Bookmarks for January 21st through January 28th

These are my links for January 21st through January 28th:

  • Shadow Government Statistics – Home Page – Have you ever wondered why the CPI, GDP and employment numbers run counter to your personal and business experiences? The problem lies in biased and often-manipulated government reporting
  • Axiomatics and Progress in the Light of 20th Century Philosophy of Science and Mathematics.pdf (application/pdf Object) – This paper is a contribution to the question of how aspects of science have been perceived through history. In particular, I will discuss how the contribution of axiomatics to the development of science and mathematics was viewed in 20th century philosophy of science and philosophy of mathematics. It will turn out that in connection with scientific methodology, in particular regarding its use in the context of discovery, axiomatics has received only very little attention. This is a rather surprising result, since axiomatizations have been employed extensively in mathematics, science, and also by the philosophers themselves.

Bookmarks for November 4th through November 9th

These are my links for November 4th through November 9th:

  • 30 Resources to Find the Data You Need | FlowingData – Let’s say you have this idea for a visualization or application, or you’re just curious about some trend. But you have a problem. You can’t find the data, and without the data, you can’t even start. This is a guide and a list of sources for where you can find that data you’re looking for. There’s a lot out there.
  • Christopher Pincock, Mathematics and scientific representation | PhilPapers – This book aims to investigate the philosophical consequences of the central role of mathematics in contemporary science. …The book will pursue the issue with a newly developed version of the following central questions: for each scientific representation, what does the mathematics contribute, how does the mathematics make this contribution and what does this contribution presuppose? I argue that there are five different kinds of contributions and structure my discussion around examples that fall naturally into these five kinds. The main conclusion of the book is that mathematics makes an epistemic contribution to the success of our scientific representations. Epistemic contributions include aiding in the confirmation of the accuracy of a given representation through prediction and experimentation.
  • Minnesota Studies in the Philosophy of Science : Minnesota Center for Philosophy of Science : U of M – Minnesota Studies in the Philosophy of Science is the world’s longest running and best known series devoted exclusively to the philosophy of science. Edited by members of the Minnesota Center for the Philosophy of Science (MCPS) since 1956, the series brings together original articles by leading workers in the philosophy of science. The ninteen existing volumes cover topics ranging from the philosophy of psychology and the structure of space and time to the nature of scientific theories and scientific explanation.
  • Cell Size and Scale -

A Limerick for Computational Epistemology

John Holbo, in a  recent post at the ever-entertaining Crooked Timber, challenged his readers to “write a song – or poem – expressing as clearly as you can, with extra style points for keeping it intelligible to an 8-year old – your favored philosophy of science.”

Here is my contribution:

A Limerick for Computational Epistemology

Science finds a normative naturalist foundation
Where logic meets mechanism in computation
Whose relevance to Man
Is supplied by an ‘aught’ implying a ‘can’
And to truths we may converge without termination.

This admittedly fails on the count of intelligibility, but it was a fun exercise nonetheless.

Update:  Another entry of mine:

I admit that Logical-Empiricism left me impressed
Though early forms couldn’t pass the verification test.
And Constructive Empiricism
Is not without lyricism,
But I find a variety of structural realism the best.

Bookmarks for August 17th through August 20th

These are my links for August 17th through August 20th:

  • Mark Colyvan, A topological sorites | PhilPapers – This paper considers a generalisation of the sorites paradox, in which only topological notions are employed. We argue that by increasing the level of abstraction in this way, we see the sorites paradox in a new, more revealing light—a light that forces attention on cut-off points of vague predicates. The generalised sorites paradox presented here also gives rise to a new, more tractable definition of vagueness.
  • Vincent F. Hendricks, The Bain of two truths | PhilPapers – A view among methodologists is that truth and convergence are related in such a way that scientific theories in their historical order of appearance contribute to the convergence to an ultimate ideal theory. It is not a fact that science develops accordingly but rather a hypothetical thought experiment to explain why science develops at all. Here, a simple formal model is presented for scrutinizing the relations between two truths and convergence.
  • Risk (Stanford Encyclopedia of Philosophy) – Since the 1970s, studies of risk have grown into a major interdisciplinary field of research. Although relatively few philosophers have focused their work on risk, there are important connections between risk studies and several philosophical subdisciplines. This entry summarizes the most well-developed of these connections and introduces some of the major topics in the philosophy of risk. It consists of five sections dealing with the definition of risk and with treatments of risk related to epistemology, the philosophy of science, ethics, and the philosophy of economics.
  • The Management Myth – The Atlantic (June 2006) – Most of management theory is inane, writes our correspondent, the founder of a consulting firm. If you want to succeed in business, don’t get an M.B.A. Study philosophy instead

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…