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Science

How Scientists Know An Idea Is a Good One 140

Posted by Soulskill
from the does-it-involve-lasers dept.
Physicist Chris Lee explains one of the toughest judgment calls scientists have to make: figuring out if their crazy ideas are worth pursuing. He says: "Research takes resources. I don't mean money—all right, I do mean money—but it also requires time and people and lab space and support. There is a human and physical infrastructure that I have to make use of. I may be part of a research organization, but I have no automatic right of access to any of this infrastructure. ... This also has implications for scale. A PhD student has the right to expect a project that generates a decent body of work within those four years. A project that is going to take eight years of construction work before it produces any scientific results cannot and should not be built by a PhD student. On the other hand, a project that dries up in two years is equally bad. ... the core idea also needs to be structured so, should certain experiments not work, they still build something that can lead to experiments which do work. Or, if the cool new instrument we want to build can't measure exactly what I intended, there are other things it can measure. One of those other things must be fairly certain of success. To put it bluntly: all paths must lead to results of some form."
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How Scientists Know An Idea Is a Good One

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  • by LordLucless (582312) on Sunday March 17, 2013 @07:44AM (#43196305)

    That's not a description of a good idea. That's a description of an idea that fits into an arbitrary 4-year timescale that fits with a PhD program's average length.

    • by sferics (189924)

      Mods... before you rate this as insightful... read the article, maybe?

    • I've heard the average time to get a PhD has increased to 5 years, though I couldn't immediately find a citation for that, so it could just be something one of my fellow grad students said to make ourselves worry about graduating on time less.

      There's also some wiggle room in either. Maybe some physics projects take necessarily 8 years or so, but with many projects in at least cell biology, you can speed it up or shape it to your timescale. Publishing as is, without all the experiments that could be don
      • Re: (Score:2, Interesting)

        by Anonymous Coward

        I can only speak for my own field (physics), but the national average length of a Ph.D. is almost 7 years. This is according to an AIP study I read about 8 years ago. There is a large spike at 5 years (theorists) and a long tail on the high end (experimentalists). Also, during the first two years before you qualify for candidacy you are rather inundated by classwork. In which case, aiming for 4 year project sounds about right. It allows for a bit of a buffer for when things break.

        • Re: (Score:2, Informative)

          by Anonymous Coward

          It is highly dependent on local conditions. In France, PhDs are by definition 3 years long.

          The main point is unaffected by the value of this number, though, just that it exists and is hopefully a small fraction of a person's career.

          • by ACluk90 (2618091)

            In Switzerland at ETH Zurich a PhD usually takes approx. 5 years. Starting a PhD program here requires a Master's degree which is usually obtained after 5 years of studying (master and bachelor together).

          • by Anonymous Coward
            Does that require a Master's degree first though? The 5-7 year PhD programs in the US essentially combines the master's and PhD programs, so you start with a 4 year degree. Some times all you need to get a master's degree while doing a PhD program is to fill out a form half way through, other cases the students don't get a master's degree because it has a slightly different requirement. The place I went would have required me to take a couple more classes for the master's degree, as it required a certain
            • Almost everybody I know who got both a masters and PhD in physics did it for one of two reasons-- 1) they started grad work at a smaller school that didn't have a PhD program (or not much of one) and switched to a larger/better program 2) they expected to work at large companies (e.g. 3M) where the pay scale gave you slightly more money if you had a masters+PhD than PhD alone, even if all you did for the masters was fill out a few extra forms and bind up some intermediate result (that you had anyway) into a

              • by Anonymous Coward
                Some places have the option for both a master's with thesis and a master's without thesis. In which case, those that I knew who took enough classes, because the school happened to offer a lot of classes in their field, did just fill out a form and get a masters along the way. That said, sometimes when you see someone get a masters in a field like physics, it could mean they were considering dropping out of the PhD program and were trying to get something out of the effort even if they failed to get the Ph
    • Or, a series of small interrelated projects.

      That is the customary approach I've seen the last decade.

