Science for Progress

Postdocs are, besides graduate students, the main workforce in academic research. Following the PhD, the postdoc position is the only way to follow a research career within academia. Many PhDs around the world are advised to go to the USA for a postdoc – or two – because it is known for its large research output and high quality research institutes. Around two thirds of postdocs in the USA are foreign born.

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In this episode I talk to Gary McDowell, a UK born scientists in protein research who over the last few years worked with “Future of Research” to investigate the conditions postdocs in the USA are facing. The situations appears to be far from optimal. And this doesn’t just hurt the postdocs and their families, it also impacts research productivity.

The goals of Future of Research are to enable PhDs to make better career decisions about whether a postdoc is a good decision, and if so how to choose the right place to apply to. Another fundamental problem is the disconnect between the lived experience of junior academics, and their senior supervisors.

At the same time the data they collected unveil systemic problems with postdocs in the USA, and Future of Research are working to change academia for the better.

The postdoc, as advertised, is a sort of apprenticeship position where PhDs develop their own research projects to become leading scientists heading their own labs. The reality is that postdocs have replaced staff researchers, working on their Principal Investigator’s project, and hardly ever being mentored, or trained in leadership and management. Even training in basic day-to-day parts of the work as an academic scholar, like conducting peer review, don’t seem to be part of their experience. At the same time postdocs are still being classified as “trainees” to justify not paying them their worth, and to deny them benefits such as proper health care.

Because postdocs are paid below their skill and experience levels, and mostly are not given the mentoring and training promised, they are basically exploited as cheap labor by the academic system. A few years ago, Obama tried to change a labor law, which would have had the effect that institutions would need to give postdocs a raise – or face the issue of having to actually keep track of postdoc working hours. Unfortunately this change didn’t become effective. On the bright side, most universities still implemented the raise – even though some universities apparently were trying to take it back. So this was good news.

Future of Research collected salary data from postdocs just after this happened (and continues to do so for a longitudinal study), and found a median income of around $47484 – a number that clearly could be related to the planned labor law adjustment. So this was a positive finding. However, we should not forget that taking all people with doctorates in the USA, median salaries are in the ranges of $70 000 to $100 000. Even worse, doing a postdoc has negative long-term effects on income that have been tracked up to 15 years following graduation to a PhD, which seem to come as a surprise to many, including industry representatives.

The USA are infamous for their bad health care and labor protection situation. Many PhDs from countries with socialized or mandated benefits, like in Europe, will be surprised that things like basic health care, vacation of more than 2 weeks, and maternal protection (let alone parental leave), are not really a given in America. And Universities often will take any excuse not to pay benefits.

Vice versa, Americans appear to be quite surprised that in the UK, for example, there is a training time mandate by funding providers. In the USA the PI has full control over a postdoc’s time. And not only are PIs allowed to keep their “trainees” from getting trained in workshops and elsewhere, they also often simply don’t mentor them themselves, either.

The example for lack of training, and general misconduct, we talk about, is peer review. PIs who are asked to review a paper for a journal, often pass the work on to postdocs or graduate students under the pretense of it being a training opportunity. But then there is no feedback given. Often the written peer reviews are handed to the editors directly without mentioning who wrote it. In this way the integrity of peer review is broken, the trainee is denied credit and networking opportunity, and the PI basically just committed plagiarism.

The work of Future of Research to inspire change has been compared to talking to climate change deniers. Senior academics responded with outright denial, the wish to only talk about the positive sides (which ones?), or even demanded that research on these issues should be stopped. You know, because it’s easier to ignore the problems this way.

Thankfully, some change is underway, despite these reactions. Many institutions are slowly realizing that the bad conditions in academia are beginning to deter the young people. Future of Research is pushing for more transparency, more Early Career Researchers on boards of societies and institutions, ways to measure the mentorship quality at a university, and guidelines for journals that will hopefully help improve the situation surrounding early career researchers who partake in peer review currently in secrecy. This will not only improve the peer review itself but it also helps when early career researchers become known among journal editors.

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In March, Bart visited the bi-annual meeting of the German Neuroscience Society (NWG) in Göttingen. And he took his brand new digital audio recorder with him! So this is the first time we can present impressions from the field!

Bart interviewed professor Karin Nordström, graduate student Robert Kossen, and a former researcher and now entrepreneur John Stowers about what brings them to the conference, and when and why students should begin attending.

Taking it a step further, we also highlight two conferences, the Neuroscience Doctoral Student’s Workshop (NeuroDoWo), which is completely organized by graduate students, and the
Women’s Career Network (WoCaNet), where graduate students also took the organizational leadership.

