Mainz Colloquium for History and Philosophy of Science / Mainzer Kolloquium für Geschichte und Philosophie der Wissenschaft

 

The Mainz Colloquium for History and Philosophy of Science is jointly organized by the Department of Philosophy, the research group in History of Mathematics and Natural Sciences at the Institute of Mathematics, and the Studium generale.

Conveners: Ralf Busse (Department of Philosophy), Meinard Kuhlmann (Department of Philosophy), Cornelis Menke (Studium generale and Department of Philosophy), and Tilman Sauer (Institute of Mathematics)

Email list: On the foot of the page, you can subscribe to the announcement list of the Mainz Colloquium.

 

Einstein-Zitat (1916), Fassade Johann-Joachim-Becher-Weg 14, Campus JGU Mainz. Foto Privat
Einstein quote (1916). Face of Building J, Johann-Joachim-Becher-Weg 14, Mainz University. Foto Privat

 

Winter semester 2021/2022

Alexander Blum (Berlin),  t.b.d.

27 October 2021, 6pm

 

 

Ralf Busse & Meinard Kuhlmann (Mainz University),  t.b.d.

17 November 2021, 6pm

 

 

Hanne Andersen (University of Copenhagen),  t.b.d.

12 January 2022, 6pm

 

 

Summer semester 2021

All events will take place online.
As a member of Mainz University, please register at the colloquium's Moodle page: https://lms.uni-mainz.de/moodle/course/view.php?id=40630. Otherwise, please write the conveners to register.

 

Till Grüne-Yanoff (Royal Institute of Technology, Stockholm): “KISS in the Times of Pandemic: Different Modelling Approaches to COVID-19”

19 May 2021

 

Talk cancelled:  Hanne Andersen (University of Copenhagen): “Learning from the past in developing machine learning for the future”

Wednesday, 23 June 2021. We will try to reschedule for a later date.

Abstract: Machine learning is being applied to more and more topics in human life. Howev-er, as the use of machine learning is becoming more and more widespread, there is also a growing concern about the possible negative implications of this development, especially with respect to high-stake decisions regarding individuals. This has spurred a rapidly growing literature on how to develop machine learning responsibly. In much of this literature, issues such as bias, fairness, and explanatory transparency are addressed primarily as ethical issues and as challenges derived from the emergence and development of machine learning. However, first, in dealing with these issues, ethics is closely intertwined with epistemology. Second, although the importance of the challenges may have been amplified by the rapid development of machine learning and algorithmic decision systems, they are not necessarily new concerns. Instead, many of the challenges derive from well-known epistemic and ethical issues related to decision-making under uncertainty. In this talk, I shall provide a brief overview of some major strands in these debates and on this background discuss where the use of machine learning amplifies problems already known, and where it creates new issues that need to be resolved.

 

Wendy Parker (Virginia Tech): “Relocating value influence in science”

7 July 2021

Abstract: Should social and political values influence how scientists choose among models, analyze data and reach conclusions? According to the “value-free ideal” for science, they should not. Recently, however, a number of philosophers have argued that such value influence can be entirely appropriate. I will suggest that the responsiveness to values that these philosophers find appropriate can be relocated within the research process, in a way that not only preserves the value-free ideal but may be more comfortable for scientists as well. I call this approach to accommodating value considerations the “epistemic projection approach”.

Simultaneously part of the Kolloquium des Philosophischen Seminars.

 

Winter semester 2020/2021

Uljana Feest (Leibniz-Universität Hannover): “Kognitive Ontologie”

18 November 2020

Simultaneously part of the Colloquium for Philosophy / Zugleich Vortrag im Kolloquium des Philosophischen Seminars (Programm/PDF)

Abstract: Folk-Psychological Concepts, Cognitive Kinds, and Investigative Practice. – When psychologists investigate their objects of research, such as (kinds of) memory, they operate with concepts that are typically derived from folk-psychology but which are – for the purposes of research – tied to specific material-conceptual set-ups, also known as experimental designs. In this vein, researchers tentatively define their concepts in terms of particular experimental tests/tasks, assumed to provide epistemic access to the “objects” in question. But what is the ontological status of such objects? Are they cognitive kinds? And if so, what kinds of things are cognitive kinds? In my paper I will argue that cognitive kinds are cognitive-behavioral whole-organism capacities, which are comprised of multiple phenomena, including (but not limited to) behavioral phenomena. With this I depart from the assumption that the behavioral criteria by which cognitive kinds are empirically individuated are mere epistemic vehicles that aid in the investigation of cognitive kinds. Rather, they are part of what it is to be such a kind. While I take cognitive kinds to be sustained by structural features in the world, I argue that they are not uniquely determined by neural mechanisms. My account of cognitive kinds is relational in that I claim that cognitive kinds are constituted relative to our sensory-conceptual apparatus and maintained by our conceptual and causal practices surrounding cognitive kinds. In turn, I argue that researchers take advantage of the relational character of their subject matter as they utilize existing concepts and fine-tune their conceptual apparatus

