How to think about science and becoming a scientist(jseliger.com)
jseliger.com
How to think about science and becoming a scientist
http://jseliger.com/2012/04/17/how-to-think-about-science-and-becoming-a-scientist/
9 comments
My friends and I build a website for scientists to discover & share journal articles that are worth reading, to discuss scientific ideas that are worth spreading, and to connect with people who share similar interests: http://www.pubup.org/ . Please let me know what you think of the idea and the website. Thanks!
The idea is great, but just so you know... my experience in academia (anecdotal) suggests that Mendeley already has a pretty substantial lead: http://www.mendeley.com/
Me and my friend use facebook, twitter, and (mostly) have appoinment to share interesting paper to read. Discussing paper offline are the reason why we meet. Haha..
True, but it seems to me that Mendeley and us are addressing different aspects of the same problem
Can you elaborate? The frontpage of PubUp seems strikingly similar to the "papers" page at Mendeley: http://www.mendeley.com/research-papers/
I'm completely open to an alternative service (or even a complementary one). So... I guess what I'm trying to say: Give me, one of your intended customers, a compelling use scenario or value-add proposition that might compel me to switch.
I'm completely open to an alternative service (or even a complementary one). So... I guess what I'm trying to say: Give me, one of your intended customers, a compelling use scenario or value-add proposition that might compel me to switch.
There is an infinite amount of work in science because the universe is big and we don’t really understand it and we probably never will.
There may be an infinite amount of work in science, but there is a finite (and very unevenly distributed) number of grants. Your conclusion rings true to me.
There may be an infinite amount of work in science, but there is a finite (and very unevenly distributed) number of grants. Your conclusion rings true to me.
What does "adjusted for IQ" mean?
I think it means that if you created a model that used IQ, quantitative skills, and working hours as inputs and tried to predict pay across all jobs in the US, it would predict that science jobs should pay higher than they actually do. Which leaves open the question of whether those variables are actually the most predictive of pay levels in non-science jobs; I suspect not.
It means normalizing a certain data set for the IQ that the subjects from whom these data points were taken have. In other words, adjusting one property of something be an amount relative to some other property of that something. This is done in cases where it is suspected that this one property influences the other. In this case, the assumption (quite reasonably, imo) is that (in the aggregate) people who are smarter make more money.
It means comparing people in different jobs who have the same IQ.
Haven't we reached the point yet where the whole idea of IQ testing is pretty discredited? And adjusting for IQ, meaning that someone is smart therefore they are expected to earn more money? It sounds like "taking into account these variables, and introducing this ridiculous one to allow me to adjust the outcomes as needed."
Well if you don't agree that somebody with an IQ of 120 can be reasonably expected to be better at making money, and in the aggregate people with that IQ do actually make more, than somebody with an IQ of 80, then you have such a radically different view from the mainstream that any discussion is pointless.
FYI, adjusting for certain variables is a fundamental aspect of statistics. All studies in social sciences and economics of real-world data do so, because no real-world effect can be isolated to the point that it can be measured independently.
"Haven't we reached the point yet where the whole idea of IQ testing is pretty discredited?"
What? No, of course not. Are you saying that there are no people who are smarter than others?
FYI, adjusting for certain variables is a fundamental aspect of statistics. All studies in social sciences and economics of real-world data do so, because no real-world effect can be isolated to the point that it can be measured independently.
"Haven't we reached the point yet where the whole idea of IQ testing is pretty discredited?"
What? No, of course not. Are you saying that there are no people who are smarter than others?
IQ is not synonymous with intelligence, it is married to the 20th century philosophy of psychology and history of testing methods.
For IQ to simply mean the intelligence scale normalized so that average intelligence = 100 would take a big marketing effort amongst the education and psychology communities.
Even if it were divorced from the twists and turns of its historical development, it seems pretty clear that at it's best IQ can aggregate the values of creativity, lateral thinking, calculation, memory-retrieval, memory-storage, memory-organization, (even, despite tester's best efforts) domain knowledge together and replace them with one number.
I think that some of the "everybody learns differently!" stuff has jumped the fence and become an old wives' tale, but there has to be a happy medium between assigning someone a 40 column printout to summarize their intelligence and slapping one number on it.
[This is not to mention all of the shift in emphasis away from intelligence towards results and output based partially on Outliers, and partially on the idea that if you praise kids for an inherent trait that they have no control over that they will stop playing to win and start playing not-to-lose.]
