Causal Conditionals, Tendency Causal Claims and Statistical Relevance

Sikorski, Michal; Dongen, Noah van; Sprenger, Jan

doi:10.31234/osf.io/t3fud

Cited by 1 publication

(1 citation statement)

References 38 publications

(29 reference statements)

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“…Whereas other studies have investigated indicative conditionals and singular causation judgments in the same experiment (e.g., Sikorski et al, 2019), we decided to additionally have participants provide counterfactual conditionals and causal power judgments. To investigate the relationship between mechanistic knowledge, causality, conditionals, and contingency, a large online study was therefore conducted with 32 between-subjects conditions that factorially varied these factors.…”

Section: Methodsmentioning

confidence: 99%

Conditionals and the hierarchy of causal queries.

Skovgaard-Olsen¹,

Stephan²,

Waldmann³

2021

Journal of Experimental Psychology: General

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Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent.According to Pearl ( 2009), understanding a causal relation involves multiple, hierarchically organized conceptual dimensions: prediction, intervention, and counterfactual dependence. In a series of experiments, we test the hypothesis that these conceptual dimensions are differentially encoded in indicative and counterfactual conditionals. If this hypothesis holds, then there are limits as to how much of a causal relation is captured by indicative conditionals alone. Our results show that the acceptance of indicative and counterfactual conditionals can become dissociated. Furthermore, it is found that the acceptance of both is needed for accepting a causal relation between two co-occurring events. The implications that these findings have for the hypothesis above, and for recent debates at the intersection of the psychology of reasoning and causal judgment, are critically discussed. Our findings are consistent with viewing indicative conditionals as answering predictive queries requiring evidential relevance (even in the absence of direct causal relations). Counterfactual conditionals in contrast target causal relevance, specifically. Finally, we discuss the implications our results have for the yet unsolved question of how reasoners succeed in constructing causal models from verbal descriptions.

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Section: Methodsmentioning

confidence: 99%