I work for a government lab that produces DNA sequences. We are obligated to release our data into a public database as soon as it has been verified for any samples that come from the US, and we release most of our foreign data, too, unless the other country involved gets pissy.
Nothing good comes of that speed. We get crackpots thinking they've made major discoveries (not one real one yet), we get scooped for major papers (think Science), sometimes by our own collaborators using only our data and none of theirs, and we generally spend a lot of time, effort and *more money* on media spin control. There is such a thing as releasing the raw data too fast.
We get a *ton* of FoI requests, too - people think we are withholding the good data, or being stubborn by not providing them composite statistics in exactly the format they want to see. The truth is, up until I got involved, the data management technology was so far behind the current bog-standard capabilities of the rest of the world, we couldn't actually answer the questions that were being asked, barring Herculean effort.
Don't get me wrong, I think we *should* be releasing all of this data - delayed by just a bit. That way the people who generate it would have a better shot to get recognition/credit for their work, the crackpots would have less ammo for their rants, the press would be more likely to get the facts right the first time, and the scientific integrity of the whole process would be upheld, as everyone would get the raw data to review. It'd probably save a ton of money.
The "reward" for doing publicly funded research is that you keep getting funded.
Collecting good data is hard work, and the payoff is big publications, which you need if you want to continue getting funded. Once you've got that big publication in your pocket, though, you'd better by coughing up that data set. Otherwise, everything you say is suspect. Kudos to the UK for getting this half-way right, but they'd better set some reasonable constraints on the timing of these required data releases, or face any number of frivolous lawsuits from conspiracy theorists and 'data analysis specialists' who don't want to do any of the hard work themselves...
I don't care one whit what you think you're entitled to: if you're taking my money, you work for me.
I don't care if you are a ditch digger or a particle physicist. Doing all the hard work and getting none of the credit sucks regardless of what we are discussing or who is paying the bills. So put up or shut up. Would you be willing to do all of the grunt work in your job, but take none of the recognition? Most people wouldn't - those are the kinds of jobs that make people go 'Postal'. If you aren't doing it (and even if you are), do you really expect anyone else to?
I've had my name included on several 'hard science' papers that had horrible statistical assumptions. I fought, and lost, because my professor had a big grant to maintain, and nobody else understood the underlying assumptions (we used an absolute scaling function, guaranteeing that our distribution was not normal, then tried to assume that it was normal). The second half of my thesis refutes the math in the last three papers I was on. Not one single person who read it understood it, which is sad because it wasn't actually all that impressive.
The only reason I'm not completely ashamed to admit that is that the bad stats don't actually change the conclusions in this case. They do invalidate the confidence intervals, though...
The training in stats required for 'hard science' is essentially nil. Most of the hard science folks I know who are not into high-end mathematical modeling just assume a normal distribution for their data, do a bit of analysis, and publish. I was in an analytical chemistry lab, where that sort of thing normally works, and to a very high precision. However, we were working with sloppy biological assays, where being within a factor of two is a miracle. Under those conditions, you need to know a lot more statistics.
Basically, the people who know enough math are working on well defined systems and theories, and the medical and biological communities don't know much math at all, but are working on very sloppy systems that need a lot of math to analyze correctly. It is therefore easier to spot the mistakes in those communities, but don't assume they aren't there in the 'hard science' papers.
My wife claims she notices three distinctly different kinds of orgasms - clit, g-spot, and a more nebulous 'vaginal' one. She never had an orgasm until I figured out where her supposedly non-existent g-spot is - that opened the flood gates to a whole bunch of really good sex.
Does the g-spot exist? Who cares. Something in the general vicinity of where my wife thinks her g-spot is can be stimulated to bring her to orgasm. Happy wife -> more sex -> happy me!
two parties is a natural evolution, its not decided by anyone...furthermore, the similarity of the two dominant parties is not a weakness of democracy, but a strength. two parties compete for the moderates of the country, this forces them to moderate their own message in order to win votes.
Get your facts straight. Two party systems are an outgrowth of a one-vote-per-voter system, the number of parties and voting system have nothing to do with the strength of democracy, and we don't even live in a democracy - it might be at best a 'representative democracy', but it is functionally more like a republic. None of that is my opinion, just poly-sci 101 and the math behind voting systems.
In a one-vote-per-voter system, a vote for a third party erodes support the the most closely aligned major party - thus all 3rd parties are necessarily fringe. Pick a different voting system, get a different result. Any of the more complicated voting systems have common results where 'compromise candidates' (i.e. middle ground) will win out. You don't just get the more moderate sounding candidate from the two extremes.
What does all of this have to do with music? Everything. The #1 selling song at Christmas is... just the most commonly purchased song. You vote with your wallet. You are not limited to one vote, or one song. If you cared, and had enough cash, you could make most any song the #1 selling song.
What happened here is that a minority of people like crappy pop, and they buy whatever the latest crappy pop is. The vast majority of the population buys music they actually like, but their 'votes' get diluted among all different genres of music. Most of the time, it doesn't matter, because good music and popularity are only slightly correlated, and may in fact be anti-correlated if you happen to dig the indie scene. Once per year, though, someone does a big press release about how crappy-pop-du-jour is outselling everything else. It may only account for a tiny fraction of total sales, but it is the #1 single. People got tired of it, and shouted it down, which they could do by picking a compromise - RATM.
Everyone who wanted *anything other* than crappy pop used one 'vote' on that song, and Bob's your uncle. That didn't change what else they went and bought - it just skewed the stats about #1 singles in an attempt to make certain advertisers STFU.
You can do that when buying music - the cost of one extra 'vote' is low enough that people who are pissed at Simon are happy to spend a bit to spike his wheel. You could do with voting for politicians, too - all you have to do is make it so that a compromise vote doesn't hurt your 'main party' candidate. Voila - 3rd parties start showing up with moderate views, the wackos still get left out of the final picture, and pretty soon, you get people voting on the merits of a candidate instead of their party affiliations and campaign promises you know they are going to break anyway. You'll still have a small number of dominate parties, but you'll have real 3rd, 4th and 5th options, and an overall decrease in cognitive dissonance among politicians.
