Réseau Montréalais de Philo des Sciences/Mtl Philosophy of Science Network

Réseau Montréalais de Philo des Sciences/Mtl Philosophy of Science Network Réseau Montréalais de philosophie des sciences / Montréal Philosophy of Science Network

Le réseau stimule la réflexion et la recherche en philosophie des sciences à Montréal. Il réunit des professeurs, des chercheurs et des étudiants de la région montréalaise pour discuter de travaux en cours et de pistes de recherche, notamment autour de conférences données par des chercheurs de passage à Montréal. Les rencontres se tiennent en alternance aux départements de philosophie de l’Univers

ité du Québec à Montréal (Chaire de recherche du Canada en philosophie des sciences de la vie), de l’Université de Montréal, de Concordia University et de McGill University, en synergie avec le Centre interuniversitaire de recherche sur la science et la technologie (CIRST). The network stimulates thinking and research in philosophy of science in Montréal. It gathers professors, researchers, and students of the broader Montreal region to discuss work in progress and avenues for research, in particular in conjunction with talks given by scholars traveling through Montréal. The meetings take place alternately at the philosophy departments of the Université du Québec à Montréal (Canada Research Chair in philosophy of the life sciences), Université de Montréal, Concordia University, and McGill University, in synergy with the Centre interuniversitaire de recherche sur la science et la technologie (CIRST).

New talk coming up soon: Naftali Weinberger (LMU Munich), "Three Myths About Causal Mediation". Friday, September 15th, ...
09/05/2023

New talk coming up soon: Naftali Weinberger (LMU Munich), "Three Myths About Causal Mediation". Friday, September 15th, 3:30 – 4:30pm, McGill University, Burnside Hall 1104.

https://montrealphilscinet.wordpress.com/activites-activities/

Abstract: Causal mediation techniques are a means for identifying the degree to which a cause influences its effect along particular causal paths. For example, in a model where a cause influences its effect both indirectly via a mediator and directly via factors not included in the model, mediation techniques enable one to measure both direct and indirect effects. Although mediation techniques are widely employed, they are often misunderstood. This is in part due to the long-term influence of Baron and Kenny’s (1986) treatment of mediation, which applies only to linear models without interaction, and which leads one to develop intuitions about direct and indirect effects that do not generalize to non-parametric causal models. In my talk, I identify and reject three persistent myths about mediation. I argue that such methods: 1. Should not be understood as decomposing the total effect into additive components corresponding to the contributions of the paths; 2. Are not a means for eliminating latent heterogeneity; and 3. Do not require one to appeal to causal concepts other than the counterfactual causal ones built into structural causal models. These points are crucial for understanding mediation effects in any contexts in which they are studied, and have particular applications for studies of fairness and discrimination, in which such effects play an increasingly central role (Plečko and Bareinboim, 2022).

This talk is co-sponsored with the Mathematics and Philosophy departments at McGill.

We are proud to host Stephan Hartmann (LMU) at McGill next week!Bayesian ExplanationismStephan Hartmann, Munich Center f...
09/19/2022

We are proud to host Stephan Hartmann (LMU) at McGill next week!

Bayesian Explanationism

Stephan Hartmann, Munich Center for Mathematical Philosophy, LMU Munich

Thursday September 29th, 2022, 5-7pm

Hybrid event: in person and online

In person: McGill University, Leacock 927

Online participation: please visit the Montreal Philosophy of Science Network website for the Zoom link: https://montrealphilscinet.wordpress.com/activites-activities/

Abstract: Peter Lipton famously argued that we want our scientific theories to be lovely and likely, that is, we want them to provide good explanations and to be very probable (if not true). Unfortunately, there is a tension between these two epistemic virtues, and it is not clear how they are related. Thus, the question arises whether the Bayesian (who prefers likely theories) and the explanationist (who prefers lovely theories) can be friends, as Lipton claims. Although much ink has been spilled over this question, in this talk I want to take a fresh look at it and make two points: First, I argue that successfully providing an explanation is an example of non-empirical evidence in favor of the theory in question. This point can be made more precise by a simple Bayesian model, which also provides (as a bonus point, so to speak) a justification for the bonus point approach to explanationism inspired by van Fraassen and championed by Douven – at least if certain conditions are met. Second, I investigate how the strength of an explanation – its explanatory power – can be measured in Bayesian terms, and show how this all fits nicely into a coherentist epistemology of science.

Vous avez manqué les conférences d'Elliot Sober à l'UQAM? Pas de problème : voici les enregistrements!You missed the Ell...
04/27/2021

Vous avez manqué les conférences d'Elliot Sober à l'UQAM? Pas de problème : voici les enregistrements!
You missed the Elliot Sober conferences held at UQAM? We've got your back: here are the recordings!

Vidéo Audio Résumé « Ockham’s Razor » Mercredi 14 avril, 15h30-17h00Commentatrice // commentator: Molly Kao (Université de Montréal) Ockham’s razor says that simpler theories are better than theories that are more complex, but what does “better” mean?  The question isn’t ...

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