Bookmarks for July 29th through August 16th

These are my links for July 29th through August 16th:

• Bayes, Jeffreys, prior distributions, and the philosophy of statistics – In this brief discussion I will argue the following: (1) in thinking about prior distributions, we should go beyond Jeffreys’s principles and move toward weakly informative priors; (2) it is natural for those of us who work in social and computational sciences to favor complex models, contra Jeffreys’s preference for simplicity; and (3) a key generalization of Jeffreys’s ideas is to explicitly include model checking in the process of data analysis.
• Does Confirmation Work the Same at Every Level of Science – In the 1960s, Kuhn maintained that there is no standard higher of rationality than the assent of the relevant community. Realists have seek to evaluate the rationality of science relative to a highest standard possible—namely the truth, or approximate truth, of our best theories. Given that the realist view of rationality is controversial, it seems that a more secure reply to Kuhn should be based on a less controversial objective of science—namely, the goal of predictive accuracy. Not only does this yield a more secure reply to Kuhn, but it also provides the foundation on which any realist arguments should be based. In order to make this case, it is necessary to introduce a three-way distinction between theories, models, and predictive hypotheses, and then ask some hard questions about how the methods of science can actually achieve their goals. As one example of the success of such a program, I explain how the truth of models can sometimes lower their predictive accuracy…
• What is a statistical model? – This paper addresses two closely related questions, “What is a statistical model?” and “What is a parameter?” The notions that a model must “make sense,” and that a parameter must “have a well-defined meaning” are deeply ingrained in applied statistical work, reasonably well understood at an instinctive level, but absent from most formal theories of modelling and inference. In this paper, these concepts are defined in algebraic terms, using morphisms, functors and natural transformations. It is argued that inference on the basis of a model is not possible unless the model admits a natural extension that includes the domain for which inference is required. For example, prediction requires that the domain include all future units, subjects or time points. Although it is usually not made explicit, every sensible statistical model admits such an extension. Examples are given to show why such an extension is necessary and why a formal theory is required…
• Are You Happy? – The New York Review of Books – Chances are if someone were to ask you, right now, if you were happy, you’d say you were. Claiming that you’re happy—that is, to an interviewer who is asking you to rate your “life satisfaction” on a scale from zero to ten—appears to be nearly universal, as long as you’re not living in a war zone, on the street, or in extreme emotional or physical pain. The Maasai of Kenya, soccer moms of Scarsdale, the Amish, the Inughuit of Greenland, European businessmen—all report that they are happy. When happiness researcher Ed Diener, the past president of the International Society of Quality of Life Studies, synthesized 916 surveys of over a million people in forty-five countries, he found that, on average, people placed themselves at seven on the zero-to-ten scale…
• Should Copyright Of Academic Works Be Abolished? – The conventional rationale for copyright of written works, that copyright is needed to foster their creation, is seemingly of limited applicability to the academic domain. For in
  a world without copyright of academic writing, academics would still benefit from publishing in the major way that they do now, namely, from gaining scholarly esteem.
  Yet publishers would presumably have to impose fees on authors, because publishers
  would not be able to profit from reader charges. If these publication fees would be borne
  by academics, their incentives to publish would be reduced. But if the publication fees
  would usually be paid by universities or grantors, the motive of academics to publish
  would be unlikely to decrease (and could actually increase) – suggesting that ending
  academic copyright would be socially desirable in view of the broad benefits of a
  copyright-free world…