Bart participated at WoCaNet and he managed to interview the three organizers, Luisa Hallmaier-Wacker, Priya Gurumoorthy, and Liubov Zakharova, too!

We also got Robert Kossen to talk us through his conference poster. To give you the full experience, he did not hold back on field specific jargon! But if you want to give it a try, here is the poster that comes with it:

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In May will be the next Pint of Science event!

Pint of Science is an annual festival that was founded by Michael Motskin and Praveen Paul. Every May scientists present their research to a public audience in a pub or a bar. It started in the UK in 2014, and it’s now spread throughout the world, with official events in 24 countries. In 2018, 120 000 people visited Pint of Science events. The events are planned by local teams, which make up the 3000 volunteers.

In this episode I spoke with Pint of Science organizer Elodie Chabrol, a former neuroscience researcher, who is now a full-time science communicator.

Already during her days as a researcher, Elodie tried to explain her work to colleagues, friends and family, which made her conscious about how to communicate effectively. As a professional freelance science communicator she wants to encourage scientists to share their stories, and to demonstrate that scientists are approachable. She loves it, when people understand what she is trying to explain.

Elodie switched to science communication in 2017, after she had been organizing Pint of Science for 4 years, already. She joined Pint of Science, because she was interested in organizing event. And when somebody else quit, she took the opportunity to become part of the core organizer team.

The work of a science communicator can be diverse. For Pint of Science Elodie trains speakers, and gives promotional talks. But she also speaks about science on podcasts or radio shows, and trains scientists in public speaking and social media use. She was able to transition into freelance work relatively smoothly, but she had established a profile over the previous 4 years, which was a lot of work.

Pint of Science will be on May 20-22. To find out whether there are events in your area, visit their website pintofscience.com – since we recorded the interview, the programmes went online.  

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Bart and I invited three scientists from both sides of the canal to talk about Brexit and how it impacts scientists and the scientific endeavor. Our guests are Andrew Phillipides (British citizen, and professor at Sussex University, UK), Thomas Nowotny (German citizen, and professor at Sussex University, UK), and Clare Hancock (British citizen, and PhD student at Göttingen University, Germany).

The goal of the EU is to promote peace, freedom, security and justice, sustainable development, social inclusion, cohesion and solidarity among member states, to respect cultural diversity, to establish an economic and monetary union (EUR).

And most important for this podcast, the European Union coordinates efforts to further scientific and technological progress across Europe. The EU runs a research programmes that is renewed every 7 years. For the current one, Horizon 2020, the EU spent nearly €80 billion that are provided by the member states. And this money goes into the funding and promotion of research across the EU.

The second important property of the EU for science is the freedom to travel, work, and live anywhere within the member states, as it is agreed in the Schengen Agreement.

In 2016 the citizens of the UK voted in a referendum to leave the European Union. This means that all these benefits from 40 years of Pan-European negotiations, are lost and have to be negotiated anew.

What are the consequences for Science in the UK and in the rest of the EU? Our guests talk about both the practical and formal consequences, but also the personal and social costs of Brexit.

On the funding site, the British Government will ensure the continuation of EU funded projects in the UK – at least for the 2-year transition period. A possible long-term solution would be the Swiss model. Switzerland contributes to the scientific funding in the EU financially, and in exchange Swiss labs can apply for EU funding programmes.

On the side of free movement, there is a little bit more of a hassle. A lot of bureaucracy is going into this. While nothing may change regarding simple travel, moving between the UK and EU to work and live is much more complicated.

The strongest impact, however, is the social one. The uncertainty of Brexit makes people reluctant to move to the UK to study or to do research. And it seems to have had affected the ability of UK labs to successfully apply for EU grants, negatively, for years.

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But it is not just funding and bureaucracy that deters students and researchers from moving to the UK. While surely many reasons have led to the outcome of the Brexit referendum, it did embolden xenophobia in the UK. Besides the chaotic political situation, this in particular has damaged the reputation of the British people.

Maybe a silver lining for the EU is that the Brexit example may have detered other countries from seriously considering to leave the EU. This may give the EU a chance to instead work on its reputation of being a barely democratic institution that mostly panders to elites.

I think everybody in this conversation agrees that leaving the EU is a bad decision that was made under questionable circumstances. And we all hope that the best solution for both UK and the rest of the EU can be found.

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Arnold Schwarzenegger famously (and half-jokingly) proclaimed that if you need more than 6 hours of sleep, you should sleep faster. Many successful people claim to sleep very little and use the extra time to be productive.