    • by Shavano (2541114)
      Isn't it better to pick a research plan you can assuredly finish in 2 years and then milk it for another 2 or the grant money runs out or you land a plum job, whichever comes first?
  • by prasadsurve (665770) on Sunday March 17, 2013 @08:06AM (#43196375)
    Science as a process is like Natural selection and just as in Natural selection, one may come with the dead end. This is not necessarily bad.
    To quote Thomas A. Edison, "If I find 10,000 ways something won't work, I haven't failed. I am not discouraged, because every wrong attempt discarded is another step forward".
    • Yep, an experiment that fails can be just as informative as the one that works. Personally I think the summary of TFS of TFA is stating the obvious, "all paths must lead to results of some form" - without results it's not a Phd, it's not even a paper, it's just an opinion.
    • by jasnw (1913892) on Sunday March 17, 2013 @11:53AM (#43197439)
      While you are theoretically correct, you are real-world dead-in-the-water. A big problem with getting science funding these days is what I'll call the Golden Fleece Award Effect (for Sen. William Proxmire's Golden Fleece Award - wikipdeida it). While funding organizations are well aware that a solid negative result in a difficult research area is just as pertinent and useful as a positive one, Congress (the source of all funding) doesn't understand it and doesn't like it. Money out needs to be balanced by succes in. I know many researchers who do 90% of the research needed for a given NSF (or NASA) proposal before they propose it so they can (a) show it will indeed result in success, and (b) it will succeed so they can get more NSF funding. Nothing breeds lack of funding like failure. This is a dumb-ass way to do science, but since all funding comes from the Kingdom of the Dumbasses you get what you'd expect.
      • Nothing breeds lack of funding like failure.

        If only that were true for "War on terror", "War on Drugs", and a host of "Great Society" programs.

        • by nazsco (695026)

          Those are very successful corruption study hypothesis. I fail to see your point

      • While you are theoretically correct, you are real-world dead-in-the-water. A big problem with getting science funding these days is what I'll call the Golden Fleece Award Effect (for Sen. William Proxmire's Golden Fleece Award - wikipdeida it). While funding organizations are well aware that a solid negative result in a difficult research area is just as pertinent and useful as a positive one, Congress (the source of all funding) doesn't understand it and doesn't like it. Money out needs to be balanced by succes in. I know many researchers who do 90% of the research needed for a given NSF (or NASA) proposal before they propose it so they can (a) show it will indeed result in success, and (b) it will succeed so they can get more NSF funding. Nothing breeds lack of funding like failure. This is a dumb-ass way to do science, but since all funding comes from the Kingdom of the Dumbasses you get what you'd expect.

        You hit the nail on the head.

        With basic research, projecting milestones is impossible and everyone from the researchers to the project managers is well aware of that fact. Thus you end up with people proposing research that is already well past proof-of-concept (90% is atypical in my field because of the large overheads) and listing milestones for research that is already being written up. The absurdity is that these results had to be funded from another grant, where you promised to do other research that w

      • by cwsumner (1303261)

        The problem is expecting to get funding from someone else! If they give you money then they own you, and your research.

        Instead get rich on something else, and then fund yourself. Then maybe you can get somewhere. And maybe get rich again.

        Rinse and repeat...

    • by m00sh (2538182)
      There might be infinite ways something won't work. There is no inherent guarantee that it's finite and even if it's finite, it's a small finite number.
    • by Hentes (2461350)

      If there are 10000 ways of doing it and only one of them is right, then finding a wrong one only gives you about 0.0013 bits of information, while finding the right one would give you 13.29 bits. While a negative isn't a waste of time, its value in general is not the same as that of a positive.

  • 4 years.. (Score:5, Informative)

    by dlenmn (145080) on Sunday March 17, 2013 @08:10AM (#43196387) Homepage

    A PhD student has the right to expect a project that generates a decent body of work within those four years.

    Four years? Ha! That's a good one!

    • Re:4 years.. (Score:4, Interesting)

      by dkf (304284) <donal.k.fellows@manchester.ac.uk> on Sunday March 17, 2013 @08:29AM (#43196451) Homepage

      A PhD student has the right to expect a project that generates a decent body of work within those four years.

