘what’ of the production of scientific knowledge itself. I’d like to suggest, however idealistic it might sound, that a holistic relationship between human beings and nature is crucial to our sense of ease and well being. When this relationship is constructed in anthropocentric terms, we dis-ease ourselves, and nature too. STEM fields often do so. We need to understand that science must become a deeply ethical enterprise that sees human beings as part of nature. A stronger connection between human beings and nature is central to our personal sense of well-being. Scientific institutions and cultures, unfortunately, often imagine science and the scientist, in opposition to nature.
A holistic relationship between human beings and nature is crucial to our sense of ease and well being. When this relationship is constructed in anthropocentric terms, we dis-ease ourselves, and nature too. STEM fields often do so.
Gita Chadha
Praachi: How do you think this can be changed or dealt with, while including students in the process of dealing with such issues?
Gita: It is important to first, integrate social science and humanities within the curriculum of graduate studies in the fields of STEM. An awareness of the historical, philosophical, social and political context of science and scientific theories would go a long way in putting measure on the absolute value of science in the minds of young people. But more importantly, this will help in creating an enabling environment for students who come from marginal social locations of gender, caste, class, disability and sexuality. If we sincerely want to make a more inclusive culture of science, it is important to promote ideas of social justice in scientific communities. While we have created a discourse of science as being above all social bias against people, we find that scientific cultures reproduce social bias at every level of their practice.
Vidita: This makes a lot of sense, Gita. The point you made about social bias is highly relevant because, more often than not, science – and by extension scientists – are viewed as highly rational and hence incapable of reproducing the biases that run rampant in society in general. This is patently untrue, but is a commonly held perception which can then prevent the calling out of deep-seated issues and biases in the scientific community that require remedial action.
Praachi: Thanks for this chat, Vidita and Gita. I hope sharing this with the wider audience will serve to seed further conversations amongst all stake-holders concerned about mental health for STEM graduate students. I just want to add that I am struck by the fact that some of the issues we highlighted today also resonate with insights gained from studies in animal models of psychiatric disorders, some of which Vidita and I work on in our lab. Work from many groups has highlighted the high cost of social isolation in setting up dysfunctional responses in neurocircuits that regulate mood behaviour. Stress alone may not result in a mental health challenge, but when it is overlaid with the continuous feeling of having no control over changing the stressful situation, it can serve as a major risk factor in setting up a state referred to as learned helplessness. Remarkably, work in the field also indicates that simply having the percept of control over terminating the stress, and hence making it relatively predictable, can be a powerful factor to promote resilience. While one has to be cautious in simply extending the observations in animal models directly to humans, this body of literature does inform us of the importance of feeling like one has some control over stressful environments and experiences. This chance to write up our chat and discussion has left me wanting more of such dialogues at all levels.
Praachi Tiwari is a fourth-year PhD student at Tata Institute of Fundamental Research, Mumbai. Her research interests encompass understanding the mechanisms that regulate susceptibility to anxiety and depression. She also studies the regulation of hallucinations by serotonin receptors. When not in the lab, Praachi loves travelling, dancing and is a food aficionado.
Vidita Vaidya is a faculty member in the Department of Biological Sciences at TIFR and works on the neurocircuitry of emotion. She is committed to diversity and inclusion in academia. When not in the lab, Vidita is happiest curled up with a book and a good pot of masala chai.
Gita Chadha is a faculty member at the Department of Sociology at the University of Mumbai and has also provided inputs for the piece. Her research interests include sociological theory, cultural studies and feminist science studies. She has published extensively and co-edited two book volumes, Feminists and Science: Critiques and Changing Perspectives in India. Gita is also a closet poet, and knows the nooks and crannies of Bombay better than many.
More than 100 years after Harvard employed 80 female “computers” who studied the stars, a new team of women are documenting their discoveries.
More than 100 years after Harvard employed 80 female “computers” who studied the stars, a new team of women are documenting their discoveries.
Curator Lindsay Smith Zrull places a glass plate photograph of a section of the sky onto a lightbox. Smith Zrull recently discovered boxes of notebooks belonging to early women astronomers who studied the glass plates as early as 1885. Credit: Alex Newman/PRI via Global Voices
In a cramped Harvard University sub-basement, a team of women is working to document the rich history of their predecessors.
