Tag Archives: Academics

The Power of Kindness

This is a response to Inger Mewburn’s post, which you can find here. It is a nice post (thanks for the book tip, Inger, I will definitely read it!). Now, I just want to share some thoughts about this topic.

The topic is about jerks in academia. I think everyone could share a story about such people. For instance, I volunteered in doing a talk shortly after my PhD. I not really had to do it – it was just a favor for a good time and a good collaboration. They wanted to extend to grant (it was a research training group), there was an evaluation commission, and so students from this project should do talks and tell about the project. My old advisor asked me and I said yes. However, I was actually the backup for someone I knew 99.999% would do the talk.

Nevertheless, I prepared the slides, practice the talk, discussed it with my old advisor. And then there was a “final rehearsal” where everyone should do their talks. My talk was the last one. It was a really bad talk. Today I am a little embarrassed when I think about it. Imagine the audience: about 30 students and about 10 professors. Students were fine (just asked a couple of questions), but there were a lot of critics from the professors.

Now, critics is fine. How you deliver it, is the question. I like to be direct and ask people to be this likewise. However, you do not have to be an asshole to be direct and vice versa. Among the professors there was the One. You probably have seen this oh-I-have-also-an-affiliation-with-a-top-university-somewhere-else-so-be-glad-that-I-talk-to-you-at-least.

One literally insulted me and my talk. “Das ist Fliegenschiss!” (about: This is no more than flyspeck – hard to translate such things!). The more he talked the more he raged and got even more angry. Minutes. I got angry – and I swear if I would have something in my hand… The others did not say anything. Fear? Do they fear this colleague so much to not interupt him? Well, one tried. She started with “Look, we appreciate your work and contribution to this research training group, but …” Then raging One took over again. Tension rising. It was a hard trial for me. I do not want to talk too much about details – because this makes me angry again. I do not want to be like this.

Nevertheless, at some point (in one of the raging breaks) another professor raised his hand. Let us call him Professor Teddybear. He looked like one. People told me that his hearing is not really good anymore. Professor Teddybear raised his hand. And he pointed out some very plain thing (something about puting a name on one of the slides), another professor pointed out just before him (another raging break). Everyone was aware of this. I looked at him and at my slide. Looked at him. I was about to say something like “Yeah, X just pointed that out.” but…

He smiled. Professor Teddybear sat there, his eyes half closed, and smiled. “This is a very good idea.“, I said and smiled, too. Suddenly, all this tension and rage… was gone. People laughed (except One, of course). Session ended well.

Do not tell me, this is not power – to relax everyons tension at once. To make people comfortable. I want to be like this. (Still, I do not know if he really just did not hear the comment before him – in future versions of this story I will probably just skip his omit the info about his bad hearing…)

Since then, I try to be more relaxed, which is hard work, in fact. Irascibility is a beast. You need to hunt it down. Every day. Every moment. Now I am at my second postdoc (Canada – incarnate politeness and diversity – love it!) and just try to be kind and nice. Not to rage. Seeing things very relaxed – a good way to stay healthy in terms of mentality.

You know what? People like me. They come to me to get an advice. I suggest things based on my experience (I do not use my experience to argue!) and try not to force my opinion on people. I tell them when I may be wrong. I tell them “my way might not be the best, you have to figure it out yourself“, etc. Being a good friend and colleague is the key for good collaborations and work. I have some ethics.

As far as I understood, this is what Inger & Friends are doing as well. I like to be part of a “Circle of Niceness” rather than a part of people everyone fears. Kindness gives you power. It can be as solid as rock withstanding waves after waves of raging. Smiling. This is true power. (By the way: buddhistic way of thinking helps a lot here!)

I think – and this is important – people appreciate kindness. There are probably far more people of kind manners and honest attitudes than you think. The only reason you never hear about these persons: Raging is much louder than smiling.

So, what do you want to do ’bout these assholes?

Ethics for a new scientific millennium


For quite a long time, people discussed about terms and concepts like ‘impact factor’, ‘negative results’, and ‘reproducibility’ in all kinds of analog and digital media. Here, I want to make a little contribution to this discussion on my own, mainly because I feel that some important points (at least important for me) often get lost in the shuffle.

The title may be familiar to you. It is as some of the following concepts and ideas based on a book I read a while ago. The German version, which I read, is Dalai Lama (2013). Das Buch der Menschlichkeit: Eine neue Ethik für unsere Zeit, Bastei Entertainment, ISBN: 9783838749174 (eng. Bstan-ʼdzin-rgya-mtsho XIV. (2001). Ethics for the New Millennium, Riverhead Books, ISBN: 9781573228831).

How does a (buddhistic) book about ethics fit in here? Well, let us start this discussion with something, which has been discussed so many times that probably everyone is tired of it. Me included. However, I think it is important for explaining the later concepts.

