Big data are getting a popular and fashionable topic in philosophy of science, and for a number of good reasons. One reason, I think, is that big data practices in the social sciences push us to rethink the notion of objectivity. At least, this is the line of argument I’m trying to develop with Jean-Christophe Plantin.
… or why mentoring young academics, whether women or men? And what to tell them? There’s quite a lot of material and discussion on the topic. Just google, you’ll find out.
So, a quick reflection on what I did today. I’ve been invited to lead a workshop on how to get your paper published, as part of a the Conference by Women in Philosophy 3# , organised entirely by MA and PhD students from the University of Amsterdam and the Free University of Amsterdam. Kudos to the Ladies there, they have done a great job!
What you’ll find in the slides is probably all known to you. Or perhaps not all. There are a few of things that I’d like to emphasise. First, we’d better publish papers with positive results, rather than just negative results. Second, we’d better write referee reports that are constructive, rather than just destructive. Third, none of our results is just ‘ours’ so we’d better do things collegially, at all stages of the publishing process.
This is the way I try to train my students in writing papers and in raising points for discussion at seminars. This is the way I try to write my papers and referee reports. This is the way I try to carry out editorial work.
This is not independent from a certain meta-philosophical stance that I tried to develop lately and that I presented at some conferences recently (more info to follow soon). And not even this is just my own idea, but the result of years of collaborations with a several people, especially my friend and colleague Phyllis Illari.
And now, go enjoy philosophy!
The epistemological relations between science and technology are a relatively under-explored topic. I started thinking about these issues a while ago, prompted by the practice of an emerging area of research: exposomics, or the science of exposure. (See e.g. this project.)
I presented some sketchy thoughts at SPT in Lisbon in 2013, and here is where my thinking on this issue is leading to. Still a lot of work to do before I can have some papers, but there we go.
Brendan Clarke, Donald Gillies, Phyllis Illari, Federica Russo, Jon Williamson
Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM.
Causality in the Sciences
Phyllis Illari, Federica Russo, Jon Williamson (editors)
Oxford University Press
L. Casini, P. Illari, F. Russo, J. Williamson