More than 40 years before women in the US gained the right to vote, women laboured in the Harvard College Observatory as “computers” – astronomy’s version of NASA’s “Hidden Figures” mathematicians.
Between 1885 and 1927, the observatory employed about 80 women who studied glass plate photographs of the stars, many of whom made major discoveries. They found galaxies and nebulas and created methods to measure distance in space. In the late 1800s, they were famous: newspapers wrote about them and they published scientific papers under their own names, only to be virtually forgotten during the next century. But a recent discovery of thousands of pages of their calculations by a modern group of women working in the very same space has spurred new interest in their legacy.
Surrounded by steel cabinets stuffed with hundreds of thousands of plate glass photographs of the sky, curator Lindsay Smith Zrull shows off the best of the collection.
“I have initials but I have not yet identified whose initials these are,” Smith Zrull says, pointing at a paper-sized glass plate crowded with notes taken in four different colors. “One of these days, I’m going to figure out who M.E.M. is.”
A dozen women computers hold hands in this 1918 photograph, which Smith Zrull calls the “paper doll” photo. To the far right is Edward Pickering, who hired the women computers. Credit: Courtesy Harvard College Observatory, Plate Stacks via Global Voices
Each glass plate is stored in a paper jacket and initialed to show who worked on it, but for decades no one kept track of the women’s full names. So Smith Zrull started a spreadsheet about 18 months ago and adds initials when she discovers new ones and then tries to locate the full names in Harvard’s historical records.
“I’m slowly starting to piece together who was who, who was here when, what they were studying,” she says. Smith Zrull has about 130 female names and about 40 are still unidentified.
Not all are computers. Her list has grown to include assistants and, in some cases, astronomers’ wives who helped with their husbands’ work.
Curatorial assistant Anne Callahan inspects a plate before it is cleaned for scanning. She makes sure the metadata from the paper jacket is properly entered into the computer before the plate goes to be wiped down and then scanned. Credit: Alex Newman/PRI via Global Voices
“We know there were at least 80 women who worked in this space on these glass plate photographs, which is a pretty amazing number considering women were still trying to get social approval to go to college, let alone work in the sciences,” Smith Zrull said.
In the Plate Stacks at the Harvard-Smithsonian Center for Astrophysics — the modern version of what was once called the Harvard College Observatory — Smith Zrull oversees a digitization project to make the glass plates available to the world. Since 2005, a custom-built scanner has been making its way through the collection of more than half a million plates from 1885 to 1993. The team scans 400 plates per day — they’re at about the halfway point now — and Smith Zrull estimates about three years of scanning remains.
‘People forgot they were there’
Last fall Smith Zrull turned her attention to about 30 notebooks in the plate stacks belonging to the women computers.
“I started to realize a lot of these books were missing,” she says. “I started doing a little bit of digging and eventually came across some proof that we might have boxes in storage off-site, which is very common for libraries around Harvard.”
Smith Zrull found 118 boxes, each containing between 20 and 30 books. Inside were more notebooks from the women computers and notebooks from astronomers who predated photography and made hand-drawn sketches of planets and the moon.
“People didn’t know they existed when they were in storage,” Smith Zrull says. “As different curators came and went here, I suppose people forgot they were there. Now that we know they exist, we can make them accessible to the public, they can be cataloged in a library so people can come across them.”
The books had moved from one library to the plate stacks to another library to a book depository, essentially lost to history until Smith Zrull began looking for more information on the women computers.
To resurrect their legacy, she enlisted the help of librarians from the Wolbach Library in the Center for Astrophysics. The librarians prepared to manually go through the boxes and begin the labor-intensive process of cataloging them. Project PHAEDRA (an acronym for Preserving Harvard’s Early Data and Research in Astronomy).
‘OK, we’ve hit pay dirt’
Then Smith Zrull made another discovery in the plate stacks: a handwritten catalog of the books from 1973.
“At some point in 1973, someone who we assume is named ‘Joe Timko’ went through all of these boxes at an item level and recorded as much information as he could find,” says head librarian Daina Bouquin. “We have no sense of why this was done or what became of the person who did this, but we thought, ‘OK, we’ve hit pay dirt.’”
