461 karma · joined August 4, 2011
- the quicker but less rigorous way: set things up like a forum like HackerNews, let the crowd-sourced upvote and comment system work its magic; make the karma/reputation points act as a proxy for the quality and relevance of the article, its authors, as well as the commenters.
- the slower way: let articles "bubble" up from smaller but more specialized workshops toward more generalized and prestigious conferences and journals. Have the technical committee recommend the best articles to those more reputable venues, along with whatever it is the authors need to work on to re-submit the extended version at that "better" venue. This is kind of already the case with workshops or conferences that have an associated Special Issue of a journal; I'm advocating for a generalization of the practice to all venues and more than a 2-level hierarchy. The reputation of the lower venues could be backpropagated by the number of papers they successfully "bubble" up, PageRank style, so that would be the incentive the committees would have in recommending their papers to the other venues.
Best of luck!
We're getting to the point where there really has to be a financial incentive to do a peer review (Springer gives you a free book, which is a start). If that were the case, I wouldn't mind doing it occasionally when I retire.
Wow, I think this last paragraph of yours manages to capture exactly what a philosophy or an ideology is for: perspectives to help create meaning.
My follow-up question then is: what makes for a "good" perspective? Can you judge it, to get back to the topic of this thread, by the number of mooks it enrolls?
edit: I guess because "01" isn't a valid token.
[1] Briot, Jean-Pierre. “Actalk: A Testbed for Classifying and Designing Actor Languages in the Smalltalk-80 Environment.” ECOOP (1989).
I think you summarized beautifully the difference between design ("make choices") and implementation ("get things to work"). Am I correct in that?
* at least universities who depend on a large extent on tuition money and government incentives to match said tuition.
Also, the authors had to show how these patterns can be implemented in different programming languages (Smalltalk and C++). Fowler could get away with one simple example of a refactoring in Java each time.
Having said that, Fowler's prose is super clear, something that cannot be necessarily said about GoF, (IMO of course)...
- Hastie is a co-author of two machine learning books, one is "Elements of Statistical Learning" which is very comprehensive, and "Introduction to Statistical Learning", which is more approachable by people without too much background in stats.