And less crappy pop music. Or not, but one can hope.
I just balked at the "reverse engineer takes on biology" angle, as if that were something biologists had never thought of.
Interesting that you should say that - the traditional biologists, by and large, don't think of doing things like this. Bioinformatics is a catch-all for any number of different disciplines, all in relative infancy, and almost always pioneered by people outside the traditional biology arenas.
I studied biochemistry in college, with a ton of extra math, physics, and computer science. Then I did a PhD developing DNA diagnostics for flu (awarded by the chem department, but I was a full time programmer and part time bench chemist).
My first paper was applying Shannon informational entropy theory to big alignments of flu DNA to look for conserved regions. No one around me had a clue what the hell I was on about. The code I wrote for that paper is still used by the Flu Division at CDC.
The only place where this article went wrong was in assuming that traits are trivially mapped to sequences. In practice, it almost always turns out to be extremely non-trivial, and in flu it almost doesn't work at all (the biologist figured out the easy cases years ago). Never the less, most really good science starts with some assumption that looks to be extremely over-simplified, and turns out to be very predictive.
There is going to be a lot of room for hackers and coders in the biological sciences in coming years - computer science has solutions to problems the traditional biologists haven't even realized are problems yet. Data storage and retrieval to support high-throughput sequencing labs, new algorithms for large-scale data analysis, instrument networking for lab automation. The job postings will go up just as soon as the biologists figure out that they have a problem...
I've got a problem with lists like this - they do point you in the right direction, but they don't tell you *why* you want to go that way.
First, my credentials. Me, a PhD in chemistry, but I write scientific software for a living. Her, dual BS in Computer Science and Applied Math and a masters in Electrical and Computer Engineering, and a job in the aerospace industry. We lived together for nine years and we've been married for 3. We're about as geeky a couple as you are likely to find -- and that has almost nothing to do with our relationship. It does influence our favorite topics for conversations, but not much else.
Your relationship isn't going to be like any other. Not because you are geeks, but because it involves two unique individuals. There will be 'rules' that you learn to play by, but they won't be my rules, or the parents rules, or the rules that people who have been together for 50 years play by.
Think of a relationship like a box - an empty container to start. You can fill it by giving of yourself, or you can take from it what your partner has contributed. You'll do both at various times, but remember this - too much take and not enough give from either party will empty it back out, leaving one or both of you very unhappy and wondering where you went wrong.
How you fill it is up to you - find out what is important to your partner, and make an effort for her. If she cares about you, she'll do the same. Lists like the parent made are good places to start, but don't stop with other people's advice - figure out what really matters to your wife.
You won't get everything exactly right all the time, but if you've built a trusting, loving relationship, and kept the box full, you'll get past the rocky patches without major injury to either party. For example, early in my relationship, my wife was sometimes too subtle about what she really wanted. I wouldn't catch the hints, and she'd end up very upset and I'd end up clueless and hurt. After it happened a couple of times, I finally just asked her to do a very simple thing for me. If it was a really important topic, I asked her to say 'This is really important'. She doesn't play that card very often, but when she does, I swallow my arguments and do my best to accommodate her request. I wasn't meeting her needs because I didn't know what they were. We are both much happier since we started doing that, and those requests are becoming more infrequent, because we are learning to recognize each others needs better.
That's what works for us, but find your own way. If you are both willing to work at getting it right, your marriage can be the best thing that ever happened to either of you.
That most highly educated men and women of science and reason are liberals. If you're a liberal like me...
Wow, biased much?
The Slashdot community prides itself on things like understanding statistics - so let's try to understand this one a little more objectively.
This article is media hype piece, about a study by an opinion polling group, asking questions about topics that are scientific in nature but tend to have political spin put on them every day.
I submit to you that by itself, the 55% statistic means *nothing*. Here's why.
If this were a scientific study instead of a public opinion survey, Slashdot would be ripping that number apart because the comparison is extremely non-scientific. For instance, compare scientists vs non-scientists by level of education. I strongly suspect that you'd find that the distribution of political orientation for those with an advanced degree was very similar between the science and non-science groups. Whereas you won't find any 'scientists' with only a high school education - you can't go into the sciences without at least a bachelors degree, and that will usually land you a lab tech position.
From there, you need to start comparing how each of the various demographics feels about politically charged scientific issues. But those statistics, too, are useless without understanding the political situation and correcting for education levels, etc.
This is a 'social sciences' sort of study, and its findings deserve to be scrutinized just as much as any other, because it suffers all the same sort of flaws as the vast majority of those sorts of studies. Do not be blinded by the fact that it deals with physical science topics.
This study, and the parent comment, show that you don't even have to lie with statistics. Just publish some crappy numbers with no real statistical rigor applied to them. If the numbers are sensational, or even leading, other people will do the job for you.
1. The majority of scientists are liberals. 2. I am a liberal. 3. By (1) and (2), I am like a scientist. 4. Scientists are always right. 5. By (3) and (4), I am right about every opinion I have. 6. We disagree. 7. By (5) and (6), you are wrong.
Speed doesn't kill anybody.... It's that coming to a sudden stop that gets you every time!
You're thinking too small! Try clipping along at 1/3 of the speed of light or so. All good *in space*, but I dare you to try that in the Earth's atmosphere!
If you think too much of *anything* won't kill, you, try adding a whole lot more.
I live in Denver and always preferred the Rocky Mountain News to the Denver Post, the local paper that has so far survived. I'm a news junkie and get all my content almost exclusively online. I never heard of InDenverTimes.com until this morning.
I live in Denver, and have always preferred the Post. I get all my news online. Interestingly, I have heard of InDenverTimes multiple times - all from the Denver Post website.
Here's the thing - they wouldn't have needed any more publicity than that, if they would have had an angle. But their whole story is 'we're going to put news on the web' which has been done before. They had some of the old Rocky staff, but the Post hired a couple of the bigger name columnists, so they didn't have an exclusive on that.
If that's all you've got going for you, why would I pay five dollars? The problem is not the lack of publicity, it is the lack of *buzz*. No one had any reason to check that site out.