For IQ to simply mean the intelligence scale normalized so that average intelligence = 100 would take a big marketing effort amongst the education and psychology communities.
Even if it were divorced from the twists and turns of its historical development, it seems pretty clear that at it's best IQ can aggregate the values of creativity, lateral thinking, calculation, memory-retrieval, memory-storage, memory-organization, (even, despite tester's best efforts) domain knowledge together and replace them with one number.
I think that some of the "everybody learns differently!" stuff has jumped the fence and become an old wives' tale, but there has to be a happy medium between assigning someone a 40 column printout to summarize their intelligence and slapping one number on it.
[This is not to mention all of the shift in emphasis away from intelligence towards results and output based partially on Outliers, and partially on the idea that if you praise kids for an inherent trait that they have no control over that they will stop playing to win and start playing not-to-lose.]
I'm not sure if you're agreeing or disagreeing with me? Yes of course there are various definitions and measurement methods of 'IQ' and 'intelligence' and one can define all of them in various ways. Exact definitions aren't interesting for the current purposes. What I said was, some people are smarter than others, even when considering orthogonal traits. If we hypothetically consider 'intelligence' as a combination of trait A, B and C, and we choose A, B and C carefully enough so that we can score or normalize each of them to a scale of 0-10, then Alice with a score of 8 on each of them is more intelligent than Bob who scores 4 on each of them. Now in the margin you can argue who is more intelligent when the scores are 5-8-4 and 5-4-8 but that doesn't take away from the point.
It's not like we're talking about one specific methodology for measuring IQ. The whole argument is in the context of the OP arguing that correcting for intelligence is necessary for making a meaningful comparison between wages earned (basically, it's discounting for opportunity cost). Which is totally reasonable and obvious.
It's not like we're talking about one specific methodology for measuring IQ. The whole argument is in the context of the OP arguing that correcting for intelligence is necessary for making a meaningful comparison between wages earned (basically, it's discounting for opportunity cost). Which is totally reasonable and obvious.
I think we were agreeing
I don't think I made the argument that being functionally disabled is meaningless, but straw men live in all discussions at some point.
My argument is that above average and even extraordinary intelligence have no correlation to money making. Smart people live in poverty all the time. To say that expectations of earned income should be adjusted for IQ is meaningless in that context because the adjustment would be zero. Making money doesn't derive from general intelligence, but from how it is applied and luck. There are many smart technical people on this message board who are clearly lucky that the world is in the middle of a massive expansion of technically complicated economic areas like apps and programming in general. It allows them to achieve wealth that otherwise is not a predetermined given.
When I refer to IQ testing I refer to the concept of a universalized IQ test that can, without cultural bias, give an objective measure of intelligence.
My argument is that above average and even extraordinary intelligence have no correlation to money making. Smart people live in poverty all the time. To say that expectations of earned income should be adjusted for IQ is meaningless in that context because the adjustment would be zero. Making money doesn't derive from general intelligence, but from how it is applied and luck. There are many smart technical people on this message board who are clearly lucky that the world is in the middle of a massive expansion of technically complicated economic areas like apps and programming in general. It allows them to achieve wealth that otherwise is not a predetermined given.
When I refer to IQ testing I refer to the concept of a universalized IQ test that can, without cultural bias, give an objective measure of intelligence.
"My argument is that above average and even extraordinary intelligence have no correlation to money making."
Well you're objectively wrong. Go to your national data office and look at income vs education (using education as a proxy for intelligence is not perfect but works OK enough for this purpose). You will see strong correlations between the two. (not perfectly linear, and not perfectly correlated, but strong enough to be not random). Look at any data set of reasonably stable and free countries that have these two data points, and you will find the same.
"Smart people live in poverty all the time."
Anecdote != data.
Well you're objectively wrong. Go to your national data office and look at income vs education (using education as a proxy for intelligence is not perfect but works OK enough for this purpose). You will see strong correlations between the two. (not perfectly linear, and not perfectly correlated, but strong enough to be not random). Look at any data set of reasonably stable and free countries that have these two data points, and you will find the same.
"Smart people live in poverty all the time."
Anecdote != data.
> Haven't we reached the point yet where the whole idea of IQ testing is pretty discredited?
