The document discusses methodological and evidential pluralism in causal modeling and argues that despite pluralism in methods and evidence, there is a single underlying rationale of variation. Specifically: 1) While causal modeling uses various methods and evidence, it is guided by a single rationale when reasoning about cause-effect relationships - the rationale of variation. 2) Variation underlies model building and testing and serves as a precondition to notions like regularity and invariance. 3) Regularity and invariance play constrained roles by ruling out accidental variations and granting causal interpretation, but the core rationale is variation.

1. The rationale of variation in methodological and evidential pluralism Federica Russo Philosophy, Kent

2. Overview This work: Metaphysics, epistemology, methodology of causality Domain; interest; objective The question: What rationale in building & testing causal models? Methodological and evidential pluralism Epistemological monism: the rationale of variation A taste of methodological arguments: Structural equations A taste of possible objections: Regularity; Invariance

3. Philosophy of causality Metaphysics What causality/cause is Epistemology How do we know about causal relations Methodology Develop/implement methods for discovery/confirmation of causal relations

4. This work Epistemology of causality Domain quantitative social science Interest causal reasoning in causal modelling Objective dig out a neglected notion in the philosophy of causality: variation

5. The guiding question When we reason about cause-effect relations in causal modelling, what notion guides this reasoning? Regularity? Invariance? Production? ... Hunting for a rationale

6. Rationale vs. definition Rationale: a principle/notion/concept underlying decision/reasoning/modelling Definition: A description of a thing by means of its properties or if its function Here: hunt for the notion underlying model building and model testing: rationale, not definition

7. Methodological pluralism Structural equation models Covariance structure models Multilevel models Contingency tables …

8. Evidential pluralism Causal modelling uses multi-fold evidence / information Data Surveys, censuses, experiments, interviews, … Evidence of established causal relations Previous studies, background knowledge, known mechanisms and probabilistic relations, …

9. Do methodological and evidential pluralism entail epistemological pluralism?

10. Causal modelling is regimented by a single rationale in model building and testing: the rationale of variation

11. Arguments Empirical: Look at informal reasoning in case studies Methodological: Look at rationale of model building & testing in various causal models Philosophical: Look at arguments given by other philosophers Foundational: Look at forefathers of causal modelling Compatibility: Look at various established philosophical accounts

12. A taste of methodological arguments Consider a structural equation Y =  X+  Variations in X accompany  -unit variations in Y Are those variations chancy or causal? hypothesis testing; invariance; exogeneity

13. Therefore… Variation is a pre condition with respect to other notions E.g.: regularity, invariance Any role left to those? Yes – constraints : Regularity: often enough Invariance: stability of parameters Rule out accidental and spurious variations, Grant causal interpretation of variations

14. A taste of objections Regularity Mine is just a reformulation of regularity theory Only partly true Regularity is more basic. Not quite: regularity of what? Invariance Invariance is more basic. Not quite: invariance of what?

15. To sum up and conclude Causal modelling in social sciences Takes advantage of different methods Uses multi-fold information and evidence Does it follow that model building and model testing are regimented by different rationales ? No. Causal reasoning in all causal models are built and tested according to the rationale of variation Regularity and invariance are constraints on the causal relation

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