Many studies have shown that confidence and accuracy can be dissociated in a variety of tasks. However, most of these dissociations involve small effect sizes, occur only in a subset of participants, and include a reaction time (RT) confound. Here, I develop a new method for inducing confidence-accuracy dissociations that overcomes these limitations. The method uses an external noise manipulation and relies on the phenomenon of criterion attraction where criteria for different tasks become attracted to each other. Subjects judged the identity of stimuli generated with either low or high external noise. The results showed that the two conditions were matched on accuracy and RT but produced a large difference in confidence (effect appeared for 25 of 26 participants, effect size: Cohen's d = 1.9). Computational modeling confirmed that these results are consistent with a mechanism of criterion attraction. These findings establish a new method for creating conditions with large differences in confidence without differences in accuracy or RT. Unlike many previous studies, however, the current method does not lead to differences in subjective experience and instead produces robust confidence-accuracy dissociations by exploiting limitations in post-perceptual, cognitive processes.

中文翻译：

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通过标准吸引实现稳健的置信度与准确度分离。


许多研究表明，在各种任务中，信心和准确性可能是分离的。然而，大多数这些分离涉及的效应较小，仅发生在一部分参与者中，并且包括反应时间 (RT) 混杂。在这里，我开发了一种新方法来诱导置信度与准确性的分离，从而克服了这些限制。该方法使用外部噪声操纵并依赖于标准吸引现象，其中不同任务的标准相互吸引。受试者判断低或高外部噪音产生的刺激的身份。结果表明，这两个条件在准确度和 RT 上是匹配的，但在置信度上产生了很大差异（26 名参与者中的 25 名出现了效果，效果大小：Cohen's d = 1.9）。计算模型证实这些结果与标准吸引机制一致。这些发现建立了一种新方法，可以在不影响准确性或 RT 的情况下创造置信度差异较大的条件。然而，与之前的许多研究不同，当前的方法不会导致主观体验的差异，而是通过利用后知觉认知过程的限制来产生强大的置信度与准确性的分离。