I see "outdated business model" time and time again on Slashdot as an euphemism for basically saying "not offering something for free".
I do not speak for the Slashdot gestalt. When I write 'outdated business model', I mean 'founded on pre-internet artificial scarcity'. That doesn't mean free, it just means *both* the supply and demand curves shift quite a bit, and the places in the system where there are profitable opportunities shift. This applies to the MPAA, the RIAA, the scientific publishing industry, and a whole bunch more.
Scientific publishing, in particular, makes money from both the author and the reader. They got greedy, claiming that they are the only way to distribute to the end reader, and that they are also the only way to set up a peer review. Both assumptions are wrong, and are now easy to get around, thanks to the internet.
First of all, business models do not become outdated. They may become worthless because someone has started doing business another way that eliminates one from making money from their current way of doing business.
If a business model was profitable, but now it is not due to advances in technology, it is outdated. Its time has passed. It is an ex-business model. It is pining for the fjords. It has gone to the great golden spike in the sky where all technologically inflexible business models must eventually go.
Now consider this, many folks are becoming independent contractors and doing crafts and whatnot at home to make a living - just like the pre-19th century factory system. Outdated indeed.
You picked a perfect example to illustrate my point. Pre-19th century, if you wanted a sweater, someone had to knit it. 21st century, if you want a handmade sweater, someone has to knit it. But the supply of handmade sweaters, which take a long time to knit, is far outstripped by the demand for sweaters.
There are those of us who, recognizing the lost opportunity cost of spending hundreds of dollars for a handmade sweater, realize that we can get a machine-made sweater for a fraction of the cost. We substitute a similar product.
The price of handmade sweaters is a supply side problem. The price of machine-made sweaters is a demand-side problem. The business models for these things are radically different due to the introduction of technology into the process. Handmade clothes are an art form, and are priced appropriately. Machine made clothes are a commodity and enjoy shatteringly larger profitability due to economies of scale.
Building a business model centered around high demand for high priced sweaters is just silly. It *would* have been a viable business model prior to the industrial revolution and the amazing rise of the textile industry, but it won't work now. It is outdated. That doesn't mean it isn't a business plan - it's just a silly one that won't work any more.
Scientific publishing will change. The publishers will find a way to adapt their business model and continue to publish, or will flail about with an outdated business model and they will perish. As in science, so it goes in scientific publishing: Publish or Perish.
This is a major blow to an industry with an outdated business model. Scientific publication is starting to move beyond the need for the middleman, and I am extremely glad to see it happen.
That said, the major publishers will scramble to try and patch this hole in the business model, and they will probably make the overall situation worse before it really starts to improve.
Oh well. Got to start that process at some point. Go MIT.
No amount of proof will satisfy Creationists, Fundamentalists, and others. They can fall back on "well that's the way god made it."
We never know what sort of experiment future science will be able to do.
Falcon's got it right. Even if we manage to come to a complete, encompassing scientific view of the universe, you could still argue that there is a God, and because he is all-powerful, he made a scientifically consistent universe.
This is the point where logical reasoning breaks down. You can always add God back into the equation. You cannot prove or disprove God with logic or science.
Ockham's Razor suggests that "the explanation of any phenomenon should make as few assumptions as possible, eliminating those that make no difference in the observable predictions of the explanatory hypothesis or theory." In this case, God is unnecessary to explain the world we see around us. However, that's just an observation - not really a hard and fast rule of science. That's all the further we can go to prove or disprove the existence of an all-powerful being.
You either believe or you don't. Anyone who tells you they can prove or disprove God has failed to study enough philosophy, or is lying to you. No exceptions.
No. We can't even *try*. And for precisely this reason, creationism is not science.
Strip away everything else and science comes down to these steps.
1. Posit a falsifiable hypothesis. 2. Design an experiment to test it. 3. If you fail to disprove it, it might be true.
Any argument that can be boiled down to '$DIVINITY did it!' fails at step one. By definition, God, miracles, etc. fall outside the bounds of science. You can't disprove them. You can *try* to reason about them logically. Everyone who has ever tried has ended up caught in a circular argument. This includes all statements made for *or against* the existence of a higher power.
This is why talking about science and religion in the same breath is utter nonsense. The two have no overlap, unless there is a God, and he is deceiving us at every turn just to be an asshole (the true believers will tell you he is testing your faith).
This 'grand deceiver' is the fallout of following Descartes' "Je pense donc je suis" to its logical conclusion, and the foundation for all of western philosophy until Sartre hit reset by deliberately ignoring everything that came before him. (See sig for more).
Religion comes down to one question. Do you believe? No logic, no science, no reasoning it out. So, do you believe?
Pascal's Wager helps to explain part of the enduring popularity of believing in God, despite a lack of empirical evidence. If you believe, and there is no God, nothing happens to you - this is the existential viewpoint. If you disbelieve, and there is a God, you are screwed - this is the religious viewpoint.
Me? I think Marcus Aurelius had it right. Worry about this life. The next will take care of itself, one way or another.
"Live a good life. If there are gods and they are just, then they will not care how devout you have been, but will welcome you based on the virtues you have lived by. If there are gods, but unjust, then you should not want to worship them. If there are no gods, then you will be gone, but will have lived a noble life that will live on in the memories of your loved ones."
My wife just took a new position, because her last boss was an idiot. He was a passive aggressive micro-manager, puffed up with his own self-importance, *at least* 15 years out of date technically, and long since regulated to the most irrelevant corner of the company.
By the metrics discussed here, though, he'd have looked like the hero! *All* had to run though him - customers, suppliers, management, co-workers - if you talked to someone without including him in the conversation, he'd flip. He threatened to fire my wife (and a few more people since) for doing their job without his constant oversight. Unfortunately, while everyone knows about the situation, my wife was the first to report it to HR, so they can only now start to think about taking action against they guy.
Counting the number of communications makes the people who send one word, no value added emails and attend a lot of meetings they don't need to be at look good.
Also, it completely misses your crack team - the 3-4 people who you can hand a problem to, and know that they'll have it solved by next Tuesday, no questions asked. When those people shut their office door, you leave them alone, because you know they are working miracles, and you'll only get int their way.