 

Andrea Loettgers (Universität Wien): “Organizationsprinzipien in der Biologie”

9 December 2020

Abstract: Scientists constructing models out of genes and proteins aim to explore basic organizational principles in biology. At the same time such material models are supposed to provide the possibility to engineer new biological parts of even whole systems. Are those epistemic and engineering goals compatible? What kind of explanations can be gained by this material model?

 

Dennis Lehmkuhl (Universität Bonn): “Einstein on Spacetime Geometry”

20 January 2021

Abstract: Einstein actively opposed the idea that the general theory of relativity (GR) should be interpreted as reducing the gravitational field to the geometry of spacetime. However, he also regularly pointed out that the metric tensor of general relativity gives a measure of the distance between any two spacetime points and is connected to the measurements of rods and clocks. How do these opinions fit, and how did they come to co-exist in Einstein’s interpretation of GR? I propose that an important hint to this lies in Einstein’s work on a relativistic theory of gravity before he ever represented gravity by a metric tensor. Thus, I will review and give a new analysis of Einstein’s work on a scalar theory of gravity in 1911 and 1912, taking into account the discussion surrounding the concept of a rigid body in relativity theory in the works of Born, Ehrenfest and von Laue in the years preceding Einstein’s scalar theory, and Einstein’s correspondence on the issue between 1909 and 1911.

 

Summer semester 2020

All talks during the summer semester 2020 had to be cancelled. / Im Sommersemester 2020 ist das Mainzer Kolloquium ausgefallen.

 

Winter semester 2019/2020

Cornelis Menke (Universität Mainz): “P < .05 – Ronald Fischer als Pragmatist”

6 November 2019

Simultaneously part of the Colloquium for Philosophy / Zugleich Vortrag im Kolloquium des Philosophischen Seminars

Abstract: Das in vielen Forschungsfeldern etablierte Signifikanzniveau von 5% bei statistischen Tests ist erklärungsbedürftig. Nach der Standard-Auffassung ist es ein eigentlich willkürlicher Grenzwert, der -- im Sinne von Neyman-Pearson-Entscheidungsverfahren -- als Fehlerhäufigkeit interpretiert werden sollte. Dies ist befremdlich, denn der Grenzwert ist älter als diese Entscheidungsverfahren und die Interpretation statistischer Tests, mit denen sie einhergehen, und ein festes Niveau für Fehlerhäufigkeiten ist diesen Verfahren eigentlich fremd. Die These des Vortrags ist, dass das .05-"limit of significance", das auf Ronald Fisher zurückgeht, bei Fisher aber eine gänzlich andere Funktion hat und, in dieser Funktion, auch kein willkürlicher Grenzwert ist.

 

Marie I. Kaiser (Universität Bielefeld): “”How Biologists Study Animal Personalities”

4 December 2019

 

Giora Hon (University of Haifa): “James Clerk Maxwell’s Methodological Odyssey in Electromagnetism: A Philosophical Perspective”

29 January 2020

Simultaneously part of the Oberseminar zur Geschichte der Mathematik und der Naturwissenschaften

Abstract: Einstein (1931): “The greatest alteration in the axiomatic basis of physics – in our conception of the structure of reality – since the foundation of theoretical physics by Newton, originated in the researches of Faraday and Maxwell on electromagnetic phenomena... Since Maxwell’s time Physical Reality has been thought of as represented by continuous fields, governed by partial differential equations, and not capable of any mechanical interpretation. This change in the conception of Reality is the most profound and fruitful that physics has experienced since the time of Newton.”

We ask, then, What was Maxwell’s key to this fundamental change in the conception of Physical Reality? By following closely the trajectory of Maxwell’s several contributions to electromagnetism, which we characterize as an odyssey, we uncover one fundamental aspect of this success – innovative methodologies.

 

Mainz Colloquium email list

 

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