Measuring Causal Invariance Formally
Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, il...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/23/6/690 |
| _version_ | 1827691096230068224 |
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| author | Pierrick Bourrat |
| author_facet | Pierrick Bourrat |
| author_sort | Pierrick Bourrat |
| collection | DOAJ |
| description | Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how invariance could be qualified for such variables. |
| first_indexed | 2024-03-10T10:54:00Z |
| format | Article |
| id | doaj.art-c293cc1c27bc42da8c46087b474799fb |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T10:54:00Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-c293cc1c27bc42da8c46087b474799fb2023-11-21T22:03:54ZengMDPI AGEntropy1099-43002021-05-0123669010.3390/e23060690Measuring Causal Invariance FormallyPierrick Bourrat0Department of Philosophy, Macquarie University, Balaclava Road, North Ryde, NSW 2109, AustraliaInvariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how invariance could be qualified for such variables.https://www.mdpi.com/1099-4300/23/6/690causationinvariancecausal specificityinformation theory |
| spellingShingle | Pierrick Bourrat Measuring Causal Invariance Formally Entropy causation invariance causal specificity information theory |
| title | Measuring Causal Invariance Formally |
| title_full | Measuring Causal Invariance Formally |
| title_fullStr | Measuring Causal Invariance Formally |
| title_full_unstemmed | Measuring Causal Invariance Formally |
| title_short | Measuring Causal Invariance Formally |
| title_sort | measuring causal invariance formally |
| topic | causation invariance causal specificity information theory |
| url | https://www.mdpi.com/1099-4300/23/6/690 |
| work_keys_str_mv | AT pierrickbourrat measuringcausalinvarianceformally |