Web analogy - Google and page rank. Rule number one is that you never trust the page to tell you how important it really is. Pages with all the right keywords and a bunch of links are one of two things - the best of the best about a topic, or an SEO linkfarm. So you take those things into account, but you do so with a *huge* grain of salt. To augment it, you go looking for other supporting metrics - what do other people think?
The HR department has just automated a human approach to the problem - they took one piece of evidence that the human brain can wrap its head around, and made the computer count that. You want to do informatics and data mining right, you need to learn what the computer is good at, and start looking for deeper patterns that are hidden by masses of data too large for the human mind to encompass.
Umm... considering how safe, secure and (since recently) stable banks are, I dunno if/. is the worse choice for your money.
Come on Slashdot - I was gunning for a 'Funny' with the hot grits, but Opportunist needs an 'Insightful' here. This is deep commentary on what is wrong with world economy (and what is wrong with Slashdot).
I can't do online banking with Wachovia, and SLASHDOT corrcetly (sic)
Banking with Slashdot? Forget which browser you use - there's your problem!
If Slashdot were a bank, we'd have all sorts of problems with easily detectable duplication of small bills, and none other than Cowboy Neal for security. Also, instead of those little suckers you get at most banks, you'd probably end up being offered hot grits...
My money will be staying under the mattress, thanks!
But if you like multi-language programming then Python is good glue.
If you eat your own dog-food... You are your own end-user, although occasionally other people may pretend.
If your target user is a non-programmer, who simply wants to be able to perform a task then you will need to wrap up the functionality in a non-programmatic way. GUIs are the best way (so far) of doing this. Because there is no intention of exposing an external call interface the overhead of mapping from language to language becomes pure overhead and there is a natural tendency towards a single monolithic language approach.
Almost 100% of *my* code is python these days, but I use it glue together any number of my old scientific applications that are often written in C. You can turn an archaic, unusable program into a slick, modern GUI or web service with very little code.
Most important here, though, are your points about who your target audience is. I think the submission author is missing that point, and it deserves to be made in no uncertain terms.
I am a scientist and a programmer. When I am writing for myself, I want to spend time on my data, not my program. So, I bang something out unix style - command line only, text I/O, move on with life. Usually, that happens in Python, but it might be in C, R, MatLab - whatever. Programs from my PhD are almost strictly command line. My co-workers from that part of my life had to learn command line if they wanted to work with my stuff. And you know what? They all did. Some of them got quite good at it, and I had more than a few inquiries about learning to program - they all saw the utility of what I was doing.
After finishing my PhD, I've worked a little for a start up and a government agency, both based on my PhD research. In both cases, I've played the role of the scientifically literate programmer. My users are somewhat tech savvy, but with few exceptions, they don't want command line tools.
A few of my old tools are still in use, though, just because they do one thing so very well, and a handful of people took the time to learn them. In return, I save them hours every day, which make those few tech savvy souls very happy.
The trend - what is likely to keep me employed for years to come - is building GUI/web programs for people who are good scientists, but don't understand.
I take a hybrid approach. What my end user sees is a standard Windows GUI. They happily click buttons to find some raw data, and then their analyzed data pops up automatically in Excel.
Behind the scenes though, my code is an amalgam of programs, most of which can still be run command line, just like they always could. The GUI code is wxPython, and it quite happily runs on Windows and Linux. I think it would run on a Mac, too, but I haven't had occasion to try it yet. It looks native in all of those environments, it never does anything to scare the users, and yet I can still do most of my analysis command line when I need to.
I'm currently developing a DNA sequence database. User interaction will all be web-based, data analysis will largely be a mixture of Python, MatLab, and C programs behind the scenes. My users won't have to care how their data gets analyzed - it'll just magically show up in the form they need it. They focus on further analysis and interpretation. Given who my users will be, this is a Very Good Thing(tm).
The point, though, is that my programming spans everything the submission discusses. These approaches aren't orthogonal. Pick the right one for the code you are working on.
If you are coding for yourself or for very tech savvy scientists, stay command line. It's easier to code and debug, and you'll get more done.
If you are selling to Joe Sixpack, a GUI with a Staples-style 'Easy Button' is probably the right choice. Add advanced options as stand-alone
This approach goes after an area on the virus that is hard to reach because of its structure.
Err, not really. Your body *could* produce antibodies to that region, but that region doesn't normally get your immune system very excited.
Flu has five primary antigenic sites that do provoke your immune system. Not surprisingly, these are hyper variable regions, hence the need to reformulate the vaccine every couple of years.
There are a standard set of tricks that you can use to force an immune response to particular part of a protein. For example, get rid of the stuff that normally provokes the immune response. TFA doesn't say that - you'd need to read the methods section of the paper, or just know something about monoclonal antibodies.
Once you've got a cell producing an antibody you like, you 'immortalize' it - basically turn it into a cancer cell. It now continues to produce a monoclonal antibody, as opposed to the broad mix of antibodies your immune system normally produces, called polyclonal antibodies.
These techniques are not specific to flu, and not very revolutionary. Also, this is a hugely expensive way to treat the flu. Monoclonal antibodies only make fiscal sense in research settings, not as a widely available treatment for humans.
Additionally, the people working on this (some of whom are my co-workers) should know better than to mention the idea of a universal treatment. Any number of antiviral drugs have been designed to target regions that don't normally vary all that much. Almost all of them are now ineffective due to the virus mutating in response to selective pressure from the drugs.
Don't get me wrong - this is cool science. But it is not a cure for the flu. Plan to keep getting your flu shot for many years to come.
Slashdot Mirror
I work for a government lab that produces DNA sequences. We are obligated to release our data into a public database as soon as it has been verified for any samples that come from the US, and we release most of our foreign data, too, unless the other country involved gets pissy.
Nothing good comes of that speed. We get crackpots thinking they've made major discoveries (not one real one yet), we get scooped for major papers (think Science), sometimes by our own collaborators using only our data and none of theirs, and we generally spend a lot of time, effort and *more money* on media spin control. There is such a thing as releasing the raw data too fast.