No, the opposite! Throw together any list of questions requiring intellectual ability, on any subjects you choose (making sure to have a wide range of difficulty). Use the list to test a few thousand people selected at random from the same society. Perform principal components analysis (a type of statistical cross correlation) on the answers. The answers will turn out to correlate with a single characteristic of the individual test takers. This common factor is labeled g, general intelligence. There is virtually no sign of multiple intelligences or other factors, just one honking big signal for the g factor.
> And adjusting for IQ, meaning that someone is smart therefore they are expected to earn more money?
There have been large studies of people from the general population, with the scientists measuring every data point they can lay their hands on. It turns out the only factor that significantly affects adult income is IQ. Earned income is almost totally uncorrelated with race, skin color, culture, family wealth, family social rank, location of residence, school system, characteristics of siblings, and so forth. IQ also strongly predicts criminality.
Studies of twins separated at birth show huge IQ correlations between identical twins, but IQ correlations between fraternal twins are no greater than for sibling pairs from different pregnancies. So IQ is mostly inherited, and mostly fixed by the time of conception. In other words, genetic.
No, the opposite! Throw together any list of questions requiring intellectual ability, on any subjects you choose (making sure to have a wide range of difficulty). Use the list to test a few thousand people selected at random from the same society. Perform principal components analysis (a type of statistical cross correlation) on the answers. The answers will turn out to correlate with a single characteristic of the individual test takers. This common factor is labeled g, general intelligence. There is virtually no sign of multiple intelligences or other factors, just one honking big signal for the g factor.
> And adjusting for IQ, meaning that someone is smart therefore they are expected to earn more money?
There have been large studies of people from the general population, with the scientists measuring every data point they can lay their hands on. It turns out the only factor that significantly affects adult income is IQ. Earned income is almost totally uncorrelated with race, skin color, culture, family wealth, family social rank, location of residence, school system, characteristics of siblings, and so forth. IQ also strongly predicts criminality.
Studies of twins separated at birth show huge IQ correlations between identical twins, but IQ correlations between fraternal twins are no greater than for sibling pairs from different pregnancies. So IQ is mostly inherited, and mostly fixed by the time of conception. In other words, genetic.
also, pretty much all the low-hanging fruit has been done in science. Even if we allow for science to be infinite, each new brick in the wall of science requires an ever-increasing amount of resources to gain, and usually those bricks are also much smaller.
My old company made what was essentially datalog viewing software. Version 1 of the software was basically just squiggly lines going across the screen. People loved it, because previously they only had squiggly lines going across paper, and a 20-minute recording was the size of a phone book. But version 2 of the software required far more developer work, and had much more polish and detailed algorithms underlying the analyses... but people bridled at 'having to pay again' when 'we don't really get that much for it'. More work, smaller bricks, less appreciation of what it takes to get there...
My old company made what was essentially datalog viewing software. Version 1 of the software was basically just squiggly lines going across the screen. People loved it, because previously they only had squiggly lines going across paper, and a 20-minute recording was the size of a phone book. But version 2 of the software required far more developer work, and had much more polish and detailed algorithms underlying the analyses... but people bridled at 'having to pay again' when 'we don't really get that much for it'. More work, smaller bricks, less appreciation of what it takes to get there...
I don't have the requisite knowledge to comment on fields other than the life sciences, and I certainly agree with your point that every new scientific and technological advance necessarily has to be more sophisticated than the one(s) that it's built upon. But the notion that the past was chock-full of low-hanging fruit just waiting to be picked seems exaggerated and doesn't give enough credit to the people who did all that work that, in hindsight, looks easy, trivial, and obvious, but at the time certainly required significant insights, advances, and effort.
John LaMattina, former president of R&D at Pfizer, weighs in: http://www.forbes.com/sites/johnlamattina/2012/03/02/there-h...
John LaMattina, former president of R&D at Pfizer, weighs in: http://www.forbes.com/sites/johnlamattina/2012/03/02/there-h...
I am graduating this spring with a materials science degree from Stanford. Materials science has the absolute most boring set of classes (seriously, it's really bad). However, Material science also has what I think is some of the most ground-breaking, fascinating, and magical scientific research topics out there, from nanotech, biotech, and energy, to novel electronic form-factors, batteries & fuel cell, and much more.
therefore:
Degree Classes != Actuality.
therefore:
Degree Classes != Actuality.
Arn't the biological sciences notorious for having way too many Phds than relevant research jobs/professorships available? Scientific research should be encouraged in undergrad with the caveat that it really only qualifies you for grad school. Instead, one could spend summers in internships and enjoy more employment opportunities upon graduation. Research can be fun, but reality bites.