Impact factor

Hence, let us talk about ‘impact’, first. What is actually impact? According to the Oxford Dictionary it is:

  1. The action of one object coming forcibly into contact with another.
  2. The effect or influence of one person, thing, or action, on another.

Do these definitions really tell us what impact is? I find them kind of vague. ‘Influence’ or ‘effect’ are exactly like ‘impact’: everyone has an imagination of the concept behind the word, but there is no math-like, exact definition. You cannot really grab it, can you?

If I throw a stone (a pack of journal-volumes) into a peaceful lake (a crowd of scientists), it will have an impact for sure. However, measuring all the effects will be impossible. First, the stone will displace the water. This will cause waves. Animals will try to dodge the falling stone in the water. It will eventually crush into the bottom of the lake and whirl up some sand or other stones. Maybe destroy something. Also, do not forget about secondary impacts such as the waves reaching the border of the lake and having their own impact there. Of course, this impact was caused by me throwing the stone.

Now, we try to measure this impact – despite the fact we do not even really understand what it is actually – by number of citations. For the metaphor from above, this would be like counting the waves the stone has caused and dividing it by the number of all waves (during a certain time period). On top, we do not even count it ourselves, we assign this task to a company with financial interests.

So, what about the impact of the stone under the surface? What about long-term impacts? What about the stone itself? With no word, I described the stone. Not the size nor color nor material. It could be toxic for the lake or just stay there for hundreds of years and be a home for organisms. But wouldn’t it be important to know all these things to get a more complete picture of the stone and the nature of its impact? To know what actually IS the stone and not (only) what it causes?

Analogously, wouldn’t it be necessary to know the content of scientific work to assess it? Sure. However, the impact factor will not tell us that at all.

Sorites paradox

Every publishing metric system so far including the impact factor is subject to the principle of the sorites paradox. If you have a heap of sand, it does not matter if you take a sand corn away or add one. However, we know that two, three, … sand corns are not a heap and therefore it would matter. So, there must be an abitrary boundary where a couple of sand corns become a heap, right? For metrics of scientific work this is – roughly – the arbitrary boundary between very important and not so important. Hypothetically spoken, if a metric system is subject to the principle of the sorites paradox, its nature is arbitrary and its value useless.

Does it matter that Cell has an actual impact factor of 32 (2014) instead of 30? Does it matter if one of my paper has 4000 Downloads instead of 3800? But it does matter if 100 people read this post instead of just 2! So, where is the boundary? 50 people? 25 people? For any metric, can you ever tell where exactly this boundary is? It seems arbitrary.

Let us for a moment assume we have a metric scale with only one boundary and we knew exactly where this boundary is (our scientific cat told us!). Then it is obvious that this boundary divides our metric scale into two areas, a low one (i.e. not so important) and a high one (very important). Within these areas (other people would say ‘classes’) the metric value becomes completely useless. As for high impact journals it does not matter if a low impact journal has an factor of 1.0 or 1.5 or 2.0… It does not matter if two persons read my article or three did.

There seems to be a straightforward solution to this problem. You can simply create more classes or areas by introducing more boundaries. For instance, you could try to distinguish between few readers (around 5), many readers (around 100), and a lot of readers (around 1000). However, the problem remains the same: the boundaries between classes are arbitrary if set and the metric values itself become useless within a certain class. The following picture visualizes this thought.

2015.08.19 - metric visualization

In turn and in my honest opinion, this renders these metrics useless and arbitrary. Yet, people like and create this kind of metrics for a simple reason. In contrast to the definition of ‘impact’ from before, a simple number is graspable. People can work with simple numbers. Counting, comparing, sharing, simple math. The higher the number, the more of ‘it’ – whatever ‘it’ is. People feel better with ‘more’ instead of ‘less’. People like having more IQ points (than others). People like having more impact points (than others). People like having more working hours (than others). The last one seems wrong at first glance, but since the impact of work generally is quantified by counting the number of working hours, more hours imply that a person is more valuable (for society). Analogously, the quality of peer-review is often quantified by counting the number of days it takes.

There is a reason why this kind of ‘simple’ metric does behave as described. These metric systems count things, which may or may not be linked to the state of a work (e.g. important, of high quality, …), instead of measuring a quantity, which is linked (directly or indirectly) to the state. The impact factor tries to describe the quality of scientific work in journals by counting citations. It should be obvious that the impact factor fails in doing this. If a journal just publishes (not obvious) frauds and people just reference to these works, because they investigate every single paper to expose these frauds then the journal possesses high impact but no quality. Hence, the state of quality is not given by counting citations. It might be an indication (in both directions), though.