We get a *ton* of FoI requests, too - people think we are withholding the good data, or being stubborn by not providing them composite statistics in exactly the format they want to see. The truth is, up until I got involved, the data management technology was so far behind the current bog-standard capabilities of the rest of the world, we couldn't actually answer the questions that were being asked, barring Herculean effort.
Don't get me wrong, I think we *should* be releasing all of this data - delayed by just a bit. That way the people who generate it would have a better shot to get recognition/credit for their work, the crackpots would have less ammo for their rants, the press would be more likely to get the facts right the first time, and the scientific integrity of the whole process would be upheld, as everyone would get the raw data to review. It'd probably save a ton of money.
The "reward" for doing publicly funded research is that you keep getting funded.
Collecting good data is hard work, and the payoff is big publications, which you need if you want to continue getting funded. Once you've got that big publication in your pocket, though, you'd better by coughing up that data set. Otherwise, everything you say is suspect. Kudos to the UK for getting this half-way right, but they'd better set some reasonable constraints on the timing of these required data releases, or face any number of frivolous lawsuits from conspiracy theorists and 'data analysis specialists' who don't want to do any of the hard work themselves...
I don't care one whit what you think you're entitled to: if you're taking my money, you work for me.
I don't care if you are a ditch digger or a particle physicist. Doing all the hard work and getting none of the credit sucks regardless of what we are discussing or who is paying the bills. So put up or shut up. Would you be willing to do all of the grunt work in your job, but take none of the recognition? Most people wouldn't - those are the kinds of jobs that make people go 'Postal'. If you aren't doing it (and even if you are), do you really expect anyone else to?
That quote sounds almost like it is right out of this article...
http://www.theonion.com/articles/new-solar-system-discovered-four-feet-from-earth,1094/
I've had my name included on several 'hard science' papers that had horrible statistical assumptions. I fought, and lost, because my professor had a big grant to maintain, and nobody else understood the underlying assumptions (we used an absolute scaling function, guaranteeing that our distribution was not normal, then tried to assume that it was normal). The second half of my thesis refutes the math in the last three papers I was on. Not one single person who read it understood it, which is sad because it wasn't actually all that impressive.
The only reason I'm not completely ashamed to admit that is that the bad stats don't actually change the conclusions in this case. They do invalidate the confidence intervals, though...
The training in stats required for 'hard science' is essentially nil. Most of the hard science folks I know who are not into high-end mathematical modeling just assume a normal distribution for their data, do a bit of analysis, and publish. I was in an analytical chemistry lab, where that sort of thing normally works, and to a very high precision. However, we were working with sloppy biological assays, where being within a factor of two is a miracle. Under those conditions, you need to know a lot more statistics.
Basically, the people who know enough math are working on well defined systems and theories, and the medical and biological communities don't know much math at all, but are working on very sloppy systems that need a lot of math to analyze correctly. It is therefore easier to spot the mistakes in those communities, but don't assume they aren't there in the 'hard science' papers.
Apparently I really can't spell.
Photonetics.
Grr.
A perfectly good pun, ruined by a voiceless consonant in an uncommon english digraph.
I'm sure you wouldn't have noticed that extra letter if you were moving at 2/3 of the speed of light.
Hooked on phontonetics worked for me.
Is this chaotic release schedule supposed to be more attractive?
My wife claims she notices three distinctly different kinds of orgasms - clit, g-spot, and a more nebulous 'vaginal' one. She never had an orgasm until I figured out where her supposedly non-existent g-spot is - that opened the flood gates to a whole bunch of really good sex.
Does the g-spot exist? Who cares. Something in the general vicinity of where my wife thinks her g-spot is can be stimulated to bring her to orgasm. Happy wife -> more sex -> happy me!
two parties is a natural evolution, its not decided by anyone...furthermore, the similarity of the two dominant parties is not a weakness of democracy, but a strength. two parties compete for the moderates of the country, this forces them to moderate their own message in order to win votes.
Get your facts straight. Two party systems are an outgrowth of a one-vote-per-voter system, the number of parties and voting system have nothing to do with the strength of democracy, and we don't even live in a democracy - it might be at best a 'representative democracy', but it is functionally more like a republic. None of that is my opinion, just poly-sci 101 and the math behind voting systems.
In a one-vote-per-voter system, a vote for a third party erodes support the the most closely aligned major party - thus all 3rd parties are necessarily fringe. Pick a different voting system, get a different result. Any of the more complicated voting systems have common results where 'compromise candidates' (i.e. middle ground) will win out. You don't just get the more moderate sounding candidate from the two extremes.
What does all of this have to do with music? Everything. The #1 selling song at Christmas is... just the most commonly purchased song. You vote with your wallet. You are not limited to one vote, or one song. If you cared, and had enough cash, you could make most any song the #1 selling song.
What happened here is that a minority of people like crappy pop, and they buy whatever the latest crappy pop is. The vast majority of the population buys music they actually like, but their 'votes' get diluted among all different genres of music. Most of the time, it doesn't matter, because good music and popularity are only slightly correlated, and may in fact be anti-correlated if you happen to dig the indie scene. Once per year, though, someone does a big press release about how crappy-pop-du-jour is outselling everything else. It may only account for a tiny fraction of total sales, but it is the #1 single. People got tired of it, and shouted it down, which they could do by picking a compromise - RATM.
Everyone who wanted *anything other* than crappy pop used one 'vote' on that song, and Bob's your uncle. That didn't change what else they went and bought - it just skewed the stats about #1 singles in an attempt to make certain advertisers STFU.
You can do that when buying music - the cost of one extra 'vote' is low enough that people who are pissed at Simon are happy to spend a bit to spike his wheel. You could do with voting for politicians, too - all you have to do is make it so that a compromise vote doesn't hurt your 'main party' candidate. Voila - 3rd parties start showing up with moderate views, the wackos still get left out of the final picture, and pretty soon, you get people voting on the merits of a candidate instead of their party affiliations and campaign promises you know they are going to break anyway. You'll still have a small number of dominate parties, but you'll have real 3rd, 4th and 5th options, and an overall decrease in cognitive dissonance among politicians.