This is the envelope Smith Zrull found in the plate stacks that included a handwritten catalog of all of the women computer’s notebooks. A person named Joe Timko painstakingly went through the collection in 1973. Credit: Alex Newman/PRI via Global Voices
Then someone found a typewritten version of the 1973 catalog, adorned with a Post-it saying “Finally done! Rachel.” On the very last page was a handwritten path to a computer file, a spreadsheet on a Harvard server that hadn’t been accessed since 2001.
The discovery sped up the digitisation project by months, if not years.
“We went from having absolutely no metadata, like 30 characters on each box, to having item-level, machine-readable, type-written metadata that we could then edit and clean up and turn into real records,” explains Bouquin. “Thank you Joe Timko and possibly Rachel, wherever they may be.”
The library has completed transcription of about 200 volumes. Right now, notebooks from two women are listed on the Smithsonian Transcription Center website. There are many more to come — nearly 2,300 out of a total 2,500 books — but the work has begun. Bouquin hopes the public will help transcribe the books, but anticipates it will still be years before everything is readable.
“You’ll be able to do a full-text search of this research,” Bouquin says. “If you search for Williamina Fleming, you’re not going to just find a mention of her in a publication where she wasn’t the author of her work. You’re going to find her work.”
Bouquin, left, and Smith Zrull, right, hold up an original image of Williamina Fleming posing in the plate stacks in a 1891 photo that was the first photo used in bestselling author Dava Sobell’s 2016 book, “The Glass Universe.” Smith Zrull says they know the 1891 image is posed because a window is closed and the tool Fleming is using to study a plate only works with window light. Credit: Alex Newman/PRI via Global Voices
‘She’s the one who really found it’
Fleming is the first famous woman computer. Fleming emigrated to the US from Scotland in the late 1870s. While pregnant, she was abandoned by her husband and found work as a maid in the home of Edward Pickering, the observatory director. In 1881, Pickering hired Fleming to work in the observatory. She would go on to discover the Horsehead Nebula, develop a system for classifying stars based on hydrogen observed in their spectra and lead more female computers.
Wolbach Library unveiled a new display case in early July showcasing Fleming’s work. The case includes pages from her diary as well as her work on the plates showing the nebula and the log book containing that discovery.
The display case in Wolbach Library includes pages from a journal kept by Fleming; a portrait of her that librarians chose because she describes buying a hat (but not necessarily the one pictured) in the diary; and one of the recently-discovered logbooks, opened to the page where she noted the Horsehead Nebula for the first time. Credit: Courtesy Daina Boquin, Wolbach Library via Global Voices
“When the [Horsehead Nebula] was discovered, it was just a little ‘area of nebulosity in a semi-circular indentation,’” says librarian Maria McEachern, who has helped the team sort through the notebooks to find the more interesting pieces. “That’s how it was described at the time. It wasn’t until years later that it became known as the Horsehead Nebula and one of the male scientists at another institution who named it was the one who got credit for it. It wasn’t even until recently that people have been doing more scholarship and finding out that, yes, she’s the one who really found it.”
But Fleming was just the first of many to become famous.
Pickering hired Henrietta Swan Leavitt in 1895. She was tasked with measuring and cataloguing the brightness of the stars. Her major discovery: a way to allow astronomers to measure distance in space, now known as “Leavitt’s Law,” an attempt to give her credit for her work.
Annie Jump Cannon joined the observatory in 1896 and worked there until 1940. Cannon created the Harvard Classification System for classifying stars, which is the basis of the system still in use today.
Cecilia Payne-Gaposchkin came to the Observatory in 1923 and earned a doctorate from Radcliffe in 1925, but she struggled to get recognition from Harvard. For years she had no official position, serving as a technical assistant to then-director Harlow Shapley from 1927 to 1938. It wasn’t until the mid-1950s that she became a full professor and later, the first woman to head a department at Harvard.
Payne-Gaposchkin’s notebooks will be the next set scanned and submitted for transcription. (Leavitt and Cannon’s notebooks are in the process of being transcribed.)