Let me try to make this even clearer by taking a converse example from physics, viz. temperature scale. Any temperature scale (metric) is linked to the physical concept of temperature. Temperature gives information about the state of matter. You can draw exact boundaries (e.g. liquid water between 0°C and 100°C, ice below 0°C, etc.) and it matters anywhere on the scale (in thermodynamic systems!) if something has x degree or x+1 degree. Tungsten melts at 3422°C not at 3421°C. Oxygen freezes at -219°C not at -218°C. This is exactly the opposite behavior of the metric systems described above.

Another important characteristic of the latter metric system is the existence of outer boundaries, i.e. it seems to have natural limits on both ends. For temperature this might not be obvious. There is an absolute zero temperature on one end. Since temperature describes a thermodynamic equilibrium the absence of this equilibrium renders the specification of temperature completely useless although it is done for describing plasma states for example. In this case, ‘temperature’ becomes a countable metric – it just counts the thermal kinetic energy of particles. In consequence, there is an upper boundary for the temperature scale (i.e. when there is no thermodynamic equlibrium anymore).

Conclusively, if we want to assess scientific work and its quality with a metric system, we cannot just count things. We have to find or create a system, which is linked to the qualitative state of the work, which allows us to set exact boundaries, and which possesses outer boundaries (i.e. is restricted on both ends). The question is just: Does such a system exists?

Criteria for assessing scientific work

Before we even think about a new metric system, we should find or define criteria by which we want to assess scientific work. No matter which we (or others) chose, in the end, the aim is always the same: we only seek a tool – no – THE tool, the one ring, the holy grail, the… to assess them all! To assess all scientific work!

Now the time has come to reference to these books I mentioned in the introduction. As said I read the German version and will therefore cite this here (did not find the original text). The following quote is about a principle to assess a moral action. One of the principles, I try to put into practice everyday.

Daraus können wir ableiten, daß ein Kriterium zur Beurteilung einer moralischen Handlung darin besteht, wie ihre Auswirkung auf die Erfahrungen oder Glückserwartungen anderer ist. Eine Handlung, die diese verletzt oder ihnen Gewalt antut, ist potentiell unmoralisch. Ich sage »potentiell«, weil die Folgen unserer Handlungen zwar wichtig sind, es aber noch andere Aspekte zu bedenken gilt, etwa die Frage nach der Absicht sowie die nach dem Wesen der Handlung selbst. Uns allen fallen Dinge ein, die wir getan und mit denen wir andere verletzt haben, obwohl das keineswegs in unserer Absicht lag. (Seite 36ff)

This is the English version (by Google translator and some modifications from my side – if someone has the original text, I would be more than happy to cite it!):

From this we can deduce that a criterion for assessing a moral action is its impact on the experiences or expectations of happiness of other people. An act, which hurts them, is potentially immoral. I say potentially because the consequences of our actions are important, but there are other aspects that are important as well such as the intention and the nature of the action itself. We all remember things we did that hurt others, even though that was not our intention. (Page 36 et seqq.)

I think, we can adapt this concept for assessing scientific work. Let us just replace ‘moral action’ by ‘experiment’ or ‘scientific work’, ‘consequences’ by ‘results’, and ‘nature of action’ by ‘performance’. Then the marked section becomes ‘the results of our experiments are important, but there are other aspects that are important as well such as the intention and the performance of the experiment itself’. Thereby, we can in general assess any experiment and in consequence any series of experiments (i.e. publication) by individually evaluating its three parts, viz. intention, performance, and results.

The intention covers the initial idea, the hypothesis, and/or the overall goal. It usually contains an essay about the state of research and how the work fits in there (introduction). Performance accurately describes how the experiments were designed and performed. What tools, instruments, and materials/chemicals were used. What was the raw data and how was the raw data processed and evaluated. Results covers interpretation, discussion, conclusion, etc.

Think of classical treasure hunting for a simple metaphor: Intention is the idea to get rich by digging up a pirate treasure in the Caribbean and outline of the plan to do so. Performance describes the tools (ship, shovel, crew members, parrots, …) you used including a picture of the map and how you got from the base harbor to the treasure island. Also, how you found the way from the beach to the X, what you lost on the way, and what the treasure was like. Results will discuss what you gained (gold, experience, illness), and if it was worth the effort. In the end, you can refer to your initial overall goal (getting rich) and judge because of your experiment (or maybe you tried severall times?) if treasure hunting is a feasible way to reach this goal.

At the current scientific state, every publication describing treasure hunting will lead to the same conclusion, i.e. that it is in principle a feasible way to get rich. Only if the authors successfully found a treasure of gold, their research will be published, though. Also, there are some problems and issues people have to solve before ‘in principle’ becomes ‘in fact’ (reducing the number of dying crew members, burried treasures are a limited resource, parrots eat all the crackers, …).

This means we need to get away from looking at the Results, only. Immediately. So, let us look at the other parts, too, in order to actually qantify the quality of the overall work!

