What’s wrong with (just) showing other people wrong

In a recent tweet, I expressed frustration with the following situation. Academic publications, especially in philosophy, are replete with arguments that aim to show that Author X is wrong, paper Y fails in this and that, the Literature doesn’t achieve much. The phenomenon is macroscopic. I observe it as editor, as reviewer, as reader, and also as a teacher / examiner / supervisor. You can see the twitter thread here.

There are a number of reasons why I think this is wrong and counterproductive. Let me elaborate.

In reading texts that spend most of their time and efforts in showing others wrong, I am frustrated and annoyed by the negative tone. They are boring to read. This, you may think, is an aesthetic issue. Sure, but there is more: your original and positive ideas are watered in negative comments about others. So it is detrimental to your own work.

But also, in spending so much time (all of your time?) in showing others wrong, you still don’t explain what the problem is, why should we care, and why it is relevant that Author X, Paper Y, the Literature hasn’t solved it.

Another issue is that, as the majority of our publications go through peer review, you are implicitly saying that the peer review failed to block this piece to get published. Actually, you have no idea of what happened behind the scenes, and it may be the case that the flaws you find in Paper Y are (also) due to changes to accommodate reviewers requests. Yes. That happens, and you don’t know. Of course peer review has its own share of problems, but that’s another discussion.

There is also a question of politeness. You really can’t keep saying that others are wrong. Each one of us deserves respect. We should express our ideas in a respectful way, and in return critical assessment ought to be respectful as well.

So what can you do instead of (just) showing that other people are wrong? Here is a (brief) positive and constructive proposal.

  • Shape your argument around a problem. What is the problem? Why does it matter? Why should we care?
  • Acknowledge others’ attempts to address it. Some attempts will be more successful than others. Sure. You have to be critical. But do acknowledge the struggle to address the problem. Do it for us, we will do it for you when discussing your paper.
  • Critical assessment doesn’t mean proving others wrong. It means to clarify what we achieved, what we didn’t, and what needs to be done next.
  • DO WHAT NEEDS TO BE DONE NEXT. This should be the most important part of your contribution. If there is a problem, and the problem is still there after other people tried to address it, DO something with it. It is too easy to criticize and not to give it a try.

Let me be clear: I don’t think the issue reduces to politeness and etiquette. What is really behind is how we conceive of knowledge. If we start (again?) to conceive of knowledge production as a collective enterprise, in which knowledge is distributed (embodied, etc.) then you will see why all of the above matters. (If you are unfamiliar with these ideas, go to the library, do some googling, you’ll see they exist.)

If you can afford writing a piece criticizing Author X, Paper Y, the Literature, well, you are building, directly or indirectly, on other people’s work. So you are not the lonely owner of your ideas, you have them also because they belong to a shared conceptual space. Next time, please acknowledge that something has been done.

Practice what you preach. I try to change these negative attitudes as much as I can. I care about these issues, I speak up, and I give advice in all of my academic roles: as editor, reviewer, author, examiner, teacher, …

Please join me in making philosophy a better place.

What’s interesting about big data?

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.

Why mentoring women in philosophy

… 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!

Mexican lectures: medicine, causal modelling, and causal pluralism


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Better late than never, here is a quick report on my brief visit to the Universidad Nacional Autónoma de México in April 2015 — a very kind invitation by Atocha Aliseda and Fernanda Samaniego. It has been an intense week, filled with marvellous discussions with colleagues and students at the Instituto de Investigaciones Filosóficas, meetings with good old friends from the Canterbury times, and even with some sightseeing — in Mexico City, I visited the Museo Interactivo de Economia and the Museo Nacional de Arte.

My Monday lecture was part of the Seminar on Logic and Heuristic organised by Atocha. The themes of their seminar is much broader than what the title suggests. I presented some ideas about philosophy of medicine, specifically how to understand medicine (as an umbrella term that includes several types of medical practices) and what kind of philosophy of science questions I consider interesting therein. Part of what I presented at the seminar is work in progress with Brendan Clarke.



On Tuesday I have a long lecture on causal modelling in the social sciences. This was part of an MA course on explanation, so the focus was what we can explain using causal models in social research, and how. I tried to condense much of what I know about causal modelling in these slides. A lot of what I presented is in my first monograph (Causality and Causal Modelling in the Social Sciences. Measuring Variations. Springer 2009) and in some more recent papers. Students asked plenty of questions — it has been a pleasure lecturing them!



Finally, my Wednesday talk was part of the seminar of the Institute: a broad and heterogeneous audience indeed! I presented what we might call causal pluralism 2.0. This is joint work with Phyllis Illari. Together we wrote a monograph on causality (Causality: Philosophical Theory Meets Scientific Practice, OUP 2014), the aim of which is to put some order in the vast philosophical literature on causation. Our goal, however, goes beyond offering just an introduction to causality. We also offer a view on how all these strands, pieces of the literature may (or should) stand together. We defend a qualified version of causal pluralism, that we explain in analogy with building a mosaic. More explanation in the slides below, and in chapters 23-24 of our book!