      Four years? Ha! That's a good one!

      The easiest way to enforce that is for the awarding institution to say that if it isn't done in 4 years, it will be taken as a complete failure. Suddenly, people find that it is possible to write up in time. (Seriously, if you can't stop pissing around "doing just one more experiment" or "reading just one more paper" and write up your thesis, you're a failure as a researcher and should be publicly branded as such.)

      • Re:4 years.. (Score:5, Insightful)

        by Anonymous Coward on Sunday March 17, 2013 @09:03AM (#43196603)

        Four years? Ha! That's a good one!

        The easiest way to enforce that is for the awarding institution to say that if it isn't done in 4 years, it will be taken as a complete failure.

        No, that rule would result in a lot of thesis committees approving completely crap theses. Believe it or not, thesis committee members are human and have a lot of difficulty telling kids that their last four (or five, or eight) years of work are worth no recognition and please leave. Thesis advisors become emotionally attached to their students and want to see the succeed/graduate, even if those students are incompetent. Sometimes you can compensate for the incompetence with time. Only rarely will a thesis committee 'over-rule' the advisor, with their input generally taking the form of 'this would become acceptable if the student adds [foo] over the next year or so.' Mandated time to completion is a recipe for diminishing the quality of theses and migrating a PhD from someone prepared for reasonably independent work to a glorified MS. Probably already moving in that direction, as many 'PhD's aren't really ready to work independently until they've finished two or more post-doctoral internships.

        • Four years? Ha! That's a good one!

          The easiest way to enforce that is for the awarding institution to say that if it isn't done in 4 years, it will be taken as a complete failure.

          No, that rule would result in a lot of thesis committees approving completely crap theses. Believe it or not, thesis committee members are human and have a lot of difficulty telling kids that their last four (or five, or eight) years of work are worth no recognition and please leave. Thesis advisors become emotionally attached to their students and want to see the succeed/graduate, even if those students are incompetent. Sometimes you can compensate for the incompetence with time. Only rarely will a thesis committee 'over-rule' the advisor, with their input generally taking the form of 'this would become acceptable if the student adds [foo] over the next year or so.' Mandated time to completion is a recipe for diminishing the quality of theses and migrating a PhD from someone prepared for reasonably independent work to a glorified MS. Probably already moving in that direction, as many 'PhD's aren't really ready to work independently until they've finished two or more post-doctoral internships.

          Except in systems where PhD contracts are fixed (e.g., most of Europe). When a PhD student starts with the certain knowledge that s/he will have to write a thesis in four years, they get super motivated to start pushing papers out around half-way through and advisers aren't so flippant about writing up results because they know they have a fixed amount of time to milk their students for results.

      • I think that you underestimate the value of soft modes of failure, particularly in maintaining quality standards. Examiners are human and it is much easier to say "not yet" than it is to say "and you're out of here".

  • by StripedCow (776465) on Sunday March 17, 2013 @08:14AM (#43196401)

    A big part of the problem is that there are few negative results in scientific literature. Ever found a paper with a clear negative outcome? I didn't. This "positive bias" in scientific publications is probably causing a major blow to the efficiency of scientific research.

    • by turkeyfish (950384) on Sunday March 17, 2013 @08:24AM (#43196441)

      There is a reason why you are wrong. There aren't enough forests to support publishing all possible negative results or enough time to read them. More aptly, there are plenty of "negative" results in the scientific literature. If you count the number of scientific papers that are in disagreement on a particular point, there are a great many of them. Science works best, when there is actually evidence gathered to accept or reject a particular scientific hypothesis. A purely negative result can be obtained without taking any data at all and hence, is of little value in advancing science.

      • Let me put it another way: assume you are starting a research project just now (perhaps you are starting your PhD), and some wizard would approach you and ask you if you'd like to receive, instantly, complete knowledge of all negative results in your field. Would your answer be "yes" or "no"?

        Science is not about "value" or "usefulness". Science just expands knowledge about the universe, regardless of whether it is good or bad knowledge, whatever that may mean.