And less crappy pop music. Or not, but one can hope.
I just balked at the "reverse engineer takes on biology" angle, as if that were something biologists had never thought of.
Interesting that you should say that - the traditional biologists, by and large, don't think of doing things like this. Bioinformatics is a catch-all for any number of different disciplines, all in relative infancy, and almost always pioneered by people outside the traditional biology arenas.
I studied biochemistry in college, with a ton of extra math, physics, and computer science. Then I did a PhD developing DNA diagnostics for flu (awarded by the chem department, but I was a full time programmer and part time bench chemist).
My first paper was applying Shannon informational entropy theory to big alignments of flu DNA to look for conserved regions. No one around me had a clue what the hell I was on about. The code I wrote for that paper is still used by the Flu Division at CDC.
The only place where this article went wrong was in assuming that traits are trivially mapped to sequences. In practice, it almost always turns out to be extremely non-trivial, and in flu it almost doesn't work at all (the biologist figured out the easy cases years ago). Never the less, most really good science starts with some assumption that looks to be extremely over-simplified, and turns out to be very predictive.
There is going to be a lot of room for hackers and coders in the biological sciences in coming years - computer science has solutions to problems the traditional biologists haven't even realized are problems yet. Data storage and retrieval to support high-throughput sequencing labs, new algorithms for large-scale data analysis, instrument networking for lab automation. The job postings will go up just as soon as the biologists figure out that they have a problem...
Aww, *hell* no!
I've got a problem with lists like this - they do point you in the right direction, but they don't tell you *why* you want to go that way.
First, my credentials. Me, a PhD in chemistry, but I write scientific software for a living. Her, dual BS in Computer Science and Applied Math and a masters in Electrical and Computer Engineering, and a job in the aerospace industry. We lived together for nine years and we've been married for 3. We're about as geeky a couple as you are likely to find -- and that has almost nothing to do with our relationship. It does influence our favorite topics for conversations, but not much else.
Your relationship isn't going to be like any other. Not because you are geeks, but because it involves two unique individuals. There will be 'rules' that you learn to play by, but they won't be my rules, or the parents rules, or the rules that people who have been together for 50 years play by.
Think of a relationship like a box - an empty container to start. You can fill it by giving of yourself, or you can take from it what your partner has contributed. You'll do both at various times, but remember this - too much take and not enough give from either party will empty it back out, leaving one or both of you very unhappy and wondering where you went wrong.
How you fill it is up to you - find out what is important to your partner, and make an effort for her. If she cares about you, she'll do the same. Lists like the parent made are good places to start, but don't stop with other people's advice - figure out what really matters to your wife.
You won't get everything exactly right all the time, but if you've built a trusting, loving relationship, and kept the box full, you'll get past the rocky patches without major injury to either party. For example, early in my relationship, my wife was sometimes too subtle about what she really wanted. I wouldn't catch the hints, and she'd end up very upset and I'd end up clueless and hurt. After it happened a couple of times, I finally just asked her to do a very simple thing for me. If it was a really important topic, I asked her to say 'This is really important'. She doesn't play that card very often, but when she does, I swallow my arguments and do my best to accommodate her request. I wasn't meeting her needs because I didn't know what they were. We are both much happier since we started doing that, and those requests are becoming more infrequent, because we are learning to recognize each others needs better.
That's what works for us, but find your own way. If you are both willing to work at getting it right, your marriage can be the best thing that ever happened to either of you.
That most highly educated men and women of science and reason are liberals. If you're a liberal like me...
Wow, biased much?
The Slashdot community prides itself on things like understanding statistics - so let's try to understand this one a little more objectively.
This article is media hype piece, about a study by an opinion polling group, asking questions about topics that are scientific in nature but tend to have political spin put on them every day.
I submit to you that by itself, the 55% statistic means *nothing*. Here's why.
If this were a scientific study instead of a public opinion survey, Slashdot would be ripping that number apart because the comparison is extremely non-scientific. For instance, compare scientists vs non-scientists by level of education. I strongly suspect that you'd find that the distribution of political orientation for those with an advanced degree was very similar between the science and non-science groups. Whereas you won't find any 'scientists' with only a high school education - you can't go into the sciences without at least a bachelors degree, and that will usually land you a lab tech position.
From there, you need to start comparing how each of the various demographics feels about politically charged scientific issues. But those statistics, too, are useless without understanding the political situation and correcting for education levels, etc.
This is a 'social sciences' sort of study, and its findings deserve to be scrutinized just as much as any other, because it suffers all the same sort of flaws as the vast majority of those sorts of studies. Do not be blinded by the fact that it deals with physical science topics.
This study, and the parent comment, show that you don't even have to lie with statistics. Just publish some crappy numbers with no real statistical rigor applied to them. If the numbers are sensational, or even leading, other people will do the job for you.
1. The majority of scientists are liberals.
2. I am a liberal.
3. By (1) and (2), I am like a scientist.
4. Scientists are always right.
5. By (3) and (4), I am right about every opinion I have.
6. We disagree.
7. By (5) and (6), you are wrong.
QED? Not so much.
Speed doesn't kill anybody.... It's that coming to a sudden stop that gets you every time!
You're thinking too small! Try clipping along at 1/3 of the speed of light or so. All good *in space*, but I dare you to try that in the Earth's atmosphere!
If you think too much of *anything* won't kill, you, try adding a whole lot more.
I live in Denver and always preferred the Rocky Mountain News to the Denver Post, the local paper that has so far survived. I'm a news junkie and get all my content almost exclusively online. I never heard of InDenverTimes.com until this morning.
I live in Denver, and have always preferred the Post. I get all my news online. Interestingly, I have heard of InDenverTimes multiple times - all from the Denver Post website.
Here's the thing - they wouldn't have needed any more publicity than that, if they would have had an angle. But their whole story is 'we're going to put news on the web' which has been done before. They had some of the old Rocky staff, but the Post hired a couple of the bigger name columnists, so they didn't have an exclusive on that.
