Cross-Cultural Differences in Informal Argumentation: Norms, Inductive Biases and Evidentiality

Karaslaan, Hatice; Hohenberger, Annette; Demir, Hilmi; Simon, Hall; Oaksford, Mike

doi:10.1163/15685373-12340035

Cited by 8 publications

(7 citation statements)

References 56 publications

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“…Hahn & Oaksford (2007) argue that in typical real-world settings Pr(C|a) > Pr(¬C|¬a), and consequently, positive arguments should be perceived as stronger than negative arguments. This prediction, and people's sensitivity to priors and likelihoods, has been confirmed experimentally (Hahn & Oaksford 2007, Hahn et al 2005, Oaksford & Hahn 2004) and replicated across cultures (Karaaslan et al 2018).…”

Section: Bayesian Approaches To the Fallacies Of Informal Argumentmentioning

confidence: 63%

“…The probability that a source is reliable, Pr(R), can be factored into the likelihoods in Bayes' theorem [e.g., Pr(a|C) becomes Pr(a|C, R)Pr(R) + Pr(a|C, ¬R)(1 -Pr(R)], which caps argument strength (Bovens & Hartmann 2003). Manipulating source reliability has predictable effects on the strength of arguments from ignorance; higher reliability leads to greater argument force and hence stronger conclusion endorsement (Hahn & Oaksford 2007, Karaaslan et al 2018.…”

Section: Bayesian Approaches To the Fallacies Of Informal Argumentmentioning

confidence: 99%

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New Paradigms in the Psychology of Reasoning

Oaksford

Chater

2020

Annu. Rev. Psychol.

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121

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The psychology of verbal reasoning initially compared performance with classical logic. In the last 25 years, a new paradigm has arisen, which focuses on knowledge-rich reasoning for communication and persuasion and is typically modeled using Bayesian probability theory rather than logic. This paradigm provides a new perspective on argumentation, explaining the rational persuasiveness of arguments that are logical fallacies. It also helps explain how and why people stray from logic when given deductive reasoning tasks. What appear to be erroneous responses, when compared against logic, often turn out to be rationally justified when seen in the richer rational framework of the new paradigm. Moreover, the same approach extends naturally to inductive reasoning tasks, in which people extrapolate beyond the data they are given and logic does not readily apply. We outline links between social and individual reasoning and set recent developments in the psychology of reasoning in the wider context of Bayesian cognitive science.

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Section: Bayesian Approaches To the Fallacies Of Informal Argumentmentioning

confidence: 63%

Section: Bayesian Approaches To the Fallacies Of Informal Argumentmentioning

confidence: 99%

New Paradigms in the Psychology of Reasoning

Oaksford

Chater

2020

Annu. Rev. Psychol.

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121

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“…5There is empirical work emerging on evidentiality in the psychology of reasoning, for example, Krzyżanowska, Wenmackers, and Douven (2013) and Karaslaan, Hohenberger, Demir, Hall, and Oaksford (in press).…”

mentioning

confidence: 99%

Paradigms, possibilities, and probabilities: Comment on Hinterecker, Knauff, and Johnson-Laird (2016).

Oaksford¹,

Over²,

Cruz³

2019

Journal of Experimental Psychology: Learning, Memory, and Cogni

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Hinterecker et al. (2016) compared the adequacy of the probabilistic new paradigm in reasoning with the recent revision of mental models theory (MMT) for explaining a novel class of inferences containing the modal term "possibly". For example, the door is closed or the window is open or both, therefore, possibly the door is closed and the window is open (A or B or both, therefore, possibly(A & B)). They concluded that their results support MMT. In this comment, it is argued that Hinterecker et al. ( 2016) have not adequately characterised the theory of probabilistic validity (p-validity) on which the new paradigm depends. It is unclear how p-validity can be applied to these inferences, which are anyway peripheral to the theory. It is also argued that the revision of MMT is not well motivated and its adoption leads to many logical absurdities. Moreover, the comparison is not appropriate because these theories are defined at different levels of computational explanation. In particular, revised MMT lacks a provably consistent computational level theory that could justify treating these inferences as valid. It is further argued that the data could result from the non-colloquial locutions used to express the premises. Finally, an alternative pragmatic account is proposed based on the idea that a conclusion is possible if what someone knows cannot rule it out. This account could be applied to the unrevised mental model theory rendering the revision redundant.

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“…We note that in related work on Bayesian models of deductive reasoning (Oaksford et al, 2000; Vance & Oaksford, 2021) and informal argumentation (Karaslaan et al, 2018), model-fitting at the individual level has revealed interesting individual variations in reasoning processes. Vance and Oaksford (2021), for example, found their Bayesian model gave a good account of conditional inference with text arguments in a majority of participants who understood the conditional probabilities of events described in those arguments.…”

Section: How Sensitive Are Individuals To Sampling Frames?mentioning

confidence: 84%

Who is sensitive to selection biases in inductive reasoning?

Hayes¹,

Liew²,

Desai³

et al. 2023

Journal of Experimental Psychology: Learning, Memory, and Cogni

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The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames -causal constraints that only allow certain types of instances to be sampled. Group data from both experiments indicated that people were sensitive to the effects of such frames, showing narrower generalization when sample instances were selected because they shared a target property (property sampling) than when instances were sampled because they belonged to a particular group (category sampling). Group generalization patterns conformed to the predictions of a Bayesian model of property induction that incorporates a selective sampling mechanism. In each experiment, however, there was considerable individual variation, with a nontrivial minority showing little sensitivity to sampling frames. Experiment 2 examined correlates of frames sensitivity. A composite measure of working memory capacity predicted individual sensitivity to sampling frames. These results have important implications for current debates about people's ability to factor sample selection mechanisms into their inferences and for the development of formal models of inductive inference.

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Cross-Cultural Differences in Informal Argumentation: Norms, Inductive Biases and Evidentiality

Cited by 8 publications

References 56 publications

New Paradigms in the Psychology of Reasoning

New Paradigms in the Psychology of Reasoning

Paradigms, possibilities, and probabilities: Comment on Hinterecker, Knauff, and Johnson-Laird (2016).

Who is sensitive to selection biases in inductive reasoning?

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