But is this sound advise? I talked with Dr. Lars Dittrich, neuroscientist and former sleep researcher, about sleep.

Lars answer questions like What does sleep do? How is it regulated? What are the side-effects of acute and chronic sleep deprivation? How do I know if I sleep enough? How could sleep research inform policies and business practices?

Sleep deprivation, even only short-term, has significant effects on your cognitive abilities. Just a single night of lost sleep has the same effects as the amount of alcohol that would make driving illegal.

This tiredness is believed to be a mechanism that dials down the activity of the brain to reduce the accumulation of metabolites that may damage the brain. During sleep, these metabolites are cleared out of the brain. It is also the time for certain cognitive housekeeping functions, such as memory consolidation.

Sleepiness is regulated through two parameters: the time since you last slept, and the time of the day according to your internal circadian clock. Both the preferred sleep duration as well as the timing of sleep in the day are different between people. On average we need between roundabout 8 hrs of sleep.

If we force ourselves to sleep fewer hours per night than we need, this can have harsh health consequences, from cognitive decline to an increased risk for metabolic diseases – in particular diabetes – and possibly dementia.

As teenagers, and when we move the time at which we have to get up to an earlier phase of the internal clock, we are awake at times that our circadian rhythm says is too early. Accordingly, we are more tired, and suffer from some reduced cognitive ability.

Because of this scientist wonder whether it would be beneficial to have high school start later. And if we want to get rid of clock changes altogether, it would be better to permanently stick to standard time, rather than having daylight saving time all year round.

Anyways, our conclusion can only be to better not take the advice from people like Schwarzenegger on sleep too seriously. I mean, especially someone like Schwarzenegger should know that lack of recovery time kills your muscle gains!

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In this episode we talk about our experience with peer review and the importance of kindness and the advantages and disadvantages of the authors knowing the identity of peer reviewers. And in the second part we talk about how twitter can be a great place for science and scientists!

Peer review can be a pretty tense process. We talk about how misunderstandings can lead to very negative reviews, and how authors a prone to take critique personally. As a reviewer Bart suggests to use the “shit sandwich” approach, where you “sandwich” bad news between positive remarks. In addition we both feel that it is better to always give authors the benefit of the doubt. So we would clearly point out parts in the text that appear unclear, or ambiguous. This gives the authors the chance to clarify possibly crucial misunderstandings.

Bart further explains why he prefers to let the authors know that it is him who wrote the review, if the journal provides this option. This is a strongly disputed position. Especially young researchers may fear career breaking retaliation from authors with influential positions in the field.

Our twitter rotating curation account @sfprocur has had its anniversary on March 13! In this context Bart and I talk about “science twitter”, the growing (loosely defined) community of scientists that communicate on the social media platform Twitter. Overall we find that Twitter offers a great opportunity to talk about science with professionals and lay people. It’s like the great “water cooler” at which scientists gather to talk about a great variety of topics.

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Who gets positions and funding in academia should depend on the merit of the researcher, project, or institute. But how do we assess these merits fairly, meaningfully and in a way that makes it comparable?

I talked about metrics with Steffen Lemke, PhD student at the Leibniz Information Centre for Economics (ZBW), in Kiel, Germany. He is part of the *metrics project, which investigates new research metrics and their applicability. The project is funded by the German Researcher Association, DFG.

In episode 9 I talked with Björn Brembs about the most prevalent metric used: the Journal Impact Factor. It turns out that the “JIF” is not a good metric.

Another commonly used metric is the “H-index”. Like JIF it is based on citations – the number of times a scientific paper was mentioned in another scientific paper. But it aims to measure the output of a researcher rather than the journal.

Both, H-index and JIF, have their own specific disadvantages. But they also share problems due to the source of data they use: citation indices. Citations are slow to accrue, which means it takes time to build a sufficient amount of data for proper evaluation. The indices are also incomplete and mostly locked behind paywalls. And finally, they are solely focused on journal articles.

But peer-reviewed research articles aren’t the only output scientists generate. Especially social sciences often publish in other formats, like books and monographs. STEM researchers, too, often create other outputs, such as designs for experimental setups, or code.

Finally, citation based metrics focus solely on the communication between scientists, not with the public.

New, alternative metrics aim to change all that. “Altmetrics” is an umbrella term for a range of still experimental metrics. They use data one can find openly on the internet. This makes them fast and diverse. They look, for example, at the dissemination of research articles on social media. But they also look at the download numbers of open repositories for code, lecture videos, presentation slides, and other resources. In this way they may cover any research product you can find on the internet.