‘They’ve always been there’
“I like to think resilience goes a long way, but I think some of these women go a little above and beyond what we think of when we think of overcoming things,” Bouquin says.
Both Bouquin and Smith Zrull said they want to give young girls more role models like the Harvard computers — role models who weren’t well-known when they were young.
“Yes, look at Sally Ride, look at modern women who people associate with the space-based sciences, but go back further,” Bouquin says. “They’ve always been there. As long as they could be, they were there.”
Smith Zrull — who hated history as a teen — said she struggled to find women who encouraged her.
“It really took me a long time to start to find women who I felt were like me, who did important things,” Smith Zrull said. “I think more women need to know, you’re not alone, you can do it.”
This story originally appeared on Global Voices. Read the original here.
On scientific method, the work of Sir Francis Bacon – the key progenitor of modern science – and whether scientific discovery can be automated.
On scientific method, the work of Sir Francis Bacon – the key progenitor of modern science – and whether scientific discovery can be automated.
Cometh the man; Francis Bacon’s insight was that the process of discovery was inherently algorithmic. Credit: NPG/Wikipedia
The duty of man who investigates the writings of scientists, if learning the truth is his goal, is to make himself an enemy of all that he reads and … attack it from every side. He should also suspect himself as he performs his critical examination of it, so that he may avoid falling into either prejudice or leniency. ∼ Ibn al-Haytham (965-1040 CE)
Science is in the midst of a data crisis. Last year, there were more than 1.2 million new papers published in the biomedical sciences alone, bringing the total number of peer-reviewed biomedical papers to over 26 million. However, the average scientist reads only about 250 papers a year. Meanwhile, the quality of the scientific literature has been in decline. Some recent studies found that the majority of biomedical papers were irreproducible.
The twin challenges of too much quantity and too little quality are rooted in the finite neurological capacity of the human mind. Scientists are deriving hypotheses from a smaller and smaller fraction of our collective knowledge and consequently, more and more, asking the wrong questions, or asking ones that have already been answered. Also, human creativity seems to depend increasingly on the stochasticity of previous experiences – particular life events that allow a researcher to notice something others do not. Although chance has always been a factor in scientific discovery, it is currently playing a much larger role than it should.
One promising strategy to overcome the current crisis is to integrate machines and artificial intelligence in the scientific process. Machines have greater memory and higher computational capacity than the human brain. Automation of the scientific process could greatly increase the rate of discovery. It could even begin another scientific revolution. That huge possibility hinges on an equally huge question: can scientific discovery really be automated?
I believe it can, using an approach that we have known about for centuries. The answer to this question can be found in the work of Sir Francis Bacon, the 17th-century English philosopher and a key progenitor of modern science.
The first reiterations of the scientific method can be traced back many centuries earlier to Muslim thinkers such as Ibn al-Haytham, who emphasised both empiricism and experimentation. However, it was Bacon who first formalised the scientific method and made it a subject of study. In his book Novum Organum (1620), he proposed a model for discovery that is still known as the Baconian method. He argued against syllogistic logic for scientific synthesis, which he considered to be unreliable. Instead, he proposed an approach in which relevant observations about a specific phenomenon are systematically collected, tabulated and objectively analysed using inductive logic to generate generalisable ideas. In his view, truth could be uncovered only when the mind is free from incomplete (and hence false) axioms.
The Baconian method attempted to remove logical bias from the process of observation and conceptualisation, by delineating the steps of scientific synthesis and optimising each one separately. Bacon’s vision was to leverage a community of observers to collect vast amounts of information about nature and tabulate it into a central record accessible to inductive analysis. In Novum Organum, he wrote: ‘Empiricists are like ants; they accumulate and use. Rationalists spin webs like spiders. The best method is that of the bee; it is somewhere in between, taking existing material and using it.’
The Baconian method is rarely used today. It proved too laborious and extravagantly expensive; its technological applications were unclear. However, at the time the formalisation of a scientific method marked a revolutionary advance. Before it, science was metaphysical, accessible only to a few learned men, mostly of noble birth. By rejecting the authority of the ancient Greeks and delineating the steps of discovery, Bacon created a blueprint that would allow anyone, regardless of background, to become a scientist.
