Digesting the whole Wikipedia 
In the most recent issue of First Monday, Royce Kimmons has an interesting analysis of community contributions in Wikipedia. His results suggest that most particular entries are the work of separate contributions by a small number of people, rather than the efforts of an ongoing community. The cool thing is that it is a systematic study of all Wikipedia entries and histories.
Abstract: Wikipedia stands as an undeniable success in online participation and collaboration. However, previous attempts at studying collaboration within Wikipedia have focused on simple metrics like rigor (i.e., the number of revisions in an article’s revision history) and diversity (i.e., the number of authors that have contributed to a given article) or have made generalizations about collaboration within Wikipedia based upon the content validity of a few select articles. By looking more closely at metrics associated with each extant Wikipedia article (N=3,427,236) along with all revisions (N=225,226,370), this study attempts to understand what collaboration within Wikipedia actually looks like under the surface. Findings suggest that typical Wikipedia articles are not rigorous, in a collaborative sense, and do not reflect much diversity in the construction of content and macro–structural writing, leading to the conclusion that most articles in Wikipedia are not reflective of the collaborative efforts of the community but, rather, represent the work of relatively few contributors.

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Carving up the words 
I have just sent off the final manuscript for my book, Carving up the world: Scientific enquiry and natural kinds. It has been about a year since I completed the first complete draft of the book. I was under contract to deliver it by February, but it had reached a point where I just wanted it out of my hands.

UPDATE: Here's the picture that I mention in the comments.

Photo by Joost J. Bakker.

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Another digit in the googleplex 
Google Scholar has now added author pages, in addition to indiscriminate academic search. It has to be set up manually, but an author can distinguish themselves from other scholars who just happen to have the same name. This is handy for me, because - although I have managed to eclipse the doctor P.D. Magnus who writes about breast feeding - I still lag behind the chemist P.D. Magnus who writes about sulfone chemistry.

[link] My Google Scholar page

As most scholars do, I occasionally check to see how widely I am cited. The new page not only puts that all in one place, it also calculates aggregate impact scores.

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Two drafts posted 
I posted two drafts to my website today. As always, comments are welcome.

No grist for Mill on natural kinds, a paper in which I analyze some data

According to the standard narrative, natural kind is a technical notion that was introduced by John Stuart Mill in the 1840s and the recent craze for natural kinds, launched by Putnam and Kripke, is a continuation of that tradition. I argue that the standard narrative is mistaken. The Millian tradition of kinds was not particularly influential in the 20th-century, and the Putnam-Kripke revolution did not clearly engage with even the remnants that were left of it. The presently active tradition of natural kinds is less than half a century old. Recognizing this might help us better appreciate both Mill and natural kinds.

Why novel prediction matters, a paper coauthored with Heather Douglas

It has become commonplace to say that novel predictive success is not epistemically special. Its value over accommodation, if it has any, is taken to be superficial or derivative. We argue that the value of predictive success is indeed instrumental. Nevertheless, it is a powerful instrument that provides significant epistemic assurances at many different levels. Even though these assurances are in principle dispensable, real science is rarely (if ever) in the position to confidently obtain them in other ways. So we argue for a pluralist instrumental predictivism: novel predictive success is important for inferences from data to phenomena, from phenomena to theories, and from theories to frameworks. Ignoring it would deprive science of a crucial tool.

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Knobe or not Knobe, that is the question 
A few weeks ago, I did an exercise in my intro course in which students read descriptions of two scenarios, answered some multiple choice questions individually. They then discussed their answers in groups, and we discussed them as a class.
Morton is a physicist working on a the properties of particular semiconductors. He is interested in this as a scientific problem and is only studying it because of its theoretical significance.
Yet the only obvious applications are in alternative energy. Ultimately, his research is used to develop solar technology, and the technology is used to produce power in ways that produce significantly less pollution than other methods would have done.

Marsha is a chemist working on a class of interesting synthesis problems. She is interested in this as a scientific problem and is only studying it because of its theoretical significance.
Yet the only obvious applications are military. Ultimately, her research is used to develop weapons, and the weapons are used to commit atrocities which probably would not have been committed without those weapons.

Just one of these two cases would have been enough for the topic we had read about, which was whether scientific significance can really be insulated from practical significance. I juxtaposed of the two cases, though, because the paradigm case for experimental philosophy. I was curious.

One of the things I asked was whether Morton deserves any credit for the reduction in pollution and whether Marsha deserves any blame for the deaths. Standard ethical theory suggests that the answers should be symmetrical: either both deserve credit/blame or neither do. The Knobe effect (named for Joshua Knobe) suggests that students should blame Marsha but refuse to credit Morton.

As a matter of fact, neither of those things happened. Most students answered asymmetrically. Of those, most were willing to give some credit to Morton but unwilling to blame Marsha.

I do not have anything systematic to say about this. I did not collect precise numbers, since it was a pedagogical exercise rather than an experimental one. (We discussed human subjects protections in the same class session, and I commented that I couldn't use the results in a paper even if I had recorded them.) The discussion also revealed that responses were shaped by the details of how the scenarios and questions were worded. For example, one student did not want to blame Marsha for atrocities but would have blamed her for more quotidian deaths.

Nevertheless, I wonder whether it matters that the actors in these scenarios are scientists whereas the actors in Knobe's original cases were businessmen.

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