        When an astronomer reports about a star that col

        • The correct answer to that wizard is no. Also, if someone tells you you can have all the knowledge in the world, this is a nasty trick they are playing on you.

          This is because knowledge is largely useless, only relevant knowledge is valuable. Also, the number of negative results in any field is probable infinite and uncountable. Although it is useful to know that this or that theory which had some data supporting it is wrong (a false positive, and a publication of a negative result), it is not useful to know

        • You seem to misunderstand what one can learn from a negative result.

          A negative result is in a sense like determining that a function is non-linear, Knowing that some phenomenon behaves as a linear function is a very tight constraint upon what one can subsequently infer about that phenomenon, since there is only one way to interpret linearity. On the other hand, simply knowing that a function in non-linear, doesn't place much of a constraint at all, since there are an infinite number of ways of begin non-l

          • So basically the moral of the story is... maybe people should use equivalence testing? Pardon me if this comment seems moronic- it's early and the tea hasn't quite kicked in yet.
            • Errr... or I guess maybe not tests for statistical equivalence specifically (upon second glance I don't even think that you were hinting in that particular direction), but that negative results should be qualified in some way?
    • by TheTurtlesMoves (1442727) on Sunday March 17, 2013 @08:59AM (#43196583)
      This is big problem in bioinformatics and biology in general. How many people have tried the same idea (ideas really aren't that original) only to find no literature on it and find it doesn't work. Then they don't publish. Its hard work publishing negative results. Its even harder to get it in a jornal anyone gives a crap about. Rinse and repeat....
      • by cryptolemur (1247988) on Sunday March 17, 2013 @10:09AM (#43196911)
        Check out Journal of Negative Results in Biomedicine: http://www.jnrbm.com/ [jnrbm.com] :-)

        Anyway, I was taught early on this is one of the main reasons to attend conferences -- after seeing an interesting presentation (or even poster) about stuff close to yours, you go for a beer or two with the presenter and hear all the failures they suffered and the wrong turns they took on the way. And share your own, too.

        The body of science is so much more than just the published papers, you know.
        • by ColdWetDog (752185) on Sunday March 17, 2013 @11:13AM (#43197241) Homepage

          Anyway, I was taught early on this is one of the main reasons to attend conferences -- after seeing an interesting presentation (or even poster) about stuff close to yours, you go for a beer or two with the presenter and hear all the failures they suffered and the wrong turns they took on the way. And share your own, too.

          And that's just one of the reasons I left academic science - people quit doing that. As funding dried up, people dried up. In fact, there were labs who had a reputation of getting it's post docs and grad students to 'hoover' the conference looking for ideas, strategies, concepts and bringing them back and working on some of the more likely leads. If that lab has eight post docs and 10 grad students, they can generally beat your solo effort if they so chose. So you didn't say much. Not much fun.

          That and the beer. Man, I hate beer.

      • This is why it's so important in biology to know people, or to have a PI who does. Friends tell friends their negative results, and that's how word gets around.
      • by ponos (122721)

        Actually, that's why clinical trials are now supposed to be registered (clinicaltrials.gov), so that when they end, we get to know what they found (or not). This way, pharma cannot avoid bad publicity, for example. It doesn't work perfectly because I'm not aware of someone actually verifying that studies did get published, but the mechanism is there and if agency "X" decides to have a look it should have a quick idea of who studied what. The situation is of course much less well-documented when it doesn't c

    • by DrProton (79239)

      Michelson Morley was a negative outcome, wasn't it? This is one of the classic modern physics experiments. In general, tests of Lorentz Invariance are experiments with a "negative outcome." Many have tried to find a violation of Lorentz' dictum, all have failed.

    • by ponos (122721)

      There are many negative results in clinical medicine. For example, all drugs that don't work in a phase III trial deserve their own publication. This is a costly failure for pharma, but less costly than failing post-marketing and being sued by everyone.

      Anyway, the term negative results is rather vague. A negative result coming from a well-designed and powered experiment can be very exciting (say, not finding the Higgs boson despite adequate design) because it makes us reconsider current theories. In my doma

    • by bjorniac (836863)

      A big part of the problem is that there are few negative results in scientific literature. Ever found a paper with a clear negative outcome? I didn't.