If that's all you've got going for you, why would I pay five dollars? The problem is not the lack of publicity, it is the lack of *buzz*. No one had any reason to check that site out.
n/t
I see "outdated business model" time and time again on Slashdot as an euphemism for basically saying "not offering something for free".
I do not speak for the Slashdot gestalt. When I write 'outdated business model', I mean 'founded on pre-internet artificial scarcity'. That doesn't mean free, it just means *both* the supply and demand curves shift quite a bit, and the places in the system where there are profitable opportunities shift. This applies to the MPAA, the RIAA, the scientific publishing industry, and a whole bunch more.
Scientific publishing, in particular, makes money from both the author and the reader. They got greedy, claiming that they are the only way to distribute to the end reader, and that they are also the only way to set up a peer review. Both assumptions are wrong, and are now easy to get around, thanks to the internet.
First of all, business models do not become outdated. They may become worthless because someone has started doing business another way that eliminates one from making money from their current way of doing business.
If a business model was profitable, but now it is not due to advances in technology, it is outdated. Its time has passed. It is an ex-business model. It is pining for the fjords. It has gone to the great golden spike in the sky where all technologically inflexible business models must eventually go.
Now consider this, many folks are becoming independent contractors and doing crafts and whatnot at home to make a living - just like the pre-19th century factory system. Outdated indeed.
You picked a perfect example to illustrate my point. Pre-19th century, if you wanted a sweater, someone had to knit it. 21st century, if you want a handmade sweater, someone has to knit it. But the supply of handmade sweaters, which take a long time to knit, is far outstripped by the demand for sweaters.
There are those of us who, recognizing the lost opportunity cost of spending hundreds of dollars for a handmade sweater, realize that we can get a machine-made sweater for a fraction of the cost. We substitute a similar product.
The price of handmade sweaters is a supply side problem. The price of machine-made sweaters is a demand-side problem. The business models for these things are radically different due to the introduction of technology into the process. Handmade clothes are an art form, and are priced appropriately. Machine made clothes are a commodity and enjoy shatteringly larger profitability due to economies of scale.
Building a business model centered around high demand for high priced sweaters is just silly. It *would* have been a viable business model prior to the industrial revolution and the amazing rise of the textile industry, but it won't work now. It is outdated. That doesn't mean it isn't a business plan - it's just a silly one that won't work any more.
Scientific publishing will change. The publishers will find a way to adapt their business model and continue to publish, or will flail about with an outdated business model and they will perish. As in science, so it goes in scientific publishing: Publish or Perish.
This is a major blow to an industry with an outdated business model. Scientific publication is starting to move beyond the need for the middleman, and I am extremely glad to see it happen.
That said, the major publishers will scramble to try and patch this hole in the business model, and they will probably make the overall situation worse before it really starts to improve.
Oh well. Got to start that process at some point. Go MIT.
No amount of proof will satisfy Creationists, Fundamentalists, and others. They can fall back on "well that's the way god made it."
We never know what sort of experiment future science will be able to do.
Falcon's got it right. Even if we manage to come to a complete, encompassing scientific view of the universe, you could still argue that there is a God, and because he is all-powerful, he made a scientifically consistent universe.
This is the point where logical reasoning breaks down. You can always add God back into the equation. You cannot prove or disprove God with logic or science.
Ockham's Razor suggests that "the explanation of any phenomenon should make as few assumptions as possible, eliminating those that make no difference in the observable predictions of the explanatory hypothesis or theory." In this case, God is unnecessary to explain the world we see around us. However, that's just an observation - not really a hard and fast rule of science. That's all the further we can go to prove or disprove the existence of an all-powerful being.
You either believe or you don't. Anyone who tells you they can prove or disprove God has failed to study enough philosophy, or is lying to you. No exceptions.
Can we disprove creationism?
No. We can't even *try*. And for precisely this reason, creationism is not science.
Strip away everything else and science comes down to these steps.
1. Posit a falsifiable hypothesis.
2. Design an experiment to test it.
3. If you fail to disprove it, it might be true.
Any argument that can be boiled down to '$DIVINITY did it!' fails at step one. By definition, God, miracles, etc. fall outside the bounds of science. You can't disprove them. You can *try* to reason about them logically. Everyone who has ever tried has ended up caught in a circular argument. This includes all statements made for *or against* the existence of a higher power.
This is why talking about science and religion in the same breath is utter nonsense. The two have no overlap, unless there is a God, and he is deceiving us at every turn just to be an asshole (the true believers will tell you he is testing your faith).
This 'grand deceiver' is the fallout of following Descartes' "Je pense donc je suis" to its logical conclusion, and the foundation for all of western philosophy until Sartre hit reset by deliberately ignoring everything that came before him. (See sig for more).
Religion comes down to one question. Do you believe? No logic, no science, no reasoning it out. So, do you believe?
Pascal's Wager helps to explain part of the enduring popularity of believing in God, despite a lack of empirical evidence. If you believe, and there is no God, nothing happens to you - this is the existential viewpoint. If you disbelieve, and there is a God, you are screwed - this is the religious viewpoint.
Me? I think Marcus Aurelius had it right. Worry about this life. The next will take care of itself, one way or another.
"Live a good life. If there are gods and they are just, then they will not care how devout you have been, but will welcome you based on the virtues you have lived by. If there are gods, but unjust, then you should not want to worship them. If there are no gods, then you will be gone, but will have lived a noble life that will live on in the memories of your loved ones."
I strongly suspect that this system is designed to identify people like your wife's ex-boss as valuable employees
You could be right about that. And any company who pulls that sort of crap deserves exactly what is coming to them.
Also,
"networking" and "synergies" and "six-sigma leveraging of core stakeholder values"
Bingo!
My wife just took a new position, because her last boss was an idiot. He was a passive aggressive micro-manager, puffed up with his own self-importance, *at least* 15 years out of date technically, and long since regulated to the most irrelevant corner of the company.
By the metrics discussed here, though, he'd have looked like the hero! *All* had to run though him - customers, suppliers, management, co-workers - if you talked to someone without including him in the conversation, he'd flip. He threatened to fire my wife (and a few more people since) for doing their job without his constant oversight. Unfortunately, while everyone knows about the situation, my wife was the first to report it to HR, so they can only now start to think about taking action against they guy.
