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BubbleBlower

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About BubbleBlower

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  1. Things will be shuffled about here and there. Despite some apparent ups and downs stagnation under any other name will continue. Britain will remain within the EU as the potential for moaning about bloody foreigners will be severely reduced outside of it. HPI will not really increase over the year as a whole, despite periods of glorious excitement and rampant despair. Any real crash will be avoided by financial shenanigans of the utmost quality. In short, much like the previous five years, not a lot will actually happen, despite the appearance of quite a lot being done very visibly by rather important people. Word economy is to ******ed up to recover, too large to fail.
  2. Thanks for the thoughtful reply. This snippet of what you said gets to the heart of what I'm asking: why do we use a small basket of goods as a sample of what people are spending money. You point out at least one inaccuracy / bias that gets introduced by attempting to model all spending in the economy by a small sample. If we have the raw data (and by we I actually mean the government who could get their hands on it) why not calculate inflation directly from the full dataset?
  3. Here is a question that has puzzled me for a long time. When we measure inflation in the economy we pick a basket of goods and measure how their price hanges over time. The choice of what goes in the basket affects the result, and we get political manipulation in the indices as we see in the differences between RPI and CPI, for example. Why is there not a inflation index where the basket is defined by what people actually spend money on? If there is such a beast could someone point me towards it? If there is not how would it be defined: assuming that we have all the statistics about what the population spent their cash on every month how would we decide what went into the basket? Are we looking for something analogous to the "mean" spending pattern, or the "median" spending pattern. Lastly, and most importantly: what would this hypothetical index be doing right now? Would it point to deflation because of belt-tightening, or inflation due to rising costs?
  4. Your Rightmove chart doesn't really prove anything. Have you got any more data? You've shown 7 months of data for a market with strong annual patterns. How about the spring supply figures for any other year?
  5. So here is the crux of the argument: everybody here seems to have a different definition of bluesky research (as frozen_out mentioned earlier). I would not call this bluesky at all - it is clearly very applied, and also very close to development into applications. I would say that bluesky research is the kind of theory that you don't know what it will be used for - but it seems obvious that it is interesting or useful. So in this context the bluesky area would be more general work in mapping out how antibodies bind. Perhaps using artificial but tractable models rather than the real data. By the time the research has reached the stage where you can point to a specific application it is no longer bluesky.
  6. This reminds me of a place that I lived in a few years back. We were renting the top-floor flat in a Georgian terrace. When we moved in the old couple beneath starting leaving lots of messages for us, quite desperate to meet us. Turns out that they wanted to complain in advance just incase we were noisy. Apparently they had this fantastic right because they owned their flat where-as we were just renter-scum (although they tried to explain it more gently than that). We thought it was vaguely amusing at first and put it down to senility - until they started to complaining to our landlord. Apparently the normal noise of people walking about was too much for their sensitive ears. We would find notes posted through our door telling which nights they were going to bed early. They quite seriously suggested that we should put down thicker carpets and find fluffy footwear to deaden the sound. Then complaints started about using garlic in food: apparently the old dear also had an incredibly acute sense of smell and wanted to dictate what type of cooking we should do. Luckily our renter-scummyness was matched by the BTL-scummyness of our landlord who told them to feck off and stop being such twats.
  7. Speak for yourself. You are confusing cost with value. Research has obvious costs: salary, equipment, labs.... The value is harder to measure. For the sake of argument lets run with your idea that everything of value can have a monetary value attached to it. You are running a lab, you have three active projects and only enough funds for two. How do you decide the monetary value of the projects? Will you try to measure some kind of income? This will be hard, all three projects are still in the research phase, none have been converted in any commercial products yet. Will you try to estimate the time to completion? This will be as hard to measure as the length of string, research tends to be an ongoing activity. Unlike most other activities in the world it also involves doing new things. Without any kind of previous yardstick to measure against it is impossible to know which sub-problems will be easy and which will encounter unexpected problems. Estimates of how long research will take tend to be in a state of flux. Will you try and estimate the impact of the research? This will be hard as often applications are discovered once research has been completed. In this case it really is a question of guesswork. In some cases research is performed because we know what some of the potential applications are, and they are important enough to justify the research. But this does not mean that the most important research is justified by applications that we know of. I don't know how familiar you are with the Drake Equation, but estimating the coefficients there a walk in the park compared to judging the value of research before it is done. In an ideal world (not this one), we would know how long it will take to invent something, and how important it will be once we have done so. From there we could estimate the income and come up with some kind of monetary value, with some kind of risk attached to it. We don't live in that universe. So how do people cope? Simple. They pick the low hanging fruit. They don't try and research the important problems - instead they choose problems that we can turn into a monetary figure within five years. Things that are already close to development and commercial products. People do this because it is not certain that any piece of research will be successful, and chasing something that doesn't pan out for a long period of time can destroy a career. But you seem to be interpreting their actions in the wrong way - nobody in charge of managing research would claim that there is a correlation between the importance of a problem and the ease with which we can assign an accurate value estimate to it. Scientists would prefer to maximise expected impact (although they admit their estimates of impact are weak at best). Funding bodies would like to minimise risk. Nobody appears to be maximising expectation (probability of success multiplied by impact) - because to do this you must accept some slack in the system, and fund speculative projects that fail, in order to hit the speculative projects that succeed and expand our future options.