I spent many summers in research labs doing different kinds of scientific projects (mostly in chemistry and physics). It was not only fun, but very rewarding and resulted in a strong foundation in scientific thinking which has always been useful, regardless of the specific job. Part of the reasons I moved towards the biological sciences in grad school was partly due to reality. As a quantum chemist (which I was at the time), opportunities were limited. It was also the time that computational biology was getting really interesting. I joined a startup 2 weeks after finishing my defense.
Caveat: I haven't been a practicing scientist for a while.
Caveat: I haven't been a practicing scientist for a while.
Basically I agree that "when in doubt, learn science." In American society, we have more of the norm of "when in doubt, don't learn any science." And that's counterproductive.
In other countries, there are explicit and implicit reminders that science students are smarter than non-science students. In my dad's (European) high school, students were literally tracked from A to F; A was math, B was physics, biology and social sciences were somewhere in the middle, and vocational school was at the bottom. Harsh? Yeah. But it meant that generically smart and ambitious kids wound up in the hard sciences by default.
In other countries, there are explicit and implicit reminders that science students are smarter than non-science students. In my dad's (European) high school, students were literally tracked from A to F; A was math, B was physics, biology and social sciences were somewhere in the middle, and vocational school was at the bottom. Harsh? Yeah. But it meant that generically smart and ambitious kids wound up in the hard sciences by default.
What country was that? In my original European high school, those with the highest grades went studying the classics, with maths being a fallback for those who didn't quite make the cut.
Interesting -- my dad went to school in Ireland and had tracks similar to the previous commenter, the A track being the most math intensive (although everyone on that track also studied Latin and Gaelic). Where was your high school?
Belgium.
I disagree with a lot of points made here. First, this is focused exclusively on the biological sciences, and is largely not applicable to other fields (hence the title is misleading). Second, there are a lot of personal anecdotes which don't move the central ideas forward. Finally, there was little in the article that discussed how to think about science, most of it was how to pursue science.
That being said, I agree with the sentiment. Most of what we teach undergraduates is about the knowledge science is produced, rather than about the process of doing science itself.
That being said, I agree with the sentiment. Most of what we teach undergraduates is about the knowledge science is produced, rather than about the process of doing science itself.
I didn't read the whole thing - it's not concise, that's for sure - but the general advice seems to be: Go find a lab job and see if you like it. Though his examples are specific to biology, I can't figure out what part of that advice is specific to biology. I did it in experimental physics and it worked out just fine.
Sure, the article is about about pursuing science rather than thinking about it. But that's the author's whole point. Enjoying a career is all about enjoying the day-to-day work: If you love thinking about DNA but don't love pipets, you're going to be unhappy a lot of the time, because life in the lab is about 10% deep thought and 90% pipets. (Or, in the semiconductor laser lab: 10% deep thought, 50% misaligned optics, and 40% mysterious process problems that you will never entirely understand, but which you will eventually solve by spending months on end turning knobs in a strategic manner.)
Sure, the article is about about pursuing science rather than thinking about it. But that's the author's whole point. Enjoying a career is all about enjoying the day-to-day work: If you love thinking about DNA but don't love pipets, you're going to be unhappy a lot of the time, because life in the lab is about 10% deep thought and 90% pipets. (Or, in the semiconductor laser lab: 10% deep thought, 50% misaligned optics, and 40% mysterious process problems that you will never entirely understand, but which you will eventually solve by spending months on end turning knobs in a strategic manner.)
Agree about low information density of article.
Same general advice applies in engineering: do your best to attach yourself to a lab, and see if it catches your fancy. Best way to test-drive a career choice.
He's kind of down on textbook-and-problem-set coursework and large lecture classes. This is not universal. Some large lectures are large for a reason -- the professor is a star. And some textbooks are really good, and some problem sets are worth sweating over.
Same general advice applies in engineering: do your best to attach yourself to a lab, and see if it catches your fancy. Best way to test-drive a career choice.
He's kind of down on textbook-and-problem-set coursework and large lecture classes. This is not universal. Some large lectures are large for a reason -- the professor is a star. And some textbooks are really good, and some problem sets are worth sweating over.
Most of what we teach undergraduates is about the knowledge science is produced, rather than about the process of doing science itself.
Which is not entirely a useless endeavor; if you don't know about what has already been discovered, how can you build on it and go further? How will you know what has already been tried?