I’m so grateful to Atocha and Fernanda for the fantastic occasion to present my work, but mostly for their fantastic hospitality. They really made me feel home. I hope to go back some time soon!

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Venetian lectures: causality, modelling, computer science


In the middle of the UvA protest, of a flu, and of an intensive semester filled with teaching, I escaped to beautiful Venice — the Amsterdam of the South ! — to talk about various things, among which causality, modelling, and computer science.

I delivered the first lecture at the Department of Management of Ca’ Foscari. The talk is based on some joint work done with my friend and colleague Alessio Moneta. The idea of drawing a conceptual distinction between associational models and causal models is useful, we think, to improve on our modelling practices. However, in practice, the two are not so much separated.

The second lecture was part of Eleonora Montuschi‘s course Philosophy of the Social Sciences. She had asked me to give a presentation on causality. As usual, the big challenge is to give a sense of the beautiful complexity of the causality debate without scare people! I decided to focus on selected methodological and epistemological issues so that it would be a ‘natural’ follow up of the previous lecture.

The last day I took part in a workshop organised by Marcello Pelillo: Philosophical Aspects of Computer Science. We gather together to brainstorm about various ideas, approaches, questions, etc related to computer science and that we tackle in our own research. I have to admit that computer science does not exactly fall into my own area of expertise, and yet I discovered that I had a lot in common with them, and certainly many overlapping interests!

Science, technology, and the technoscience of exposure


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.

A session on history and philosophy of #interdisciplinarity at #hsspsa2014

The biennial meeting of the Philosophy of Science Association and the annual meeting of the History of Science Society took place in Chicago on 6-9 November 2014. Quite some interesting work has been presented there — let me just mention two sessions on the history of interdisciplinarity and on on the philosophy of interdisciplinarity (for the combined programme of the two meetings see here). I myself contributed to the second.

I presented a paper on the integration of social factors in the aetiology of diseases (especially non-communicable diseases). This is joint work with Mike Kelly and Rachel Kelly. Listen to this short interview of Mike and you’ll easily realise why it is important to reflect on what it means to have a mixed aetiology for disesases that are not ‘biologically communicable’ but are instead socially communicable (as it as been suggested in the Q&A after my talk). We argue in the paper that it is not sufficient to include socio-economic-behavioural factors in an epidemiological analysis, as mere ‘classificatory’ devices. These factors play an active role in aetiology and we need a concept of ‘mixed mechanism’ to account for that.

#Variation in #causal-modelling


I had the chance to take part in the conference of the Danish Philosophical Association in Aalborg, early March 2014. For the occasion, I decided to try out again the idea of ‘variational reasoning’ in causal modelling. If you haven’t came across it already, it is actually quite simple. One question concerning causal reasoning is what notion(s) guide model building and model testing. This is an epistemological question. My answer is that we reason around variations. In other words, without variations we cannot detect causes at all. Of course, detecting variations is not enough to establish causal relations, and that’s why we need to impose further constraints, for instance regularity or invariance. If it is so simple, why is it so important? My view is that it sheds light on important aspects of causal epistemology, and it helps putting other causal notions (e.g., manipulation, regularity, …) in the right place of the #causalmosaic.

If you want to know more, look at the presentation below, or read chapter 4 of my 2009 Springer book, or chapter 16 of the 2014 OUP book on causality (co-authored with Phyllis Illari).


Evidence hierarchies and mechanisms

This is the second talk I gave in Brazil, in October 2013, in occasion of the V Seminar on Technology Management and Innovation in Health, where epidemiologist Mauricio Barreto organised a round table on Evaluation of Health Impact of Technological Interventions. There, I presented work on EBM and evidence hierarchies (output of a joint project with Phyllis Illari, Brendan Clarke, Donald Gillies, Jon Williamson).

By the way, if you are interested, we also set up a blog, called EBM+!

On the concept of #invariance in social science #methodology

I was delighted to be invited to speak at the HPS department in Cambridge in November 2013. [I know it is a while ago, I’m catching up with stuff to put online.] The audience has been simply wonderful. Great questions, engaging and engaged, but not aggressive. Their questions helped me a lot  rephrasing bits of the paper that stems from this (and some others!) presentations on the concept of invariance.

I hope it is now clear (or clearer) that the objective of this paper is not to criticise the notion of ‘invariance under intervention’ just for the sake of finding black spots in a given account. I’m trying to solve a genuine problem in social science methodology, and more generally in observational studies. Oh, the paper is now out in International Studies in Philosophy of Science, with the following title: What Invariance Is and How to Test for It. If you cannot access it, email me and I’ll gladly send you a copy.