      Perhaps you should publish this finding.

    • A big part of the problem is that there are few negative results in scientific literature. Ever found a paper with a clear negative outcome? I didn't. This "positive bias" in scientific publications is probably causing a major blow to the efficiency of scientific research.

      I think the problem is that there aren't any reputable journals that publish negative results. If you could drive your h-index publishing all the stuff that didn't work, the paucity of negative results in the literature would vanish overnight. But it's a chicken-and-egg problem to make that happen.

  • Luck... (Score:4, Insightful)

    by mutube (981006) on Sunday March 17, 2013 @08:27AM (#43196445) Homepage

    ...and the ability to think on your feet.

    It is not possible to plan 4 years ahead to ensure success. What you get instead is a PhD project plan that's wrapped in a set of general concepts (AKA escape routes) in case you hit a dead end. I'm currently doing a life science PhD and have changed tack at the half way point. A number of my colleagues have also, often quite drastically, whether for reasons of practical feasibility or time constraints.

    If we know accurately what we were going to work on that far in advance, it has probably already been done.

    • Re:Luck... (Score:4, Informative)

      by SomeKDEUser (1243392) on Sunday March 17, 2013 @09:58AM (#43196857)

      Yeah, the trick is that you should always try to get funding for projects you have already completed, thus claiming a 100% success rate. Of course, this only happens in very large lab and has a bootstrap problem.

      On the other hand, the biological sciences are especially tough because experiments are hard, expensive and unreliable, and those doing them typically not so sophisticated with data analyses. Or else you are doing bioinformatics, which is either algorithmic research or also costly and generally inconclusive unless you do in vivo validation, in which case you are back to problem number one.

      But seriously, if you work with old-school biologists, do the world a favour, and teach them that a Gaussian error on a number of cells is dumb and wrong.

      • Re:Luck... (Score:5, Interesting)

        by ColdWetDog (752185) on Sunday March 17, 2013 @11:20AM (#43197273) Homepage

        But seriously, if you work with old-school biologists, do the world a favour, and teach them that a Gaussian error on a number of cells is dumb and wrong.

        I think that entry into either medicine or the biological sciences should require a passing grade on a graduate level statistics course. Only then do you stand a chance in hell to start moving away from a century of misconstrued numbers. In medicine, it's still painfully obvious that most researchers couldn't get past Stats 101. And that is even after they have the manuscript reviewed by a biostatistician (who is probably shivering in a basement closet hoping that the next group of researchers gives up looking for him and goes to a bar.)

        Of course, I'd still be fixing cars for a living, but that might have been a better outcome for myself and society....

        • 90% of MDs don't understand conditional probabilities. This is probably about the same as the general public (see the Monty Hall problem), but in that case it has very real consequences.

          But then I don't expect much from MDs anyway.

          But for researchers, not understanding what a model is (never mind a statistical one), this is a sin.

      • On the other hand, the biological sciences are especially tough because experiments are hard, expensive and unreliable, and those doing them typically not so sophisticated with data analyses.

        Try low temperature physics...

        When I was in grad school I used to ride bikes with a guy who was a biology PhD-- I can't remember if he was a post-doc or staff somewhere. One time we were out and he asked "How many experiments do you do a week?" I almost fell off my bike laughing. I ran my experiment 3 times in 6 years (all in the last 1.5 years), and each time it ran for no less than 4 weeks (I think the longest run was 12 or 13 weeks). But up to the first successful run (as in all the engineering worke

  • by Anonymous Coward

    Chris Lee may be a physicist when he dons that hat, but in TFA he speaks as a people/resource manager, not as a physicist. In the science of physics, the only thing that determines whether an idea has merit is the scientific method, and that's very well documented.

    Resource management is much more about cost and "return on investment" than about physics, even in the hard sciences, He wasn't speaking as a physicist in any way that's relevant to the science of his field.