Which is not entirely a useless endeavor; if you don't know about what has already been discovered, how can you build on it and go further? How will you know what has already been tried?
If you can, don't choose. Get 2 degrees. I studied physics. I make a lousy physicist, but I learned a lot, got to play with some cool stuff and it gave me a whole new appreciation of the world and how it worked.
It is also the last time you get to play with lab equipment that costs hundreds of thousands of dollars.
Absolutely no regrets.
It is also the last time you get to play with lab equipment that costs hundreds of thousands of dollars.
Absolutely no regrets.
If one were truly amazed by science, nothing would be in ones way to becoming a scientist; the knowledge is all there, the tools are all there (reactants, catalysts and conditions for illegal materials notwithstanding), and if you are indeed one of these people who are destined to be a scientist ("he who seeks knowledge"), rather than an engineer ("he who wants hands-on") then there is nothing to explore than the minds of your own, or the minds of others (by means of scientific databases, readily available online).
So how would you go about learning LC-MS/MS and applying the various separation techniques to small molecules or proteins?
Instruments start at 250k and many in universities are decades older than what is currently used in industry. For small molecules, the most challenging (and exciting) library's of compounds are owned by third parties.
It is my opinion that science, much like programming, one has to do it to learn it. There are limitations to the knowledge you gain without being hands on. See E.O Wilsons musings of the impact his formative years and post grad school wanderings in the south pacific. He is certainly a scientist but much of his knowledge and insight is due to the hands on approach he used to to gain that knowledge.
Instruments start at 250k and many in universities are decades older than what is currently used in industry. For small molecules, the most challenging (and exciting) library's of compounds are owned by third parties.
It is my opinion that science, much like programming, one has to do it to learn it. There are limitations to the knowledge you gain without being hands on. See E.O Wilsons musings of the impact his formative years and post grad school wanderings in the south pacific. He is certainly a scientist but much of his knowledge and insight is due to the hands on approach he used to to gain that knowledge.
Completely agree. I don't think I am going to put a 900 MHz NMR or an Orbitrap in my basement :)
I know! I can just hear my daughter, 'Daddy, turn that down. I'm trying to watch Doc McStuffins. Why do you have to do science on a Saturday morning?'
Then there is the electrical bill and I already get hell from my wife for the water bill during the summer months.
Then there is the electrical bill and I already get hell from my wife for the water bill during the summer months.
I obviously don't know your background, but a statement like this: "If one were truly amazed by science, nothing would be in ones way to becoming a scientist" expresses the kind of sureness in the motivational power of joy and wonder that one I mostly hear from non-scientists (or non-literary people: replace "science" with "literature" and you'll get something similar).
The ones I know who are actually grad students or professors tend to take a much more pragmatic view.
I wrote this in another thread: "'Science is a wonderful thing if one does not have to earn one's living at it.' -- Albert Einstein" -- from Philip Greenspun's Women In Science: http://philip.greenspun.com/careers/women-in-science .
The ones I know who are actually grad students or professors tend to take a much more pragmatic view.
I wrote this in another thread: "'Science is a wonderful thing if one does not have to earn one's living at it.' -- Albert Einstein" -- from Philip Greenspun's Women In Science: http://philip.greenspun.com/careers/women-in-science .
Much current research is published in journals so expensive that reading them is prohibitive without an institutional subscription.
That was awesomely inspiring and fun to read, actually makes me feel bad a little for pursuing CS :)
The profession of science is really, really hard, and generally does not pay well. But, when you learn something new in science, you have learned something that no one else knows, that is fundamental to the very structure of reality.
To be a happy professional scientist, the emotional stimulus of that kind of discovery needs to be strong enough to carry you through all the hardship.
To be a happy professional scientist, the emotional stimulus of that kind of discovery needs to be strong enough to carry you through all the hardship.
Scientists and engineers expand the size of the economic pie; lawyers mostly work to divide it up differently. Whenever possible, work to be a person who creates things, instead of a person who tries to take stuff created by someone else. There is an infinite amount of work in science because the universe is big and we don’t really understand it and we probably never will. New answers to questions in science yields more questions.
Greenspun makes and attend to his discussion of what grad school in the sciences is like, especially this, his main point: “Adjusted for IQ, quantitative skills, and working hours, jobs in science are the lowest paid in the United States.”
In other words, science is good for society but bad for the individual, from a purely economic standpoint.