Bacon’s insights also revealed an important hidden truth: the discovery process is inherently algorithmic. It is the outcome of a finite number of steps that are repeated until a meaningful result is uncovered. Bacon explicitly used the word ‘machine’ in describing his method. His scientific algorithm has three essential components: first, observations have to be collected and integrated into the total corpus of knowledge. Second, the new observations are used to generate new hypotheses. Third, the hypotheses are tested through carefully designed experiments.
If science is algorithmic, then it must have the potential for automation. This futuristic dream has eluded information and computer scientists for decades, in large part because the three main steps of scientific discovery occupy different planes. Observation is sensual; hypothesis-generation is mental; and experimentation is mechanical. Automating the scientific process will require the effective incorporation of machines in each step and in all three feeding into each other without friction. Nobody has yet figured out how to do that.
Experimentation has seen the most substantial recent progress. For example, the pharmaceutical industry commonly uses automated high-throughput platforms for drug design. Startups such as Transcriptic and Emerald Cloud Lab, both in California, are building systems to automate almost every physical task that biomedical scientists do. Scientists can submit their experiments online, where they are converted to code and fed into robotic platforms that carry out a battery of biological experiments. These solutions are most relevant to disciplines that require intensive experimentation, such as molecular biology and chemical engineering, but analogous methods can be applied in other data-intensive fields, and even extended to theoretical disciplines.
Automated hypothesis-generation is less advanced, but the work of Don Swanson in the 1980s provided an important step forward. He demonstrated the existence of hidden links between unrelated ideas in the scientific literature; using a simple deductive logical framework, he could connect papers from various fields with no citation overlap. In this way, Swanson was able to hypothesise a novel link between dietary fish oil and Reynaud’s Syndrome without conducting any experiments or being an expert in either field. Other, more recent approaches, such as those of Andrey Rzhetsky at the University of Chicago and Albert-László Barabási at Northeastern University, rely on mathematical modelling and graph theory. They incorporate large datasets, in which knowledge is projected as a network, where nodes are concepts and links are relationships between them. Novel hypotheses would show up as undiscovered links between nodes.
The most challenging step in the automation process is how to collect reliable scientific observations on a large scale. There is currently no central data bank that holds humanity’s total scientific knowledge on an observational level. Natural language-processing has advanced to the point at which it can automatically extract not only relationships but also context from scientific papers. However, major scientific publishers have placed severe restrictions on text-mining. More important, the text of papers is biased towards the scientist’s interpretations (or misconceptions), and it contains synthesised complex concepts and methodologies that are difficult to extract and quantify.
Nevertheless, recent advances in computing and networked databases make the Baconian method practical for the first time in history. And even before scientific discovery can be automated, embracing Bacon’s approach could prove valuable at a time when pure reductionism is reaching the edge of its usefulness.
Human minds simply cannot reconstruct highly complex natural phenomena efficiently enough in the age of big data. A modern Baconian method that incorporates reductionist ideas through data-mining, but then analyses this information through inductive computational models, could transform our understanding of the natural world. Such an approach would enable us to generate novel hypotheses that have higher chances of turning out to be true, to test those hypotheses, and to fill gaps in our knowledge. It would also provide a much-needed reminder of what science is supposed to be: truth-seeking, anti-authoritarian, and limitlessly free.
Ahmed Alkhateeb is is a molecular cancer biologist at Harvard Medical School.
As Trump’s travel ban hangs in limbo, what does it mean for science?
As Trump’s travel ban hangs in limbo, what does it mean for science?
Will protesters have to flood US airports again? Credit: Patrick Fallon/Reuters
Donald Trump has signed a new executive order preventing citizens of six Muslim-majority countries from entering the US for the next 90 days. The decree covers Syria, Iran, Sudan, Somalia, Libya and Yemen, but it will not apply to visa holders or dual citizens. Refugees will be denied entry to the country for a period of 120 days.
Trump’s original travel ban was struck down by the courts in January; it also included Iraq, which has been left off the list this time.
Beyond the effects that the new ban will have on people from the Middle East and North African region, it also has serious repercussions for science. Trump’s travel prohibitions are an integral part of a broader ideology that is at war with rational critical thought. It is from that perspective that my scientist colleagues and I find ourselves most concerned.
