<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The advantage of examining causality from the perspective of modelling is thus that it puts us naturally closer to the practice of the sciences. This means being able to set up an interdisciplinary dialogue that contrasts and compares modelling practices in different fields, say economics and biology, medicine and statistics, climate change and physics. It also means that it helps philosophers looking for questions that go beyond the narrow ‘what-is-causality’ or ‘what-are-relata’ and thus puts causality right at the centre of a complex crossroad: epistemology/methodology, metaphysics, politics/ethics. This special issue collects nine papers that touch upon various scientific fields, from system biology to medicine to quantum mechanics to economics, and different questions, from explanation and prediction to the role of both true and false assumptions in modelling.</p></abstract>

The advantage of examining causality from the perspective of modelling is thus that it puts us naturally closer to the practice of the sciences. This means being able to set up an interdisciplinary dialogue that contrasts and compares modelling practices in different fields, say economics and biology, medicine and statistics, climate change and physics. It also means that it helps philosophers looking for questions that go beyond the narrow ‘what-is-causality’ or ‘what-are-relata’ and thus puts causality right at the centre of a complex crossroad: epistemology/methodology, metaphysics, politics/ethics. This special issue collects nine papers that touch upon various scientific fields, from system biology to medicine to quantum mechanics to economics, and different questions, from explanation and prediction to the role of both true and false assumptions in modelling.

Causality and Modelling in the Sciences: Introduction

Universidad Nacional de Educación a Distancia

Disputatio

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Causality and Modelling in the Sciences: Introduction"}

The advantage of examining causality from the perspective of modelling is thus that it puts us naturally closer to the practice of the sciences. This means...

Causality and Modelling in the Sciences: Introduction

Publié en ligne: 16 oct. 2018

Pages: 423 - 427

Reçu: 05 sept. 2017

Accepté: 02 nov. 2017

DOI: https://doi.org/10.1515/disp-2017-0013

Mots clés
Causality, modelling, causal explanation, scientific models

© 2017 María Jiménez-Buedo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Causality and Modelling in the Sciences: Introduction

Publié en ligne: 16 oct. 2018

Pages: 423 - 427

Reçu: 05 sept. 2017

Accepté: 02 nov. 2017

DOI: https://doi.org/10.1515/disp-2017-0013

Mots clésCausality, modelling, causal explanation, scientific models

© 2017 María Jiménez-Buedo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Causality, modelling, causal explanation, scientific models