Assessing scientific work

For now, all three parts described in the previous section shall be equivalently weighted, i.e. 1/3. Thus, this reduces the importance of results by 2/3 (from almost 100%) while the importance of the other two parts strongly increases (from almost 0%). Then, let us analyze each section and discuss how we could assess it.

We start with a tough one. The content of intenstion is hard to judge – almost impossible – and trying to do so (like reviewers do for example) causes the “we cure cancer”-phenomenon. Authors feel the urge that their contribution to science has to be something bigger, something that scratches at the doors to Stockholm. Also, by every journal policy it has to be a novel piece. In consequence, authors justify all of their intentions with “a new way” to “eventually cure cancer”. Maybe one of my readers thinks now “is this really so important?”.

As the title of this blog posts suggests, the content is about ethics. Is the ethical and moral OK to (indirectly) force people to hide their true intentions? I think not. Allow people to be honest! Accept that people were “just” interested in this because no one else did it! Accept that people have cool ideas by doing nerdy stuff because for the sake of (“Why?” “Because we can!”)! Accept that people tried to reproduce things from another scientific work, but were unable to do, and want to publish their efforts including discussion and conclusion! Let them tell their story in a simple language!

Second section to assess is the performance section, which reminds you probably of the “Materials and methods” section of most papers. However, in which journal did you see that this is 33% of the work? Usually, it consists of many short subsections roughly describing the experimental methods by omitting all kinds of important details (humditiy, anyone?). If it is too long you can look up the remaining parts in the suplementary files, a wild jungle of text and pictures no one cared about to write, format, or review. Let me pull up a quote something from the Hitchhiker’s guide to the galaxy:

The plans were on display. […] even if you had popped in on the off chance that some raving bureaucrat wanted to knock your house down, the plans weren’t immediately obvious to the eye […] I eventually had to go down to the cellar! […] With a torch! […] It was on display in the bottom of a locked filing cabinet, stuck in a disused lavatory with a sign on the door saying “Beware of the Leopard”.

So, the experimental details may be all there. Some in the manuscript, some in the supplementaries. You just have to find them! And be able to open it, because they might be submitted in a unknown or rare data format.

However, the performance of an experiment is the central point of any scientific work. We cannot talk about the lack of reproducibility, if we force authors to reduce the fraction of this central point to 5%, maybe 10%, of the whole work. Some journals even print this section in a smaller font visually reducing further the importance.

Here, we again force authors to do something, they may not want, i.e. shorten and part their description of the performance. An then we accuse their work of not being reproducible. This remindes me of Nelson telling people “stop hitting yourself” while constantly hitting them in the face. It should be clear that if you shorten something to a certain degree, you have to omit things. If the description of an experiment requires 10 pages, you cannot reduce this to one paragraph and on the same time keep the same grade of detail. You cannot tell people to write the “most important things” in the manuscript and put the rest in the supplementaries. I do not even see the point.

In our digital era, there is absolutely no need to shorten something for the sake of shortening it or because it looks “nicer” and fits the journals policies. However, journals and publisher dictate what and how things will be scientifically published. Academic ethics have to defer to journal policies. For the sake of ethics and science, we have to change publishing.

These policies cause another issue. Publishers practically implemented something I will call “reproducibility by obscurity” (referring to “security by obscurity”). As described above, finding the details of methods and experiments is sometime a real hassle. Thus, we withdraw responsibilities from the authors and publisher and push it to the reader. If you cannot reproduce something from a paper, you never know if you just couldn’t get all of the details together (so the problem is on your side) or something is missing in or really wrong with the description. When in doubt, you just try to find another work. Thus, nobody (or hardly anyone) contest the reproduciblity of the work, i.e. it has some kind of existence – even it may be only virtual (Schrödinger’s cat may be dead by now!). Just because of obscurity. There is absolutely no ethics in this developement. It obfuscates the state of reproduciblity. This is a problem. A big problem. (Personally, I noticed that the higher the impact factor the less details you find in the papers. This is probably just my own impression, though.)

Last but not least, let us talk about the most controversial section on the list, i.e. results. So far, results have been the only quantify to assess scientific work. Well, to be more precise, arbitrary concepts of positive and negative results have been. However, how can results be positive or negative at all? I’ll make an action, there is an equal reaction. I’ll do an experiment, there is a result. Always. Case closed.

Unless you apply your expectations on the results. Then you derive a new concept of “results” I will call here “expectults” but everyone else will keep calling “results”. Obviously, expectults change with expectations. If my expectation on any publication is that its results will cause world peace and solve starvation, well, then practically every publication published negative expectults. So, they should be retracted. All of them!