    • by Anonymous Coward
      Physics research still has limited resources and needs management like decisions. That is part of any physicists job, so I would hope any other physicist would be able to speak about that to some degree. Yes, the scientific method is used for evaluating results. But you also need to evaluate which hypothesis you are going to actually test and iterate, because there are typically far more ideas than there are time and resources to work on.
  • by Anonymous Coward on Sunday March 17, 2013 @08:38AM (#43196487)

    Ancient Persians would debate ideas twice - once sober and once drunk. It had to sound feasible in both states to be a good idea.

    • by Chemisor (97276)

      "Man, we should totally invade Greece! That Alexander is a real sissy and needs a lesson."
      "Hear, hear! Now let's drink so we can evaluate this proposal more thoroughly!"

  • by Antique Geekmeister (740220) on Sunday March 17, 2013 @08:47AM (#43196525)

    I'm afraid the title of your note is misleading. Good science, much more than good engineering, involves testing new or old theories, to find how they work in previously untested ways, or to make sure that the previous test was really valid and caught all the important factors. A good graduate school project, involves a constrained project that can be reasonably tested in a few years, that does involve something of interest to the adviser, and that with good luck can be turned into a career of related questions.

    The key is to make the initial question relatively simple, so that the concept can be expanded into tests or other related fields as time and funding permits. This isn't asking the "right size" of question, it's asking a question with enough related, interesting implications but that still has relevance if only the simplest parts can be addressed. Let me take an example of something I'd love to find a good thesis for: the cost of using different sorting algorithms.

    The maximum computational costs of complex sorting algorithms is well understood (and well described at Wikipedia). But the additional computational cost of maintaining registers is not factored in, especially for small or modest data sets, and the cost of comparison _itself_ between different formats, or between positive and negative numbers, is not factored in to those computational costs. Neither is the cost of a partial sort that has to be started over from scratch or the benefit of algorithms that can be used when it is partially sorted. There is _wonderful_ material for a thesis in that kind of question, and even material for almost immediate application to industry. The preliminary survey and testing work with computational models can be done within a year by someone competent, but testing it against different CPU or software environments would be even more valuable and could easily fill out the rest of a graduate program, even leading to a creer in optimization of computational algorithms.

    • by femtobyte (710429)

      Wow, good thing you're not (...just guessing here...) in a position to hand out PhD thesis tasks. That type of grindwork sounds like a fine thing to foist off on a high-school summer intern. Not that doing thesis research doesn't involve a lot of tedious grinding on sub-tasks; however, you seem to be confusing "immediately useful for industry" with "good thesis project."

      You also (...just assuming here...) don't seem to have ever gotten deeper in the study/practice of programming than reading Wikipedia pages

  • and is always an option
  • See how Nikola Tesla did it, but do the same without the likes of Edison, big money, banksters, corrupt politicians, in other words, you're doomed!
  • by SirAstral (1349985) on Sunday March 17, 2013 @09:24AM (#43196691)

    Good ideas are hard to determine, and sometimes you find out something was actually a really bad idea only after several years like trans fats, or saccharin.

    The results of scientific discovery are diminished by classifying them as success/failure. The only 2 classifications should be "A Truth Discovered" or "Pseudo Science".

    Any lab experiment which is conducted to seek the truth even if it does not yield a commercially viable result is still a truth discovered. A so-called failed experiment still is a success at discovering a method which does not work to achieve desired results, and discovering what does not work in some cases can be more important then finding out what does and is an actual truth discovered.

    Any experiment performed to skew results in a particular direction, or where evidence is tossed that does not agree with your idea's is nothing but pure Pseudo Science. Unfortunately we have so much of this it has made people distrust scientists because they have proven that they are just as opportunistic as normal people and will do just about any dishonest thing for a buck! True Science be damned!

    • by m00sh (2538182)

      Any lab experiment which is conducted to seek the truth even if it does not yield a commercially viable result is still a truth discovered. A so-called failed experiment still is a success at discovering a method which does not work to achieve desired results, and discovering what does not work in some cases can be more important then finding out what does and is an actual truth discovered.

