Proof and Uncertainty in Causal Claims
DOI:
https://doi.org/10.31273/eirj.v5i2.238Abstract
Causal questions drive scientific enquiry. From Hume to Granger, and Rubin to Pearl the history of science is full of examples of scientists testing new theories in an effort to uncover causal mechanisms. The difficulty of drawing causal conclusions from observational data has prompted developments in new methodologies, most notably in the area of graphical models. We explore the relationship between existing theories about causal mechanisms in a social science domain, new mathematical and statistical modelling methods, the role of mathematical proof and the importance of accounting for uncertainty. We show that, while the mathematical sciences rely on their modelling assumptions, dialogue with the social sciences calls for continual extension of these models. We show how changing model assumptions lead to innovative causal structures and more nuanced casual explanations. We review differing techniques for determining cause in different disciplines using causal theories from psychology, medicine, and economics.
Downloads
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC-BY), which permits use and redistribution of the work provided that the original author and source are credited, a link to the license is included, and an indication of changes which were made. Third-party users may not apply legal terms or technological measures to the published article which legally restrict others from doing anything the license permits.
If accepted for publication authors’ work will be made open access and distributed under a Creative Commons Attribution (CC-BY) license unless previously agreed with Exchanges’ Editor-in-Chief prior to submission.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. (see: The Effect of Open Access)