An attack on scientists
The US today is the world’s leading scientific research hub and the largest producer of skilled scientists and engineers. It is difficult to estimate what percentage of the world’s active scientists are US-trained, but it is well documented that somewhere between 30% and 50% of US-trained scientists and engineers at the PhD level are foreign-born.
Many of these highly talented individuals return to their countries to support development at home. Many remain in the US to become the researchers, engineers, medical doctors and tech-entrepreneurs that fuel the economy there.
The US is where some of the most important scientific conferences, such as the Gordon Conferences, take place, and thus where some of the best ideas that might shape the future of the world are exchanged. It is therefore no surprise that the European Molecular Biology Organisation has criticised the travel ban and created a platform by which its members can offer to host their stranded colleagues.
Many scientists are now wondering whether, in solidarity with their banned colleagues, they should boycott US conferences and refuse invitations to speak in the country. Others believe this to be counterproductive, and the debate rages. Both sides make excellent points, and the answer is not simple.
What is clear is that if the proposed isolationist and discriminatory policies continue, a scientific boycott would have strong moral and political justification, comparable to that of other boycott movements that protest against discriminatory policies all over the world.
An attack on science
The travel ban is detrimental to scientific exchange and progress in the US and possibly globally – not just because it is potentially based on bad data. However, there is a far greater menace underlying its ethos, and that of the Trump administration.
From a scientific perspective, it is tragic. Science is a process of generating facts (we call them data). In science there are no alternative facts. There may be alternative interpretations of the same facts, but not alternative facts.
Without confidence in facts, there can be no meaningful debate on interpretation, and thus no progress. It is a fact that the planet is warming. It is also a fact that human activity contributes significantly to that warming. Scientists may debate how to tackle these changes, and which model will best predict future effects. However, they do not disagree on the facts.
And science is much more than the collection of data. It is a process of analysis and discussion of data. It is the process that allows rational thought, open debate and the evolution of understanding to rule over personal preferences, individual biases and ideological positions.
This is not the monopoly of people in white coats who speak weird jargon and drink too much coffee. Science is the prerogative of every person in the world. It is what sustains freedom of exploration, respect for positive debate and acceptance of a better idea based on proof.
This is what the language and attitude of the current US administration seeks to undermine.
The travel ban imposed by the US administration is one symptom of a wider and more dangerous assault on fundamental values of rational thought, evidence-based opinion making and debate.
It is no coincidence that this assault also counts among its victims serious journalism and the courts of law.It is a great irony that we are witnessing attacks on both fact and people from the Middle East and North African region, given that the father of the scientific method is the great scientist and mathematician Ibn Al-Haytham, who just happened to hail from what is today Iraq.
The core values I have mentioned are key to scientific research, but they are also integral to modern democracy and respect for human dignity and equality. As such, they are worth standing up for by all of us, most of all by scientists.
Bassem Hassan, Neuroscientifique, directeur de l’équipe Développement du cerveau, Institut du Cerveau et de la Moelle épinière (ICM)
Evading science communication simply because it is difficult, time-consuming or not important enough reflects more on how much scientists value their own work and its place in posterity.
Evading science communication simply because it is difficult, time-consuming or not important enough reflects more on how much scientists value their own work and its place in posterity.
Science communication is often the dissemination of the results of research that has been funded by public money. The Indian Institute of Science, Bengaluru. Credit: abhishek_kr/Flickr, CC BY 2.0
Among other things, Twitter is an excellent echo chamber. But the benefits of seeing dissenting viewpoints far outweighs the satisfaction of getting your own ideas reinforced.
Recently, I was drawn to a thread where a scientist (Gautam R. Desiraju, a noted crystallographer at the Indian Institute of Science, Bengaluru) and a science communicator locked horns to discuss whether scientists should be responsible for science communication.
After many exchanges of 140 characters each and a hastily written article by the scientist explaining his point of view, it became clear that I did not agree with his opinions. As a practicing scientist, I think it is time to give voice to the many young and upcoming scientists and communicators who believe that science communication by scientists is important.