While writing the last paragraph I realized how stupid the word “expectults” is. I think it fits very well, because this is what we do. We literally expect that every publication cures cancer. On top, we only publish things, which fit in the big picture of curing cancer. Things, which are politically (i.e. by policy) not acceptable, will not considered for publication. This fits the definition of censorship.

The odd thing is that editors and reviewers are enforcing this. Both groups are scientists. Working in the same system. Maybe dooming and cursing this system. They could change it. Still, they are doing the same process over and over again. In the end, scientist are just censoring themselves.

Do you know what is even worse than negative expectults? Let us assume you have a collaboration with another group and they should do something for you (measure, synthesize, etc). After a while, they tell you there were “no results”. “No results?” you ask. “Yeah, no results. Did not work.” they say. This is a direct result of above policy and I am sooo tired of this. I spend (i.e. waste) so many hours of tearing answers out and getting the actual results from them, so we can track down issues and work on them. Why not just say “This is the spectra. It does not show the expected product lines, but here you can see the lines for educt 1, 2, 3, and an unknown line. What do you think?”. Does this only happen to me?

How do you fight censorship? By transparency, i.e. open science. However, you have not only to publish reviews of manuscript (versions), which were accepted, but on all those which were not accepted. Transperancy does not work in one direction, only. Of course, this renders a distinction between accepted and not accepted publications completely useless. So, simply let the people publish whatever results they have. Let everyone review and assess the work. In public. This is the only way.

For assessing the results we want to exclude any (personal) expectations out of it. Otherwise, it will only cause discussions on virtual experiments to perform, which may or may not show some point the reviewer wants to make – most likely to prove somehow that the authors did not do the experiments properly or at all. Well, but if you want to do more experiments, then do it. Write it up and publish it yourself!

Also, is it even ethical to always assume the worst? Why not just assume the authors did everything right (pro reo) and write supportive reviews instead of assuming they were all douchebags (contra reo) and try to destroy their work?

Ok, we roughly discussed now what we want to assess. How can we meter it? This is what the next section is about.

Metering the quality of scientific work

If you read the previous section, then you can already presume the conclusion of this section. There is no specific metric, which can do what we want. Each work is individual and, therefore, should be treated individually. Read individually. Reviewed individually. Discussed individually. Assessed individually, by words and language not by some arbitrary metric system.

Even formal things are impossible to meter. Scoring or measuring the quality of explanation and presentation, for example. Text styles are as many in number as there are people. Some might come up with ideas such as “giving the text to 10 random-selected, undergraduate students – every student who understood it is a point”. This is random, arbitrary, and elaborate.

Many things could be considered binary maybe trinary, such as logic of an explanation or reproduciblity of an experiment. The explanation is or is not logic (or partly). The experiment can fully, can partly, or cannot at all be reproduced. Integers could be assigned to these states (e.g. 0, 1, 2). Then, you could try to count these things and divide them by the total amount, e.g. count reproducible experiments. I explained before why counting things to quantify quality is a bad idea. For experiments, where does one experiment start and another one ends? Is setting a solution to a certain pH one or two experiments (adding acid/base as one, measuring the pH as the other)? Two simple experiments may be easier to reproduce than an experiment involving the Large Hadron Collider.

Let us assume that we could somehow meter the quality of the invidual parts, viz. intention, performance, and results. How will the individual parts be weighted? For the last part of my post, I set them to 33% each, mainly to reduce the importance of and focus on the results section. Difficult. Also, all section will most likely have different metric systems unless we implement a simple 5-stars-option (this works good for hotels all over the world, right?). How to combine different metric systems to a final one?

Another option would be badges! Achievements! Everyone likes achievements, right? Let us give paper the ‘Golden Reproducibility Badge’ for works being replicated by at least three other research groups! Let us give people the ‘Mo-Mo-Monster Review’-Achievment for writing ten good (respectful and helpful) reviews! At least they are very popular among the open communities. Why not in science?

As I wrote before, in the end we only seek THE one tool to assess all scientific work! Maybe someone in future finds a nice system. I do not know. No one can know this. However, I know that we become so focused on this quest that we already forgot about the thing, which matters most: the scientific content behind the number(s).

Ethics for a new scientific millennium

In another article I already described the imbalance of so-called peer-reviewers and authors of a submitted manuscript. Anonymous peer-reviewers have been granted power. Enforcing their anonymous point of view on authors. Demanding more and more experiments and citations. Being a sexist. Being douchebags. However, being a douchebag or sexist is independent of anonymity. For instance, see several Twitter ‘discussions’. I think, we need some guidelines for assessing and discussing in a scientific context.

Of course, there already a bunch of guidelines and rules for good scientific practice, which are enforced by research foundations like DFG. However, all of these guidelines and rules are only for creating scientific work (i.e. scientific misconduct, which is important!), but there are no real guidelines for assessing scientific work. So, I wrote up some ethical guidelines, which might help you and others. I do not and will not want to call them rules, since I am not seeking to enforce them on anyone (see # 1). They are in no specific order.