      The problem there are infinite number of truths to be discovered. There already have hundreds of dissertations and re

  • by 140Mandak262Jamuna (970587) on Sunday March 17, 2013 @09:47AM (#43196787) Journal
    If you know `a priori whether an idea is "good" or "bad" it will bring prejudice that will taint the results. One of the famous example is a naive Indian astrophysicist on his first trip outside India met Eddington on eve of his big presentation, in 1929. That guy explained in great detail his idea and Eddington not only dismissed it, he was scheduled to present just before this paper from that young man. He trashed the idea so much that the young man abandoned that field altogether and chose to pursue a different field [*]. Most others dismissed that paper too. It eventually garnered that young man a Nobel Prize in physics, and is the foundation of what is known as Chandrashekar Limit that tells you if a star is big enough to go supernova. That paper was discovered about 15 years later, after WW II. So in theory they should not know if an idea is good or bad.

    But that is theory. In practice, having some realistic goals based on available resources of money and time is common to all fields, not just science.

    [*] Chandrashekar was not bitter about Eddington, he credits being forced to change fields in his late 20s, taught him how to learn and he deliberately abandoned his field of study about every ten years, he continued to be productive into his late 70s. If you find the spoof paper written in his style The Imperturbability of Elevator Operators, by S Candlestickmaker, by one of his grad students, it makes hilarious reading for the geeks. ]

  • Four Years??! (Score:4, Informative)

    by period3 (94751) on Sunday March 17, 2013 @10:15AM (#43196925)

    Four years? Not in Canada - and presumably not in the US either. The department average in my program was more like 6 (I took about 6.5), and I've known people who have taken as long as 10 to complete their PhD.

    From some document I found on startpage: http://careerchem.com/CAREER-INFO-ACADEMIC/Frank-Elgar.pdf

    "Median time-to-completion of the PhD has nearly doubled during the last three 2 decades (from 6.5 to 11 years). "

    • A "four year thesis project" sounds just about right to me. My particular program in biology has an average completion time of 5.5 years, and the national average I believe is 6.5 years. But I don't even have a formal thesis project until I write a proposal for the end of my second year. I spent my first year taking classes and doing research rotations. I'm currently in my second year, I've picked a lab and started to do some productive research, but I still have classes and TA duties, and I spent a lot
  • Hindsight (Score:5, Insightful)

    by naroom (1560139) on Sunday March 17, 2013 @10:43AM (#43197067)
    The only way to know if an idea was good, is after you've already done it. Future prediction is always a crapshoot. People who claim to be good at it were typically just lucky, and are deluding themselves into thinking it was all skill.
  • "Scientists" isn't some coherent group that "knows" something. Some take guesses, some succeed, some fail. Many get it wrong too, and quite frequently.

  • by Sir Realist (1391555) on Sunday March 17, 2013 @12:12PM (#43197569)

    Scientists tell if an idea is a good one by trying to prove it wrong, over-and-over-again and in as logical a thought-out way as possible, til they give up. This is known as "science", and the fact that they do it this way is why we call them "scientists".

  • Once again we see that one can determine with decent success value of a scientific effort in the near future, not just centuries down the road. This is quite relevant to the funding of science. If the scientists themselves are trying to figure out what activities will be more fruitful, then that's a strong indication that society ought to be doing this as well.
  • A PhD is a several year apprenticeship in some area where you learn to do right-size research projects. The largest error of many new graduate students is to choose a project that has already been done, one that is too trivial to get publications out of, or one that is too large to finish in 3 years of work. There are fields outside of my PhD where i think I know pretty much the basic knowledge,e.g. computer science. But I would not be able to choose a "right size" R&D project without help.
  • If I had a dollar for every time some moron with a really stupid idea was able to get other people to part with their money for it, I'd be a rich man. George Carlin sums it up nicely when he said "You nail two pieces of wood together that have never been nailed together before and some schmuck will buy it from you." I would extend that further by saying "If you have charisma, you are able to convince people that the words coming out of your mouth are pure gold." In my experience, as with role-playing gam

"Time is money and money can't buy you love and I love your outfit" - T.H.U.N.D.E.R. #1

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