{'fraction_non_alphanumeric': 0.026143790849673203, 'fraction_numerical': 0.0032679738562091504, 'mean_word_length': 5.004901960784314, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Belief-based and covariation-based cues affect causal discounting.

Causal discounting occurs when the perceived efficacy of a putative cause is reduced by the presence of a stronger causal candidate. Previous studies of causal discounting have defined the strength of causal candidates in terms of the degree to which the cause and the effect covary (e.g., Baker, Mercier, Vallee-Tourangeau, Frank, & Pan, 1993). In contrast, in the present study, causal strength was defined in terms of both covariation- and belief-based cues. Seventy-two participants made causality judgments for a fictional causal candidate both in isolation and when paired with either a stronger or a weaker cause. The results demonstrated that the degree to which a causal candidate is discounted depends not only on the degree to which an alternative cause covaries with the effect, but also on whether the alternative is a believable or unbelievable candidate. Indeed, it was observed that a highly believable alternative will produce the discounting effect, even if it is a weaker covariate than the original candidate. These findings suggest the need to incorporate both belief-based and covariation-based cues into models of causal attribution.