  1. I do not enforce my opinions and views on others, no matter what. All my comments, remarks, and assessments are meant to be respectfully written recommendations and advices.
  2. I will not assess any scientific work by its results only nor will I ever use or apply the arbitrary concepts of negative and positive expectults, or no results.
  3. I am aware that I might be wrong on anything. If I am wrong, I will admit this. If I am not sure about something, I will admit this. If I have no clue, I will admit this.
  4. I will not support or tolerate reproducibility by obscurity. Performances of experiments should be as accurate as possible. Accuracy is mandatory.
  5. I will not demand more results, experiments, citations (esp. on my own work), or other things for the sake of. Additional things should offer added value. Also, they should not be mandatory.
  6. I will not use any metric for judging or proving the quality of scientific work.
  7. I will bear full responsibility for my assessment, comments, and remarks as authors of scientific work bear full responsiblity for their work.
  8. I will not tolerate, obscure, or turn a blind eye on any form of discrimination, harassment, or the like, at any point.
  9. I do not directly or indirectly force people to act in an improper or unethical way.

Some of these points remind you probably of rules and guidelines in discussion forums. But what is assessing work other than a discussion? At least it should be one. Maybe you find the list redundant. Maybe you find some things be über-natural. Well, please go ahead and search for the lists of all these ‘respectful’ comments from reviewer 3.

This list and its points are not set in stone. They are mine. I try to follow them and maybe extend them in future. Everyone can make his/her own list. My point is just: We need ethical guides for assessments. They will not turn douchebags to upright people – I know this. However, they are a tool, which allows me to clarify my position and distinguish myself from douchebags. I simply want to do science.

Final remark

I hope, you liked my little contribution. Leave a comment with your own point of view and share it (and mine) with others!

At least do not call it ‘peer’-review.

First, I want to show you the definition of the word ‘peer’ from Wiktionary. The one in the Oxford Dictionary is similar.

Etymology 2
From Anglo-Norman peir, Old French per, from Latin par.

peer (plural peers)

  1. Somebody who is, or something that is, at a level equal (to that of something else).
  2. A noble with a hereditary title, i.e., a peerage, and in times past, with certain rights and privileges not enjoyed by commoners.
  3. A comrade; a companion; an associate.

Source: Wiktionary

I think this definition is very clear and explains very well what a ‘peer’ is. I consider most of my colleagues and friends peers despite their actual title or degree. I can walk up to anyone of them and ask them for advice or to review something I did and wrote (and vice versa, of course). ‘Look, is this understandable? How did I present the data or the experimental setup? Is something missing? Can you please check language and spelling? …’ I think, you get the idea.

After reviewing they will come back to me and we will discuss their suggestions, critics, remarks, and other comments. We are both open in this discussion and its outcome, simply because no one depends on the other one. It does not matter if I do not accept everything (or anything at all). My peer does not insist of taking over everything (or anything at all). Sometimes really nice and new ideas can rise from such a discussion, which improve the work (‘Did you think of using this for …?’). We both meet at eye level, true peers, because we know each other – background, experience, oppinions, point-of-views on certain things, etc. We know these things, because we are able to find out, since we know who the other person is. We can talk to each other. We can look up work we did before. Etc.

Sometimes my peer-reviewer asks why I did a particular thing in this particular way. I will explain. We discuss. In the end, my reviewer could take along something new from the discussion, as well. Not surprising, since both of us are peers, this whole process provides equal opportunities (learning, improving, …) for both of us.

Now, let us switch to the so-called blind ‘peer’-review process of most journals out there. I send the manuscript to an editor of a journal I want to publish in (indirectly over some very static webpage, but still). In the end the manuscript is forwarded to some reviewers, I do not know. I maybe can assume that the editor at least selected one of the five demanded suggested reviewers – but who knows? Not me, for sure.

While I as applicant (well, suppliant) try to make an effort in writing a nice cover letter, I can hardly expect any salutation or even complete sentences from my reviewers. Do not know if it is my German background or just me, but such things offend and insult me. It shows (to me) that a person does not care at all, because the person has not to. Being harsh, aggressive, ‘bitchy’, insulting, cynical, ironical, sarcastic? No problem on this side.

Suppliantly, I tolerate and accept remarks, comments, critics, and point-of-views without (great) discussion. On top, I will thank(!) the reviewers for their comments and suggestions. I – as others – just take the line of least resistance, the primrose path for scientific publishing.

There was this one reviewer who told me and my co-author not to invent words such as programmatically. I felt young and rebellious. I wanted to send him a free copy of the Oxford Dictionary, but couldn’t – I did not know who the reviewer #3 was. I changed the sentence(s) and avoided to ‘invent’ words. End of rebellion.

