User talk:Kiefer.Wolfowitz/Archive 14
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Copyright Violations, Plagiarism, etc.
Disinfopedia
I've looked at a few of those articles, and they seem ok - and then I noticed they were created on 20 August 2004, so hopefully any major problems will have been fixed since. I'll look at the rest as I get the chance, though. Black Kite (t) (c) 00:37, 31 July 2011 (UTC)
- Hi BK!
- Thanks for the quick reply.
- My quick look at the 3 articles indicated that, in each case, the bulk of the present article had been input by the energetic IP that day. However, others' additions would make the quick-deletion nomination more of a headache. (I noted my BLP/RS/NPOV concerns, earlier.)
- The spirit is willing to investigate more articles, but the flesh is indeed weak.
- Cheers, Kiefer.Wolfowitz 00:43, 31 July 2011 (UTC)
- I cleaned up the present version of Thomas L. Rhodes. Another editor had cut & pasted copyrighted material from National Review Online. (That IP's two copyright violations had been cleaned up.) I suppose that the history must be cleaned up. Kiefer.Wolfowitz 02:11, 31 July 2011 (UTC)
- For future reference IP did about 15 more similar uploadings of articles from disinfopedia, on August 20, according to his edit summaries.
- {{db-g12|url=sourceurl}} {{tl|close paraphrasing}} Kiefer.Wolfowitz 04:22, 31 July 2011 (UTC)
- I tagged the problem ones as best as I could. Three additional copyright violations have been deleted, bring the total to 5, and two other articles are flagged as having copyright problems (with salvageable text otherwise).
- As you had wished (above), the WP community did fix most of the articles. Kiefer.Wolfowitz 06:31, 31 July 2011 (UTC)
I don't think the situation at Committee on the Present Danger is clear.
While the bulk of the current text matches what appears at this sitec, note the CC 3.0 license.
Perhaps you did, and were arguing that it is plagiarized, rather than a copyvio.
However, much of the material in the WP article was there in 2005, so it may be that the linked site copied the WP site. Whether the original WP material is valid is not yet clear.
I'm going to add the template that hides the content, and send this off to the copyright experts, unless you think I'm missing something.--SPhilbrickT 00:24, 2 August 2011 (UTC)
- Please use the link I supplied, which is to the 1989 page, which has (in this case) been updated. The 1989 page was plagiarized/copied. And it still furnishes the bulk of the article. Kiefer.Wolfowitz 00:48, 2 August 2011 (UTC)
- It was the original: " Posted: January 06, 1989" and "Updated: 7/89".
- Thanks for your quick response. Kiefer.Wolfowitz 00:49, 2 August 2011 (UTC)
- I copied this discussion to the CopyVio noticeboard, where the conversation started. Sphilbrick is correct that the CC 3.0 license allows copying, but only if appropriate credit is given. In these cases, it seems that the credit has not been given, and so at minimum extensive re-writing (inserting quotation marks, footnotes, etc.) is needed to bring the articles into compliance. Kiefer.Wolfowitz 02:29, 2 August 2011 (UTC)
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Carleman
Hi,
you have recently edited the article on Torsten Carleman, reducing the part devoted to alcohol abuse. I feel it can be further reduced (in favour of expanding the scientific part); esp. the part about antisemitic remarks. The citation (of Feller) says: "... partly because C. is of the touching opinion that one should execute all Jews and immigrants (which, however, he only tells his assistant after consuming a nonnegative amount of alcohol)". This is the only source I found in the internet mentioning antisemitic remarks by C, and even this could apply to a single episode (also note that Feller mentions one assistant, whereas the article is in plural). Especially, there is no evidence of any antisemitic actions on his part.
To my opinion, a footnote with exact citation (like in the article on Feller) would be more appropriate. (For comparison, the well-known antisemitic activity of dozen or more of Soviet mathematicians with a firm "record" -- e.g. Sergey Stechkin -- is not mentioned anywhere in the articles.)
What do you think?
Thanks,
Sasha (talk) 22:17, 4 August 2011 (UTC)
- Hi! please edit it as you see fit. I have not looked at the recent books on Swedish far-right and Nazi organiations during the 1930s and 1940s, to check for Carleman. Kiefer.Wolfowitz 18:18, 5 August 2011 (UTC)
- please have a look (at the revised version). I have not looked at these books either -- do you know a precise ref.? -- but honestly, I find it hard to believe he was a member of a Nazi organisation (and if he would, this would probably have been well known by now).
- Best,
- Sasha (talk) 00:25, 6 August 2011 (UTC)
- Hi Sasha!