Is this really true? What does "communicate" mean? If you publish your result in a refereed journal, I should think that would suffice. https://t.co/hb6jq1IY5S
First, some context: Science communication, which didn’t exist as a field until the 19th century, came up in response to the emergence of ‘public science’: undertakings funded not just by private patronage and the Royal Societies but by universities and other public institutions. Science communication is quite simply conveying the results of science to the public. The field gained credibility because the public benefited from scientific advances – including the steam-powered printing press, which greatly enhanced public education through books.
Science communication today remains fairly unchanged. It still involves talking to the commons about how science is done in various fields, the salient results of major experiments and how new data from these experiments changes our understanding of the world, at least as we know it. Not only does this help us to make informed decisions in our daily lives, it also empowers us to choose candidates for government office whose policies are scientifically sound.
The importance of science communication
In the Twitter conversation that I mentioned earlier, some of the participants argued that science communication was not the responsibility of working scientists. By listing out their most salient points, I am going to argue/explain why I think science communication is vital for scientists. I will also propose ways in which science communication, done by both scientists and science communicators, can be encouraged and improved.
This work is too ‘complicated’ for the public to understand – Explaining science can be as complicated or simple as necessary, depending on the questions asked. Communicating concepts can be individually tailored to the audience at hand.
To begin with, assess the general education level. Is the audience the lay public? Do they have a working knowledge of basic science? Can they be pegged at a high-school or college level? The level of exposure to science in daily life is important – Is the audience from a metropolis with a large number of universities famous for doing good science? Are they famous in other fields such as business or law? And then, gauge the level of curiosity. Are they mostly non-scientific but with a curiosity for science? Are they scientists themselves and are curious about other scientific fields?
Nobody is too stupid to understand science. What it needs is a paring down of difficult concepts into smaller standalone chunks that can be easily explained and later assembled into a bigger picture. Some abstract concepts can be difficult to unpack to a lay audience, and which might need the help of comparisons and metaphors. But no concept is inexplicable or un-understandable. When approached properly, with the right examples and the correct flow of thought, even quantum gravity can be easily explained to a high school student.
Some results are too ‘sensitive’ to be spoken and explained out in the public – In both basic and the applied sciences, certain results need to be handled carefully before they can be released to the public. For example, researchers work with patent offices to ensure that their intellectual property can be transformed into profitable products. In such cases, prematurely releasing information to the public can be detrimental. That being said, effective science communication can still easily straddle the requirements of financial necessity and public edification. Explaining how a drug molecule works to cure disease, or how lasers allow iris-scanning, can be done while allowing the researchers to reap the benefits of their efforts.
Very explicitly, science communication is often the dissemination of the results of research that has been funded by public money. Scientific grants are funded by government budgets, which in turn are fuelled by taxpayers’ money. If the public deserves to know how their tax money is used to maintain roads, run schools and improve infrastructure, then why should they be kept in the dark about how their money is being used to advance science?
Scientists have too much on their plate already – Choosing the path to becoming a career scientist is by no means straightforward. The challenges for a pre-tenure scientist are to generate a solid body of scientific publications, mentor students, write to private and public granting agencies for money to keep the laboratory funded and, finally, fulfil teaching and administrative obligations as mandated by the university. After getting tenure, the university will guarantee the scientist a permanent position, regular salary and some funds to keep the laboratory running. Thus, in comparison to many other professions, science academia relies on an unrelenting, unwavering commitment on the part of the young scientist, despite extreme financial and personal hurdles. Science is a demanding discipline and, yes, scientists do have a lot on their plate.
But science communication is varied and adaptable. Many interactions can count towards scientific communication. For example, taking a day out of the year to go talk to school and college students about scientific careers; volunteering to give a short talk at a local bar on a science night about your research; allocating time to talk to the university’s science communication representative; mentoring an interested school student; writing articles for newspapers and magazines; maintaining a working and updated webpage to chronicle the laboratory’s scientific advances and publications and tweeting about new advances in the field. All these count towards science communication and all of them can be performed voluntarily, with flexible hours at one’s own leisure.
