Organisation: Zhitao Zhang & Alexander Gebharter
Time: 15:50 – 19:30, September 4, 2025
In philosophy of science, causality has become an increasingly popular topic. Many scientific claims and laws are stated in causal terms. For example, we say that a solar storm caused signal jamming. Though the laws of electromagnetism can be used to explain this phenomenon, it is usually the causal relation on which our actions are based—we monitor the solar activities because we know that solar storms can cause signal jamming (whatever the exact mechanism). On the other hand, causal relations are different from logical and statistical relations. Inference about causal relations is usually more complex and requires more specific background assumptions. Causality is deeply connected to other concepts such as correlation and manipulation. The discussions about causality and causal inference in science encompass diverse perspectives. This workshop’s focus lies on the intersection of metaphysics and methodology. Exemplary questions to be addressed are:
- How should we understand and conceptualize causality?
- Which properties of the causal relation are relevant for science?
- To what extend do contemporary methods for causal inference track the metaphysical concept of causality and under which conditions do they succeed?
For further information see the conference website: https://sophia-conference.org/
Speakers:
- Elisa D’Olimpio (CPSP, Marche Polytechnic University)
- Sepehr Ehsani (University College London)
- Alexander Gebharter (CPSP, Marche Polytechnic University)
- Stavros Ioannidis (National and Kapodistrian University of Athens)
- Barbara Osimani (CPSP, Marche Polytechnic University)
- Stathis Psillos (National and Kapodistrian University of Athens)
- Julian Reiss (University of Linz)
- Michał Sikorski (CPSP, Marche Polytechnic University)
- Zhitao Zhang (University College London)
Program:
| Time | Room SR 1.004 |
| 15:50 | Opening |
| 16:00 | Talk 1 |
| 16:35 | Talk 2 |
| 17:10 | Break |
| 17:20 | Talk 3 |
| 17:55 | Talk 3 |
| 18:30 | Break |
| 18:40 | Talk 5 |
| 19:15 | Closing |
Titles & Abstracts:
Sepehr Ehsani: Causal inferences from mechanistic and law-based models in cell biology
In the field of cell biology, as with other allied sciences such as organic chemistry or ecology, investigators seek to provide a causal story of a phenomenon of interest. This causal story, in cell biology, is almost exclusively in the form of mechanistic explanations. There are various reasons for this exclusive focus on mechanisms, and while this type of explanation has had many successes, it also faces various challenges. A proposal, named ‘principled mechanism’ (or ‘mechanism-plus-X’ as previously known), has been advanced in the past several years to set up a framework in which mechanistic explanations could be augmented withlawlike generalizations (i.e. lawlike generalizations that would be specific to and operative at the cell-biological level), somewhat akin to how mechanistic explanations are augmented with organic-chemistry-operative generalizations (e.g. permutations of thermodynamic laws) in organic chemistry. Although no generalizations on par with thermodynamics are currently known in cell biology, there is nevertheless a scattering of known lawlike generalizations specific to explaining cellular phenomena, and a program for discovering further such generalizations is being developed. This talk concerns the steps that come after. Specifically, there has been much discussion in the contemporary philosophy of science literature about mechanism discovery, modelling and causal inference. But how would these work when we have a lawlike generalization in place? Can we create a ‘model’ of a lawlike generalization in isolation and then infer a causal story from it, and what about when the lawlike generalization is combined with a mechanism in a ‘principled mechanistic’ explanation? These are some preliminary questions in the burgeoning area of principled mechanistic explanations, and I hope to discuss some initial thoughts in the talk.
Alexander Gebharter, Barbara Osimani, Michał Sikorski, Elisa D’Olimpio, & Zhitao Zhang: A causal account for estimating effects across populations
when no causal information is available
The question of how experimental results obtained in a study population can be used to estimate causal effects in a target population is key in science and evidence-based decision making. This task becomes especially challenging in the presence of heterogeneity, i.e., when the values of some variables are distributed significantly differently among individuals in the two populations. In this paper, we develop an account for effect estimation across populations that combines causal models and Jeffrey conditionalization. We formulate a criterion for empirically testing whether the effect of an intervention in the target population can be estimated from experimental results obtained in the study population and argue that causal effects in the target population can be estimated without any prior knowledge of the underlying causal structure if the criterion is satisfied. This is a major advantage of the approach, as obtaining causal information is often difficult, particularly in policy-making contexts.
Stavros Ioannidis & Stathis Psillos: TBA
TBA
Julian Reiss: Great Causatives Have Great Consequences
Since Elizabeth Anscombe’s inaugural lecture at Cambridge University, it has been well known among philosophers that natural languages provide multiple ways to express causal relationships other than ‘cause’ and its closest cognates such as ‘causes’, ‘causing’ etc. Anscombe’s ‘small selection’ of so-called ‘causatives’ (words that express causal relationships) was: “scrape, push, wet, carry, eat, bum, knock over, keep off, squash, make (e.g. noises, paper boats), hurt”. Though well known, the consequences of this circumstance are still underappreciated. The main goal of this paper is to discuss a number of philosophically significant consequences of the grammar of causatives. Among other things, there is no fully generic causative, one that expresses nothing but ’the’ abstract causal relationship. Even ‘cause’ itself has a number of more specific implications not shared by other causatives. ‘Make’ is sometimes described as the prototypical causative (and not ‘cause’!), but even ‘make’ has connotations that aren’t shared by other causatives. Natural languages allow of different mechanisms to construct causative phrases. Anscombe’s list contains ‘lexical’ causatives where the idea of causation is built into the semantics of the verb itself. ‘Morphological’ causatives turn a verb into one that expresses causing by adding a prefix or suffix or other kind of change to the word stem. They exist in English only as remnants of Germanic construction in word pairs such as lie/lay, sit/seat, fall/fell. ‘Analytical’ causatives add a verb clause to the main verb: the child burped vs the father made the child burp. Which verb clause is used has important consequences for the meaning of the whole phrase, cf. she forced him to take the poison vs she let him take the poison. The paper concludes with a discussion of the consequences of these facts for philosophical ideas about causation.
Zhitao Zhang: TBA
TBA
Project funded under the National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.1 — Call for tender No. 1409/2022 of 14/09/2022 of the Italian Ministry of University and Research funded by the European Union – NextGenerationEU. Award Number: P2022RT4AT_001, Concession Decree No. 1371 of 01/09/2023 adopted by the Italian Ministry of University and Research, CUP I53D23006890001, Controlling and Utilizing Uncertainty in the Health Sciences.