- According to the oral history of Swedish probabilists and statisticians, anti-semitic Carleman blocked William Feller from a professorship because he was Jewish. Someday, somebody will look at the archives of Stockholm/Uppsala Universities, Carleman, Feller, and Cramér and write a scandalous history.
- I did not say that he was a Nazi. There were many professors who were members of nationalist organizations, some of which had fascist ties, in the 1930s. It would be useful to look at the books that name names.
- Best regards, Kiefer.Wolfowitz 07:16, 6 August 2011 (UTC)
- Hi again! Your edits look fine. The quote from Feller says enough, and I am glad that you left in the article. Cheers, Kiefer.Wolfowitz 08:58, 6 August 2011 (UTC)
- About anti-semitism back in the U.S.S.R., you may wish to consult Freiman's "It Seems That I Am a Jew", which names names. It contains an appendix signed by 10-20 of the most renowned emigrants affirming that the anti-semitism described was real and further naming names. Kiefer.Wolfowitz 09:01, 6 August 2011 (UTC)
- thanks! I did not know this story (about Feller) -- indeed, his letter hints this, but I have never heard it in other places.
- There are indeed lots of ref-s about Soviet antisemitism (e.g. "You Failed Your Math Test, Comrade Einstein: Adventures and Misadventures of Young Mathematicians, Or Test Your Skills in Almost Recreational Mathematics", which is a story about Bella Subbotovskaya and her environment). Are there any books about antisemitism/ fascist sympaties in the Swedish universities at the 30-s - 40-s (is that what you proposed to check)?
- Best regards,
- Sasha (talk) 15:02, 6 August 2011 (UTC)
- Hi again, Sasha!
- I looked at one book of Swedish Nazi/Extreme-Nationalist members some years ago, and saw that a dear friend's great grandfather was listed (as I had feared, given the inherited books on phrenology and racial types in the family), and didn't want to look more. Sweden and in fact Uppsala University had a world-leading center for racial science, and eugenic sterilization was practiced until 1970 or so---more on persons with disabilities---but apparently somewhat on nonconformists, or Samis/Laps or Gypsies. I get depressed already by the contemporary Anti-Imperialism of Fools and the "classic" Socialism of Fools, which has never gone out of style in Europe, that I don't have the energy to dig around the past. There is enough to do with trying e.g., to reduce Jew-baiting on Wikipedia.
- You might ask at the WikiProject Sweden for help, though. Or at the talk page for the Carleman article (or better for something about extreme right wing politics in Sweden in the 1930s ...) on on Swedish Wikipedia. My guess is that the Swedish Universities of the 1930s were not as cheerfully liberal, cosmopolitan, and welcoming as the brandy-sifting British ruling class portrayed in Remains of the Day. I think that all the political parties committed anti-semitic and nationalistic sins in the 1930s.
- About discrimination in the 1970s in the USSR, there were good articles in the Mathematical Intelligencer and Notices of the AMS, also. Boris Polyak made a good and appropriately brief acknowledgment of "shameful" history in his lecture on "Optimization in the U.S.S.R", which I cited on Kantorovich's article (for its other virtues); it cites a few good sources, briefly.
- Sincerely and striving to avoid misanthropy, Kiefer.Wolfowitz 17:32, 6 August 2011 (UTC)
- Hi again, and thanks for the interesting conversation.
- Returning to wiki articles about antisemitic activity of mathematicians: my modest opinion is that this subject is unworthy of excessive wikification. As to Carleman, time will "pardon him for writing well" (and proving well).