It is not the scientists’ ‘job’ to communicate to the public – Aptly phrased by Bernard of Chartres, we are dwarves standing on the shoulders of giants. All new knowledge is discovered while standing on already well-established truths. These truths are hard to understand and difficult to scale – much like climbing giants. Since scientists are the ones who take pains to climb to such heights to look upon the horizon, who better to explain how beautiful the sunrise looks from up there?
Doing science has not been and never should be ‘just another job’. Scientists are among the few and fortunate that work on the very limits of human knowledge. It is our duty and privilege to create new knowledge and push existing boundaries, along with the best and brightest minds in the world. And therefore, communicating science to the public is, in fact, the best chance scientists have to inspire young minds and motivate the people to know more about their world.
It is also very easy for scientists to wash their hands of this important task by claiming that, since they have published in a scientific journal and passed peer review, they are under no obligation to explain anything else to the public. This point of view is not only dangerous in the short-term but also absolutely detrimental to science in the foreseeable future. There are two major explanations for why publishing in a journal is not equivalent to science communication.
First: Scientific papers are specifically written to pass peer review. This means that all scientific papers are written to explain new results of the field to other scientists in the same field. They are written in highly technical language for effective communication between peers. The common man reading any given paper from a scientific journal, without any background, will fail to understand anything.
Second: The way the scientific publishing system is currently designed, it is impossible to get hold of peer-reviewed and published work from a well-known journal without paying a substantial sum of money for a subscription. Unless one has access to a university or an allied subscription (or an open-access journal), it is not possible for the public to read any of the articles published in for-profit, closed-access scientific journals.
Thus, even though a scientist can claim that she has done her ‘communication duty’ by publishing her work in a scientific journal, the net result is that the public is still in the dark about her work, simply due to a lack of access. Therefore, the onus is on the scientists to make sure that their work actually reaches the public.
It is “demeaning” to discuss science in social media – Science does not exist in a vacuum. It is a deeply human endeavour intertwined in our social fabric. Social media, like all methods of information distribution, is a tool. There is nothing demeaning about using a tool that makes it easy to reach out to a potentially large audience. It is in fact unforgivable not to. There are many different styles of communication to suit every need: Twitter for short updates; blogging for long-form; podcasts for better speakers and storyboards for visual explainers. The only effort is in picking the right medium.
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Now that we’re here, what can be done to improve status quo? Science communication can be significantly improved by making it a priority for both scientists and communicators. One way is to create incentives to help scientists.
We could include science communication as a course in graduate school. Just as medical students have a residency year to begin practicing medicine, graduate students in science can have an option to work with local and national agencies to improve the penetrance of science in the country. We also ought to increase opportunities to interact with the public. Regular public lectures held in universities can promote interaction between scientists and the commons. And motivated scientists should be given the chance to hone their communication skills by learning from experts in media and communications.
Science communication can also be incentivised by providing extra funding from the university. They, along with other public institutions, can promote effective science outreach by rewarding the extra time spent by a scientist through salary bonuses and intramural and seed grants. Moreover, if a scientist meets a specific target per year of adequate science communication, the university can relieve her of some administrative or mentoring duties.
The history of science communication could be used as a metric for awarding tenure. Just as the number of publications, grants and mentored students are used to decide the eligibility for tenure, a scientist could also be judged by the merit of their outreach. A good scientist with excellent communication skills can effectively influence policy-making and large scale funding decisions, significantly improving the field as a result.
In terms of helping science communicators, we ought to make science communication courses act as an interface between journalists and scientists. This will help dispel any misunderstanding and miscommunication between how scientists wish their work is projected and how communicators ‘package’ it for wider distribution.
There is also a need to project science communication as a legitimate career choice. Whether it is approached from the science side or the media side, it should be should be shown to have a clear future and achievable goals, which it increasingly does. There must also be better access to graduate-level courses so that communicators can learn or brush up on basic knowledge. These courses can then also help build a community over time.
Ultimately, as a scientist, I find it difficult to understand how another scientist can so easily justify dodging the responsibilities of the profession. As graduate students and postdocs in training, we are made to learn and master extremely difficult protocols and techniques. Evading science communication simply because it is difficult, time-consuming or not important enough reflects more on how much the scientist values their own work and its place in posterity.
Shruti Muralidhar is a neuroscientist in Cambridge, Massachusetts.