Whether a metric predicts a scientific impact (citations) fast and well, can be tested. So far it appears that data from online reference managers can predict citations well. You don’t need to wait for citing authors to write and publish their own papers, you just look if they bookmarked your paper for later use.

An obvious disadvantage of altmetrics is that they can be gamed. One can buy services from social media providers to advertise posts. Or one can use bots to amplify the impact on social media, or download files thousands of times.

Soberingly, researchers found altmetrics not to cover humanities and social sciences, sufficiently. Less than 12% of the research output from these fields showed up in the altmetrics tested.

Steffen Lemke and his co-authors asked why there is so little representation of social sciences on social media. Surprisingly, while social scientists usually justify their work with the relevance for the public, they see interacting with it on social media as a waste of time. Some answered in the survey, that they would be overwhelmed by information. It was hard to tell the quality of information on the internet. Others say they’d not be seen as serious would they be caught using social media – even for work – by their supervisors.

In Steffen’s article you will find the interesting term “metric-wiseness”. Coined by a different research group, it describes the knowledge of researchers about metrics, and the ability to understand their meaning and applicability. In their research surveys, the *metrics project asks researchers about their knowledge of metrics.

Even very junior researchers know about JIF. And they try to optimize their research output to achieve publications in journals with a high JIF. However, there is little knowledge of how it is generated, and no awareness of the massive caveats this metric has. Similarly for the H-Index. Altmetrics, however, appear to be almost completely unknown. The whole concept appears to be alien to researchers.

The careers of researchers depend on metrics, and paying attention to measurements is their bread and butter. Still, after more than a decade as a researcher, myself, these findings are no surprise to me.

Altmetrics may be the path to better research evaluation in the future. They are fast and cover a larger portion of the overall output of researchers beyond scientific articles. But as all metrics, they can be gamed.

Once a metric becomes representative for productivity and impact, people will optimize their behavior for the metric. At the moment it appears to be a robust approach to use the bookmark data from reference managers to predict impact of articles within the scientific community. But once this has become a metric (and this is my own opinion), Elsevier, which owns the very popular reference manager “Mendeley”, will begin selling visibility for papers on that platform – and authors or their employers will buy it.

Overall, altmetrics are not ready to be universally applied. Many fields are insufficiently represented in the databases altmetrics rely on.

At the end, however, I think the most important part is to inform researchers about the metrics they are relying on.

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This episode of Bart and Dennis Talk is actually our first anniversary episode! While Science for Progress was founded in July 2017, the podcast went online on February 20th 2018!

At the beginning of the episode I announce that I will be on the Twitter “rotating curation account” @RecovingAcad, which belongs to the Recovering Academic Podcast. We had a crossover episode with them, last November. I will be tweeting about leaving academia and transitioning into industry from February 25th to March 2nd.

On March 3rd I will do a live video AMA on the account @theaddictivebrain on Instagram. Addictive Brain is a science communication project that was initiated by Chinmaya Sadangi, who was curator on our twitter rotating curation account @sfprocur. My AMA on Instagram starts at 3 p.m. UTC and will take about an hour.

At this time we have had 20 episodes, 10 of which were from the phase when I did an episode every three weeks. But since we started doing the B&D episodes, we’re publishing an episode every other week.

I hope you agree that the production quality has increased. I am still working on improving my editing skills but I think that is also becoming better. Compared to the early episodes we went from one hour to 30 minutes, which I think is better. We also went from a conversation style to a narrative style in our interviews.

I would be very interested to and to know what you think about that! Do you prefer the heavily edited version where I try to make everything more clear, or do you prefer to listen to a more natural conversation?

I personally think that every episode has actually pretty good content, but the journal impact factor episode with Björn Brembs is a clear winner when it comes to downloads. In terms of content for the future I will continue to do episodes on Academia, topics of general interest like the GMO episode, and science communication.

We then looked at some data from the paper on science communication podcast by Lewis MacKenzie. He looked at a number of science podcasts. I am not sure whether our podcast really fits in the study, because it doesn’t fit the criteria 100%. But still we compared our outcomes with those described in the paper.

It turns out we are above average dedicated to this podcast! The median lifespan of independent (not affiliated to an institute or company) science podcast is just 16 episodes. I am happy to see that we did beat that already in the first year! The median survival rate of podcast that are affiliated with a company or an Institute of some sort, is 24 episodes, and I’ve already recorded our episodes 21 and 23, episodes 25 and 27 are in planning (update: actually, by the time this episode is published, I already recorded episode 25, too).