Counting the number of communications makes the people who send one word, no value added emails and attend a lot of meetings they don't need to be at look good.
Also, it completely misses your crack team - the 3-4 people who you can hand a problem to, and know that they'll have it solved by next Tuesday, no questions asked. When those people shut their office door, you leave them alone, because you know they are working miracles, and you'll only get int their way.
Web analogy - Google and page rank. Rule number one is that you never trust the page to tell you how important it really is. Pages with all the right keywords and a bunch of links are one of two things - the best of the best about a topic, or an SEO linkfarm. So you take those things into account, but you do so with a *huge* grain of salt. To augment it, you go looking for other supporting metrics - what do other people think?
The HR department has just automated a human approach to the problem - they took one piece of evidence that the human brain can wrap its head around, and made the computer count that. You want to do informatics and data mining right, you need to learn what the computer is good at, and start looking for deeper patterns that are hidden by masses of data too large for the human mind to encompass.
Umm... considering how safe, secure and (since recently) stable banks are, I dunno if /. is the worse choice for your money.
Come on Slashdot - I was gunning for a 'Funny' with the hot grits, but Opportunist needs an 'Insightful' here. This is deep commentary on what is wrong with world economy (and what is wrong with Slashdot).
I can't do online banking with Wachovia, and SLASHDOT corrcetly (sic)
Banking with Slashdot? Forget which browser you use - there's your problem!
If Slashdot were a bank, we'd have all sorts of problems with easily detectable duplication of small bills, and none other than Cowboy Neal for security. Also, instead of those little suckers you get at most banks, you'd probably end up being offered hot grits...
My money will be staying under the mattress, thanks!
Just to expand on a couple of your points:
But if you like multi-language programming then Python is good glue.
If you eat your own dog-food ... You are your own end-user, although occasionally other people may pretend.
If your target user is a non-programmer, who simply wants to be able to perform a task then you will need to wrap up the functionality in a non-programmatic way. GUIs are the best way (so far) of doing this. Because there is no intention of exposing an external call interface the overhead of mapping from language to language becomes pure overhead and there is a natural tendency towards a single monolithic language approach.
Almost 100% of *my* code is python these days, but I use it glue together any number of my old scientific applications that are often written in C. You can turn an archaic, unusable program into a slick, modern GUI or web service with very little code.
Most important here, though, are your points about who your target audience is. I think the submission author is missing that point, and it deserves to be made in no uncertain terms.
I am a scientist and a programmer. When I am writing for myself, I want to spend time on my data, not my program. So, I bang something out unix style - command line only, text I/O, move on with life. Usually, that happens in Python, but it might be in C, R, MatLab - whatever. Programs from my PhD are almost strictly command line. My co-workers from that part of my life had to learn command line if they wanted to work with my stuff. And you know what? They all did. Some of them got quite good at it, and I had more than a few inquiries about learning to program - they all saw the utility of what I was doing.
After finishing my PhD, I've worked a little for a start up and a government agency, both based on my PhD research. In both cases, I've played the role of the scientifically literate programmer. My users are somewhat tech savvy, but with few exceptions, they don't want command line tools.
A few of my old tools are still in use, though, just because they do one thing so very well, and a handful of people took the time to learn them. In return, I save them hours every day, which make those few tech savvy souls very happy.
The trend - what is likely to keep me employed for years to come - is building GUI/web programs for people who are good scientists, but don't understand.
I take a hybrid approach. What my end user sees is a standard Windows GUI. They happily click buttons to find some raw data, and then their analyzed data pops up automatically in Excel.
Behind the scenes though, my code is an amalgam of programs, most of which can still be run command line, just like they always could. The GUI code is wxPython, and it quite happily runs on Windows and Linux. I think it would run on a Mac, too, but I haven't had occasion to try it yet. It looks native in all of those environments, it never does anything to scare the users, and yet I can still do most of my analysis command line when I need to.
I'm currently developing a DNA sequence database. User interaction will all be web-based, data analysis will largely be a mixture of Python, MatLab, and C programs behind the scenes. My users won't have to care how their data gets analyzed - it'll just magically show up in the form they need it. They focus on further analysis and interpretation. Given who my users will be, this is a Very Good Thing(tm).
The point, though, is that my programming spans everything the submission discusses. These approaches aren't orthogonal. Pick the right one for the code you are working on.
If you are coding for yourself or for very tech savvy scientists, stay command line. It's easier to code and debug, and you'll get more done.
If you are selling to Joe Sixpack, a GUI with a Staples-style 'Easy Button' is probably the right choice. Add advanced options as stand-alone
This approach goes after an area on the virus that is hard to reach because of its structure.
Err, not really. Your body *could* produce antibodies to that region, but that region doesn't normally get your immune system very excited.
Flu has five primary antigenic sites that do provoke your immune system. Not surprisingly, these are hyper variable regions, hence the need to reformulate the vaccine every couple of years.
There are a standard set of tricks that you can use to force an immune response to particular part of a protein. For example, get rid of the stuff that normally provokes the immune response. TFA doesn't say that - you'd need to read the methods section of the paper, or just know something about monoclonal antibodies.
Once you've got a cell producing an antibody you like, you 'immortalize' it - basically turn it into a cancer cell. It now continues to produce a monoclonal antibody, as opposed to the broad mix of antibodies your immune system normally produces, called polyclonal antibodies.
These techniques are not specific to flu, and not very revolutionary. Also, this is a hugely expensive way to treat the flu. Monoclonal antibodies only make fiscal sense in research settings, not as a widely available treatment for humans.
Additionally, the people working on this (some of whom are my co-workers) should know better than to mention the idea of a universal treatment. Any number of antiviral drugs have been designed to target regions that don't normally vary all that much. Almost all of them are now ineffective due to the virus mutating in response to selective pressure from the drugs.
Don't get me wrong - this is cool science. But it is not a cure for the flu. Plan to keep getting your flu shot for many years to come.