Of course, I know that these reviewers are my scientific peers. Well, actually. I do not know. People and Wikipedia tell me that. I cannot check or review the professional expertise of my reviewers.

For fun, consider this: What exactly prevents an editor of Food & Functions to ask Vani Hari for reviewing? Only the editor knows. No one can check. Not during the process. Not later.

The reviewers, however, can check. They have my name and the power of Google, Scifinder, or ISI Web of Knowledge/Science. They can look up my work and see my expertise (or the lack of). This can change their opinion on my manuscript or the way they formulate their comments. I have to guess.

Do I assume the reviewer has a broad but general knowledge in this field but is a novice to this particular technique we are describing in our manuscript? Could insult the reviewer, if I start to explain simple things to him. Do I really want to talk about vocabulary (see above) with the reviewer? Could insult him, if a German tries to explain English to a native speaker. Also, a simple comment could mean something completely different depending if the person is an expert or novice to this field. Misunderstanding could annoy the reviewer. Commenting on reviewers comments is like gambling.

Now, may I ask you, my dear reader, where exactly this is ‘peer’-reviewing?

Post scriptum, I want to add three things:

  • Do not get me wrong: There were some really good suggestions in every review-round. Sometimes they changed a great portion of the manuscript and improved the overall work. But don’t reviewers deserve credit for this?
  • I do not consider reviewers ‘gatekeepers’ as some people do. In the end, it is the editor’s decision. The editor could completely ignore the reviews and let the manuscript pass (or not). Editor’s decision. Editor’s responsibility. Editor’s gatekeeper.
  • Of course, the main thing is that the system works and there are absolutely no flaws. I mean, could you instantly bring up a single case of fraud? On top, the quality output of ‘peer’-reviewing speaks for itself! Especially, in the most reputable journals, right? RIGHT?

Somethings strange in the (academic) neighbourhood. Who ya gonna call?

(Warning: Rant incomming.)

Some weeks ago I finished my new proposal and submitted it to Deutsche Forschungsgemeinschaft (DFG; English: German Research Foundation). Among others I applied for some non-personnel costs – including publication costs. You can apply for € 750 per year, which should suffice for submitting papers but also for printing costs (posters). In sum, that are € 2250 for a 3 year project.

I wonder. How am I ever able to pay any article processing charges with this kind of funding? For instance, the new Science Advances Journal charges $ 3000-4000 per article! Of course, this is an extreme case. But even the ‘moderate’ charges are around € 1500. The flagship of open access, PLOS ONE, is not cheaper

This not a sole problem with open access journals, though. If you look at more traditional journals such as the Journal of Separation Science, you will find charges for everything. Pages. Color figures. Everything.

What is the solution for a early-stage researcher like me? Save money to only publish one or two papers per 3-year-cycle? Underpay graduate students even more (not that I will!), so they can publish? Use your own money?

How comes that I pay for (gold) open access – i.e. transparent science – but the publisher can’t transparently tell me what the money is for? Applying for a doi? Paying the reviewers? *cough* Of course, they have to pay servers, some personal, etc. But couldn’t that be covered by fixed deals like BioMedCentral has with the University of Regensburg?

University of Regensburg is a member of BioMedCentral. No charges for authors! Hooray!

University of Regensburg is a member of BioMedCentral. The charges are completely covered by the membership, i.e. no charges for the authors! Hooray!

I have a problem here. The very first question for me at every journal is: what will it cost me to publish in there. Not the quality. Not the audience. Not the content. The costs are top priority. Should that be the case?

Somethings strange in the (academic) neighbourhood. Who ya gonna call?

Thomson Reuters, spamming you since 2008!

The last few days I got two spam mails from Thomson Reuters. Same wording. Searching the web, I found out that a) other got these mails, too, and b) that the wording of this emails have not changed since 2008! Only the links, which now point towards thomsonreuters-authorconnect.com (I removed them and some HTML from the message below):

Date: Tue, 19 Aug 2014 19:50:11 -0400
Reply-To: “ISI Research” <...@thomsonreuters-authorconnect.com>
From: “ISI Research”
To: “S Kochmann”
Subject: Urgent: Breaking news for publishing authors
MIME-Version: 1.0

ISI Opt-in

View as a Web page

Dear S,

Please be aware that newly enacted e-mail legislation prohibits
future contact with you if we do not receive a reply to this
communication. To ensure that you receive critical breaking
news and information about your field, please reply promptly
by clicking here.
I am certain that you will find this information intriguing and
essential to your work.

As a publishing author represented within Current Contents®,
Biosis Previews®, or Web of ScienceSM, from Thomson Reuters,
you require the latest news and resources to stay current in your
area of research. That’s why we think you’ll benefit from getting
valuable research information right at your desktop. At no cost
or obligation!

