Category Archives: Recommended

Recommended: Is the staggeringly profitable business of scientific publishing bad for science?

I attended a talk about a decade ago on the problems with for-profit publishing of scientific research and the need to aggressively adopt the open source publication model. It was a message I was ready for, because I had benefited greatly from citing open source resources on my website. I knew that if I cited an open source resource, anyone anywhere could look up that resource. They didn’t need access to a University Library.

This article explains how the for-profit research journals (perhaps better described as a reader-pays model, in contrast to an author-pays model) developed a system that locked in research libraries to their product and then hiked the price. Then they developed journal bundles that further squeezed libraries by forcing them into a take-it-all-or-leave-it-all system that devastated their budgets.

There is still a struggle between the reader-pays model of for-profit publishing and the author-pays model of open source publishing, and I believe there is room for both approaches, though I would argue that we need to promote open source publishing more aggressively than we currently are doing.

This article provides a very nice historical context to the development of for-profit publishing in scientific research. It oversimplifies things, perhaps, and may be a bit too harsh, but it is definitely worth reading.

As an ironic footnote, newspapers have been devastated by the Internet because of the expectations of readers that all of their content should be available for free. There is a note at the bottom of the Guardian article that reads: “Since you’re here we have a small favour to ask. More people are reading the Guardian than ever but advertising revenues across the media are falling fast. And unlike many news organisations, we haven’t put up a paywall – we want to keep our journalism as open as we can. So you can see why we need to ask for your help. The Guardian’s independent, investigative journalism takes a lot of time, money and hard work to produce. But we do it because we believe our perspective matters – because it might well be your perspective, too.

Take some time to read this and think about it. I normally ignore pitches like this on Wikipedia and elsewhere, but the irony of citing a newspaper article available for free to criticize for-profit research publishing got to me, so I became a supporter of the Guardian at $6.99 per month.

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Recommended: ProbOnto

If you work with probability distributions a lot, you find there are mutliple parameterizations (e.g., the two different forms of the exponential distribution), as well as interesting relationships (the geometric distribution is a discrete version of the exponential distribution). I have found Wikipedia to be a nice guide for some of this, but the coverage is uneven in quality. One of the Wikipedia links mentioned a new website, ProbOnto, that offers a systematic and standardized attempt to catalog every important probability distribution and the relationships among these distributions. Continue reading

Recommended: Why R is Bad for You

Arguing about R versus SAS often takes on a religious fervor, so I normally hesitate to recommend articles that trash one package or the other. But this one raises an interesting point which makes it worth reading. Note that “recommended” does not mean that I endorse these conclusions. But rather than bias you with my perception of the issue, just read this on your own. Continue reading

Recommended: ROSE: A package for binary imbalanced learning

Logistic regression and other statistical methods for predicting a binary outcome run into problems when the outcome being tested is very rare, even in data sets big enough to insure that the rare outcome occurs hundreds or thousands of times. The problem is that attempts to optimize the model across all of the data will end up looking predominantly at optimizing the negative cases, and could easily ignore and misclassify all or almost all of the positive cases since they consistute such a small percentage of the data. The ROSE package generates artificial balanced samples to allow for better estimation and better evaluation of the accuracy of the model. Continue reading