On March 3rd there will be an episode on alternative metrics, with Steffen Lemke. These “Altmetrics” are supposed to complement citation based metrics such as the journal impact factor or the H-index. I talked with Steffen about the advantages and disadvantages of these metrics.

On March 31st there will be an episode called “Sleep Faster” with Lars Dittrich. Until recently, Lars studied sleep, and we talked about whether it is a good idea to try shave off a few hours of sleep every night in order to get more productive hours during the day.

On April 28th there will be an episode about the Pint of Science with Elodie Chabrol. Pint of Science is a science communication event that happens once a year and has grown massively over the last six years.

And finally on May 26th there will be an episode called “Energiewende” with Tanja Kneiske. Tanja works for the Fraunhofer Institute on smart power distribution systems. We will talk about the German transition out of fossil fuels and nuclear power, the efforts to replace them completely with renewable energy.

The Chinese researcher who created the first genetically edited babies, He Jiankui, is being punished by the Chinese Government. We had been asking ourselves whether this experiment was illegal in China. It turns out it absolutely is. At the same time Stanford University has begun an investigation following claims that some of its staff had known about the Chinese scientist and his plans to create the world’s first Gene edited babies.

We then talk a little bit about a survey done in Germany, Switzerland and Sweden on whether people trust in science and/or whether they trust in scientists.

They asked about a thousand people each and they found a clear ambivalence of people towards science and the application of research. They distrusted the scientists’ motives more than they distrusted science itself. Between 50 and 60% of respondents say that they rather or completely trust science, which is pretty much chance.

The amount of education a person has, has a positive effect. People with more education are more likely to trust in science, however this effect is very small. In Germany 76% say that there is a problem with a conflict of interest, and only 17% say that they will trust scientists on GMOs. In general, affiliation matters. In Sweden and Switzerland they found that people trust academics more than they trust industry researchers.

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The stereotype of academics is that they live a well protected life in the ivory tower. But this is not the case for most of them. Maria Pinto from Portugal is a PhD student in marine microbiology in Austria. With the final stages of her work approaching, Maria is beginning to think about the future.

We talk about the many uncertainties in academia, particularly for early career researchers. In general the salaries are not good, but in poorer countries, where the salaries are particularly low and may not even include social security, there is also an expectation of students to pay field work trips themselves. In general, traveling in order to present your work at conferences is important to researchers and their careers, but for many, this is not affordable.

PhD students and postdocs are in the typical age for founding families. The academic career, however, demands mobility. For many this means that they need to move countries several times – a factor that greatly affects life planning security negatively.

And all of this is happening in a climate of increasing PhD graduations and stagnating long-term or permanent job openings.

Yet, leaving academia is often discouraged. Among early career academics and their advisers it’s simply expected to try hard for an academic career. This often means that PhDs think about a possible transition outside of academia very late. And then there is always the gnawing question: Do I have any value on the private market?

We don’t have an answer to the problems we highlight, but maybe we can work a little bit against the stereotype of the spoiled academic. And maybe we can push some early career researchers to think about plan B, earlier.

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• How Ph.D.s Romanticize the ‘Regular’ Job Market

In the light of the latest animal use numbers in Germany (2017), Bart and I are having a conversation about animal use in fundamental research. We then move on to talk about a new statistical method that might help researchers get some of their data out of their drawers and into an article!

Numbers in short (as presented by tagesschau.de):

Bart and I regularly discuss the merit of animal research on social media, and we also had a podcast episode on animal wellfare in science.

Our conversation mostly is about fundamental scientific research – which is what we do. We talk about how scientists don’t prefer animal experiments, if there are better ways to answer the research question. But we also mention how difficult it is to know in advance what the outcomes of a study will be good for, particularly in fundamental research. We then address the ethical considerations of the value we assign to different animals.

The statistical tests usually applied in scientific studies look at the data of two or more groups and check whether they are different enough to say that there is an effect between them.

It appears that often lack of such differences is used as an argument against publishing the data at all. Because of this, experiments may be repeated unnecessarily by different groups, simply because they don’t know about the results.

The paper that Bart highlights is “A new statistical method to test equivalence: an application in male and female eastern bluebird song” by Rose et al, 2018 (link below). In order to show that the songs of male and female Eastern Bluebirds are not just not significantly different, but identical, they applied this new statistical method.

This may allow scientists to pick up some of their old studies and publish them!

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• PRESSEKONFERENZ DER INITIATIVE TIERVERSUCHE VERSTEHEN (press conference of the initiative “understanding animal experiments”

• Verwendung von Versuchstieren im Jahr 2017 (Use of laboratory animals in 2017 – official website of the German Federal Ministry for Agriculture and Nutrition)