Readit Newsthe impression I get from anecdotes and remarks is that pre-1990s, university departments used to be the major scientific social institution, providing organization where the science was done, with feedback cycle measured in careers. Faculty members would socialize and collaborate or compete with other members. Most of the scientific norms were social, possible because the stakes were low (measured in citations, influence and prestige only).
It is quite unlike current system centered on research groups formed around PIs and their research groups, an machine optimized for gathering temporary funding for non-tenured staff so that they can produce publications and 'network', using all that to gather more funding before the previous runs out. No wonder the social norms like "don't falsify evidence; publish when you have true and correct results; write and publish your true opinions; don't participate in citation laundering circles" can't last. Possibility of failure is much frequent (every grant cycle), environment is highly competitive in a way that you get only few shots at scientific career or you are out.
I use this method often for prediction applications. First, it’s a sort of hyper parameter selection, so you should obviously use a holdout and test set to help you make a good choice.
Second, I often see the method dogmatically shut down like this, in favor of lasso. Yet every time I have compared the two they give similar selections — so how can one be “evil” and the other so glorified? I prefer the stepwise method though as you can visualize the benefit of adding in each additional feature. That can help to guide further feature development — a point that I’ve seen significantly lift the bottom line of enterprise scale companies.
The distaste for step-wise selection comes from its typical use. If one reads Harrell's complaints quoted in the blog post carefully, quite many of them are less about the selection method but what analyst does with it, namely, interpretation of inferential statistics. When you see step-wise in the wild, practitioner often has used step-wise or other selection method and then reports the usual test-statistics and p-values for the final fitted model ... that are derived with assumptions that don't usually take into account the selection steps. It is quite unfortunate in fields where people put lot of faith in coefficient estimates, p-values and Wald confidence intervals when writing conclusions of their paper.
With LASSO and its cousins, the standard packages and literature strongly encourage the user to focus on predictions and run cross-validation right from the beginning.
>Although modest bivariate associations were detected with educational attainment (r = .17) and body mass index (r = −.17), almost all regression-adjusted coefficients were nonsignificant. No clear pattern of moderation was detected between delay of gratification and either socioeconomic status or sex. Results indicate that Marshmallow Test performance does not reliably predict adult outcomes.
I guess the question is whether the covariates that were adjusted for in the regression are true confounders and not, say, something caused by ability to delay gratification.
Well. You have to exist, which means you compete, which might mean you grow.
Why growth? At some point you would eventually hit perfect saturation anyway, the steady state where everyone already is buying your product to the extent anyone can buy it. I get that losing business is bad, and it's better to "overcorrect" to growth, but as long as you compete enough to keep approximately same market share against other competitors, selling inflation adjusted $30 buckets of bricks to each generation of kids with profit sounds like perfectly good business. Owner of the business would receive steady income selling the inflation adjusted $30 buckets.
I'd imagine you'd hit problems when the buckets of bricks you are selling are ~eternal and number of kids is no longer growing, so nobody needs new ones.
What should be encouraged is for academics to blog about their research as well. It would even help when recruiting and onboarding new members. Right now the sociological and economical incentives don't promote this at all.
Here is an added complication: succinct technical communication can be efficient when communicating to peers who work on the exactly same domain, similar problems as you, and want digest your main ideas quickly.
On the other hand, for any particular paper, the size of the audience to whom it is directly relevant and addressed to can be small. The size of the audience who got to reading it anyway may be vast. (Maybe I am reading your paper because someone cited a method paper that in lieu of a proof or explanation writes just two words and citation to your paper. Maybe I am a freshly minted new student reading it for my first seminar. Maybe I am from a neighboring field and trying to understand what is happening in yours. Maybe I tried to find what people have already done with particular idea I just had and search engine gave your paper. And so on.)
During my (admittedly lackluster) academic career I recall spending much more time trying to read and understand papers that were not addressed to me than papers that were and where I enjoyed the succinct style that avoids details and present the results. (Maybe it is just an idiosyncratic trust issue on my part, because I am often skeptical of stated results and their interpretation, finding the methods more interesting). But that is not all.
I also noticed that genuine misunderstandings coming from "brief" communication of technical "details" were quite common; two different researches would state they "applied method X to avoid Y/seek Z[citation]" in exactly so many and almost exactly same words, where X,Y and Z were complicated technical terms, yet the authors would have quite different opinion what the meaning of those words were and what would be the intended reading and how and why X should be implemented.
In conclusion, I think many a scientific field would benefit from a style where authors were expected to clearly explain what they did and why (as clearly as possible).
I’ve never used jupyter for taking notes in a lab setting, but with more and more instruments being computer/network connected, I imagine this would make total sense - put your data and notes with your analytics work.
Many jupyter users are not «software developers», they just use code to perform their work.
(How one does a diff of a data object look like? If there is a natural text format to save it in, it still is usually quite messy, and Git doesn't really like Gb sized csvs.)
My preferred workflow is to version the source files in Git and store the associated data objects in a separate archive directory with meaningful name and the hash of commit of generating code as metadata attribute.
Now if you had a version control "IDE" software that would render changes in figures and other blobs nicely, then it would make sense to build a workflow around it.
I would argue contrariwise, the education today is bad because the textbooks are devoid of content and nobody can recite any of the little they have. For my parents' generation it was not unexceptional for people to cite poems from memory. I have bunch of their middle school books, and it appears they read more and longer texts for middle school than some university students today. During my grandfather's time kids were expected to recite a chapters of textbooks aloud in front of class, and he also remembered good bunch chunks from the Bible.
Compared to that, fill-in textbooks we used when I was in school seem a bit underwhelming -- and I am in my 30s. Kids today use e-learning environment (makes direct comparisons difficult).
Today, very few people appear to read anything, let alone books, even fewer remembers anything. Thus conversations about anything factual seem often pointless. But it is not like one can blame anyone for that, it only makes sense: Why truly should I remember anything when I can flip out a smartphone and hit query to a search engine? But people reading the same Wikipedia article or repeating the same news cycle talking points at each other makes for a boring conversation.
If current FPV drones are bit lackluster, it doesn't preclude 'next generation' that are purposefully developed for military use won't be useful. Also it sounds like the designation of "FPV drone" is specific to particular family of drones specific in current day and time, which may be something quite else next year. Like, obviously the next stage is a FPV drone with some capabilities of "reusable" drone or loitering munition author complains of (capability to hover easily)? Or "reusable" drone with FPV camera?