  8. Really. Where exactly is it? Because every news broadcast in the past 24 hours has been leading with the story that the Haiti government disappeared in the immediate aftermath of the quake, along with the UN force sent in to shore them up. Both presumably crushed by falling debris. Although the topic title by KFM is in bad taste, it does raise a simple and straightforward point (which is easy to express free from strawmen). Haiti is an example of a pure Free Market. There is no law, and there is no enforcement of that law. There are resources with huge demand (in particular water). Why is it not functioning according the idealistic picture of a Free Market painted by neo-libertarians?
  9. A couple of corrections: IBM has been at the forefront of nano-scale materials science for the past ten years. This is the very definition of blue-sky research; they are not selling products based on molecular assemblers and won't be for decades. Yet they are funding the research now on the understanding that it may produce dividends a long way down the line. Similar remarks can be made about their input to algorithms and other areas in TCS. Some details are available here. My field is within computer science so I can say from experience of at least a dozen universities that this is not true. But it soon will be. In the UK many CS departments are within engineering faculties, but this does not mean that they exclusively do engineering. CS has always been an interdisciplinary field somewhere between maths and engineering. Within the context of an engineering faculty most CS departments will still have theoretical research groups that research areas quite far from applied engineering. Unfortunately the proposed changes to EPSRCs funding criteria will shift this balance directly as they want basically want evidence of short-term application impact (the so-called 'socio-economic relevance'). This is very short-sighted, just as a single example of why it will break the essential interaction between theory and practice consider the problem of circuit design. Today we have vast industries based on large scale design and fabrication of circuits. Yet that would not be possible without the huge strides made in verification over the past two decades. All of those verification technologies (and I'm thinking of Model Checking in particular) started out as purely theoretical work in the maths ends of the subject. Not one of the original researchers would have been able to demonstrate the short-term socio-economic relevance of their work. So what you describe will come to pass if EPSRC gets their way. I would disagree strongly with what you've said, although if I've interpreted you properly I agree with what you mean. Perhaps it is a nitpick but I would disagree with calling the failed results waste. They are certainly a cost of doing research, but waste implies that they are avoidable rather than being an intrinsic part of what is being done. If we can separate out the successful results from the failed results in advance then what we are doing is not research - it is development work. Yes, this is a basic sociology problem, and one that we do not know how to solve. Sadly politicians think that it is a problem with how we do science and try to fix it by moving the goalposts.
  10. I love my job, and it makes me almost unique amongst the part of academia that I know. HPC is a good representative sample of academia in general; most people employed within academia are bitter and loathe what they do. I would claim that it is because we employ far too few academics in academia. During my PhD my supervisor did more than just tell me how to get through the process; he taught me what research is, and how to go about. That basic training is mostly lacking in most people in the sector. They do not understand why they are researchers, let alone how to go about improving their contributions. The basic problem is that the academic sector is too large, and the attempts to control (stiffle) its growth have driven out those who actually had the talent to be academics. Things are going to get worse. Performance Measurement is going to happen in academia, no matter how much people fight it. By itself there is nothing wrong with measuring performance, and even adjusting pay based on it. The real problem is that nobody has any good way of measuring academic output.There are many bad ways: counting publications, counting citations, counting grants income. Each of these measurements is open to gaming, and I know people who successfully game those particular metrics. They are not good researchers. So what is the problem with measuring academics? Their obvious output and the effect that they have on the world are largely separate. To measure their effect you need to examine lots of non-numeric data and find ways of ranking it. And you need to run your measurements over a long enough time period to account for the huge lag in how they influence the world.So that means that the academic sector is basically screwed. There is no good way to measure talent, and measurement will be enforced top-down. Conclusion? The talent will leave, and those that stay will be those that know more about gaming the system than doing the research that they are paid for. This would be a dark day for mankind if the division between blue-sky and applied research was as clear-cut as argued earlier on this thread. One bright point that wasn't mentioned is that companies do a lot of blue-sky research - and they do it according to a budget (as frozen_out was arguing), but over a long time-scale (as others were arguing). Look at the output of IBM in basic materials science, or Bell Labs, or any of a range of corporate research labs.The other ray of hope is that not every country is destroying its academic sector in the same way. I've had a good run as a postdoc in the UK, but I'll be looking for Lectureships in Europe.
  11. Having a quick look at their performance over the past three months they seem to be quite volatile. Is there a good reason that they seem to go up in the first half of the month and then drop down again for the month end? It looks very weird...
  12. Nice link. If you tweak the url a bit you can see what the UK version looks like here. It doesn't work on the .co.uk domain so take this American version and stick something like "london, uk" in the search box to see local listings. Seems quite cool.
  13. What did it? The rambling incoherent post decrying flats for their lack of protective ubermen, or the peculiar olfactory guide to living in poverty?
  14. Yes you are in the minority. Rather than being fantastic news for homeowners, this is good news for home-sellers and terrible news for home-buyers. Still, I wonder how many of the chartists on this board are looking at the rally in house prices while excitedly dribbling "double top double top...." under their breadth? I assume from your other comments that you are planning to sell up while the going is good. Are you going to join the (very small) army of buyers lining up to get screwed by these recent rises or are you going to join the winners on the side-lines? I can't help but wonder if getting rid of your property would reduce your bullishness on the market...
  15. Good to hear the old theme is coming back. Looking at the IP-Board link in the pinned Webmaster thread, is there any way we could get the "CleanLook" theme as well? I know many people have slated the new blue theme because of how comments look, but my main gripe with it is just that the filled in numbers and tags on the thread index look horrific. It would be nice if that CleanLook theme just dropped into the options at the same time as the classic...
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