Explanatory completeness

Korman, Joanna; Khemlani, Sangeet

doi:10.1016/j.actpsy.2020.103139

Cited by 19 publications

(8 citation statements)

References 39 publications

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“…If the evidence includes observations, A, B, and C, then the generation process will involve memory search for causes and analogies related to A, B, and C. Indeed, we know that causal relationships act as stronger retrieval cues than non-causal relationships with equally strong associative strength (Fenker, Waldmann, & Holyoak, 2005). Plausibly, the narrative would be built up until it is deemed a sufficiently complete explanation (Korman & Khemlani, 2020).…”

Section: R42 Objection 5: Cnt's Representational Framework Is Too Sim...mentioning

confidence: 99%

Conviction Narrative Theory: A theory of choice under radical uncertainty

Johnson

Bilovich²,

Tuckett

2022

Behav Brain Sci

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Conviction Narrative Theory (CNT) is a theory of choice under radical uncertainty—situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people use narratives—structured representations of causal, temporal, analogical, and valence relationships—rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels ‘right’ to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We propose 12 principles to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences.

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Section: R42 Objection 5: Cnt's Representational Framework Is Too Sim...mentioning

confidence: 99%

Conviction Narrative Theory: A theory of choice under radical uncertainty

Johnson

Bilovich²,

Tuckett

2022

Behav Brain Sci

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“…Our research may also further some debates surrounding the mental model theory of human reasoning (Johnson-Laird, 1983;Johnson-Laird et al, 2015), which is often portrayed as a competitor to the new paradigm (e.g., Elqayam, 2018;Over, 2009). In the context of the mental model theory, the term explanation is closely linked to causal reasoning (e.g., Johnson-Laird & Khemlani, 2017;Khemlani et al, 2014;Korman & Khemlani, 2020). We did not restrict our model to causal explanations, but we agree with Korman and Khemlani (2020) that explanation is often causal.…”

Section: Contributions and Future Researchmentioning

confidence: 67%

Can conditionals explain explanations? A modus ponens model of B because A

Sebben

Ullrich

2021

Cognition

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“…The knowledge that books can be heavy and shelves flimsy enables individuals to simulate the situation in which the weight of a book causes a shelf to break. Reasoners appear to prefer a complete causal simulation from the initial cause to the final effect in the scenario, and in which each effect has a cause (Johnson-Laird et al, 2004; Korman & Khemlani, 2018, 2020; Zemla et al, 2017). On learning that the book was not put on the shelf, reasoners can halt the simulation, and, as a consequence, cease to believe that the subsequent events occurred in the chain.…”

Section: Discussionmentioning

confidence: 99%

Causal conflicts produce domino effects

Khemlani

Johnson‐Laird

2020

Quarterly Journal of Experimental Psychology

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Inconsistent beliefs call for revision—but which of them should individuals revise? A long-standing view is that they should make minimal changes that restore consistency. An alternative view is that their primary task is to explain how the inconsistency arose. Hence, they are likely to violate minimalism in two ways: they should infer more information than is strictly necessary to establish consistency and they should reject more information than is strictly necessary to establish consistency. Previous studies corroborated the first effect: reasoners use causal simulations to build explanations that resolve inconsistencies. Here, we show that the second effect is true too: they use causal simulations to reject more information than is strictly necessary to establish consistency. When they abandon a cause, the effects of the cause topple like dominos: Reasoners tend to deny the occurrence of each subsequent event in the chain. Four studies corroborated this prediction.

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Explanatory completeness

Cited by 19 publications

References 39 publications

Conviction Narrative Theory: A theory of choice under radical uncertainty

Conviction Narrative Theory: A theory of choice under radical uncertainty

Can conditionals explain explanations? A modus ponens model of B because A

Causal conflicts produce domino effects

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