From time to time, we would like to e-mail you:

  • “Call for Papers” requests from scholarly publishers
  • News related to your field of research
  • Information about journals and books in your areas of interest
  • New scientific applications relevant to your field of research

From time to time, Thomson Reuters works with other companies to provide you with information about relevant third party product and service offerings that may be of interest to you. Your business contact information may be made available to such other companies to facilitate communications.

If you would like to receive information from Thomson Reuters or
other carefully selected organizations,
click here.

We hope you will find this information intriguing and essential
to your work.


George Kowal

Web of Science & Biosis Author Connect®
Thomson Reuters
1500 Spring Garden Street
Philadelphia, PA 19103

Looking at the salutation and the to-header, viz. ‘Dear S’ and ‘S Kochmann’, it is clear to me that they are generating the mails from some publication database (probably Web of Science?). Bernd-Christoph Kaemper suggests that they are one of the biggest address dealers in the scientific world. They do their business by exploiting the names of ISI & co. I think he is right…

No, Thomson Reuters, I do NOT want you to mail me. Never.

Seminar time

Over the last year, I noted down the times of every of our workgroup seminar. Well, not for every seminar but for 26. Our seminar is meant to be once a week. We talk about general things (instruments, conferences, publications, …) as well as individual projects (everyone in the group should give some information about the progress/problems/issues of his/her project). During the semester we also have a presentation from someone of the group (about 20 minutes).

Now, I did some statistics about it:

Time spent in 26 workgroup seminars over the last year (from 25th of September to 6th of August).

Time spent in 26 workgroup seminars over the last year (from 25th of September to 6th of August).

I wonder. Is 83 ± 35 min a lot of time for a workgroup seminar for about 10 people?

Tips from Ken for starting professors

A few days back, Kenneth Hanson shared his experiences of his first year as assistant professor (read it!). I asked him if he could give one, single advice for someone starting his or her professorship.

Here is his answer:

Hello Sven,

That is a tough question. I spent a few days thinking about it and could not come up with one definitive piece of advice. Here are several:

1) Be willing to let go of lab work. We spend most of grad school and our postdocs in complete control of our projects and day-to-day measurements. It is basically impossible to maintain that level of control when supervising several people/projects. The sooner you trust your students and let go of lab work, the sooner you can dedicate to writing papers/proposals.

2) Prioritize based on importance and rate-determining step. Prioritizing based on importance is easy. There are some things we want done first. However, in addition to importance you have to account for your reliance on other people that do not have the same priorities. Just assume that if you are relying on someone else for equipment/training/renovations that it is going to take longer than you think and longer than they say. Make the initiating steps and follow up on those projects a priority even if they are lower on the list. I won’t suggest that you hound people aggressively but friendly reminders will get you far.

3) Be a good coworker but be willing to say no to senior colleagues. Sometimes you just can’t take on another project.

4) Set up group meetings as soon as possible. It will likely start out as a regular literature review or you explaining an instrument/concept but at least it gets something on the calendar. This formalizes the schedule and gives you a venue to talk to prospective students even through your lab might not be up and running.

5) Partition your day, in formalized time blocks, i.e. 8-10 course content, 10-12 proposals, etc. You cannot wait for those two open days to write a proposal, those days will never come. Instead you should rely on a few hours per day. It adds up very quickly.

That is all I have for now.
Good luck.

Lets see 🙂

Peer-review ring at SAGE’s Journal of Vibration and Control

SAGE anounced the retraction of SIXTY papers from the Journal of Vibration and Control. These papers had been published by a peer–review and citation ring. How does such a ring work? Actually, it is very simple:

While investigating the JVC papers submitted and reviewed by Peter Chen, it was discovered that the author had created various aliases on SAGE Track, providing different email addresses to set up more than one account. Consequently, SAGE scrutinised further the co-authors of and reviewers selected for Peter Chen’s papers, these names appeared to form part of a peer review ring. The investigation also revealed that on at least one occasion, the author Peter Chen reviewed his own paper under one of the aliases he had created.

I really despise such a behaviour. You know, I myself am always thrilled to get every bit ‘right’ in my publications about doing intersting stuff. Preparing it for weeks, submitting it, being excited and nervous about the reviewers’ comments, and so on. And then someone has just spends all his time and resources on cheating. SIXTY papers!

Find the full press release here.

The PHD Movie 2: Still in Grad School by Jorge Cham

Jorge Cham, the creator of the famous PHD comics and the PHD Movie, is looking for some money on kickstarter to produce a sequel. There are nice rewards, such as a signed manuscript, a poster with signature of the cast, and/or a personal comic of you.

If you have not watched (or bought) the first movie, you can watch it free this month on phdmovie.com.

Now, go on Kickstarter and support him!

PHD Comics