- Best regards,
- Sasha (talk) 19:10, 6 August 2011 (UTC)
- You are right. I think it's okay to have the one quotation from Feller, for now, unless somebody writes an article on Carleman. Carleman was a saint compared to Bierberbach, et alia .... Kiefer.Wolfowitz 19:17, 6 August 2011 (UTC)
last post here, but fyi
Closed discussion
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china forex purchases devalue reniminbi
Reply, continued
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Bayesian vs. Frequentist vs. Likelihood
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As a person with only a working knowledge of frequentist statistics, I find the internet to be a bit scarce when it comes to good (and comprehensible) reference articles that contrast these three sub-disciplines. Since you are a statistician and like to add content in here, maybe that is something you can contribute to along with your hated enemies from Bayesian and Likelihood schools. --Bobthefish2 (talk) 21:52, 11 August 2011 (UTC)
Statistics, since 1950A decision-theoretic justification of the use of Bayesian inference was given by Abraham Wald,[citation needed] who proved that every Bayesian procedure is admissible.[citation needed] Conversely, every admissible statistical procedure is either a Bayesian procedure or a limit of Bayesian procedures.[1] Wald's result also established the Bayesian approach as a fundamental technique in such areas of frequentist inference as point estimation, hypothesis testing, and confidence intervals. Wald characterized admissible procedures as Bayesian procedures (and limits of Bayesian procedures), making the Bayesian formalism a central technique in such areas of frequentist statistics as parameter estimation, hypothesis testing, and computing confidence intervals.[2] For example:
Likelihood heuristics are not frequentistThe "Likelihood" school has all the problems of Bayesian inference and few of its virtues. Finding a zero of the derivative of the likelihood "function"
is preferable to "maximum" likelihood estimation in many cases, and certainly for a general asymptotic theory, and it
The neo-Fisherian "method" of "testing hypotheses" on the data generating them was labeled the most dangerous fallacy of induction by Peirce. (Maximum-likelihood estimation was the most popular fallacy!)[1] Reasoning and the Logic of Things (RLT) (The 1898 Lectures in Cambridge, MA)
This looks like a very very long read (and I have not even learned there is a "Fisherian" and "Pearsonian" school of thought). Do you think the main differences can be illustrated with a simple defining example? --Bobthefish2 (talk) 23:31, 11 August 2011 (UTC)
ExampleConsider a coin toss. We agree to wait for Jimbo Wales at a Wikimania convention, and we ask one of his disciples for a penny, because it will cure us from our lack of "the sum of all human knowledge". We wish to use this penny in the future, to break the Methodist Book of Discipline by gambling, so we want to know how fair it is.
The frequentist could give you median/mean-unbiased estimators if you allow him to flip the coin (as could a confused and cowardly Bayesian who is afraid to be called "subjective" and so mumbles "likelihood").
I ask you, if you cared about using this estimate in practice, which of these estimates would you use? A Bayesian statistician could give you a true probability distribution on the parameter space, the interval [0,1], which you could use to do simulations. We could do more flipping, and we would find that after 30 throws, there wouldn't be much difference between them. Asymptotically, all of the estimators will agree, but the Bayesian estimator (say median posterior) is robust and useful for small sample-sizes and can be used honestly by practitioners wanting to do simulations (and unwilling to pick a single number for their parameters). The likelihood approach and the Bayesian approach rely on probability models, which are always wrong (apart from electron emissions, etc.), and which almost always are so bad that nobody bothers updating the posterior when more data arrives. Usually, scientists just improve the measurements by improved experimental technique; the jaw-boning about n goes to infinity is just irrelevant to scientific practice (as Peirce noted long ago). It is better to use design-based inference, using the randomization specified in the sampling/experimental design, than to put up a parametric model, if possible. If inference relies on a model, warning labels should be attached, imho. The posterior median and median-unbiased estimators are invariant under reparametrization. A ML estimator (if defined with some initialization) is invariant somewhat in a weaker sense. The mean-unbiased estimator is not invariant under reparameterization. Kiefer.Wolfowitz 23:54, 11 August 2011 (UTC)
NonparametricsThis book is a good overview of how much statistics can be done, and done very well, without any parametric model:
Such methods don't give probability models that can be used for predictive inference and decisions, though. Kiefer.Wolfowitz 00:15, 12 August 2011 (UTC) Statistics since 1950You should beware of any survey of inference (most unfortunately) which doesn't deal with the following concepts (about which I write in "Statistical inference"). Like any good mathematical theory, it has links to concepts in mathematics and related mathematical sciences (communication theory, computer science, physics, etc.), it improves our understanding of previous results, and raises new questions. Kiefer.Wolfowitz 00:08, 12 August 2011 (UTC) Information and computational complexityOther forms of statistical inference have been developed from ideas in information theory[1] and the theory of Kolmogorov complexity.[2] For example, the minimum description length (MDL) principle selects statistical models that maximally compress the data; inference proceeds without assuming counterfactual or non-falsifiable 'data-generating mechanisms' or probability models for the data, as might be done in frequentist or Bayesian approaches. However, if a 'data generating mechanism' does exist in reality, then according to Shannon's source coding theorem it provides the MDL description of the data, on average and asymptotically.[3] In minimizing description length (or descriptive complexity), MDL estimation is similar to maximum likelihood estimation and maximum a posteriori estimation (using maximum-entropy Bayesian priors). However, MDL avoids assuming that the underlying probability model is known; the MDL principle can also be applied without assumptions that e.g. the data arose from independent sampling.[3][4] The MDL principle has been applied in communication-coding theory in information theory, in linear regression, and in time-series analysis (particularly for chosing the degrees of the polynomials in Autoregressive moving average (ARMA) models).[4] Information-theoretic statistical inference has been popular in data mining, which has become a common approach for very large observational and heterogeneous datasets made possible by the computer revolution and internet.[2] The evaluation of statistical inferential procedures often uses techniques or criteria from computational complexity theory or numerical analysis.[5][6]
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