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On the category adjustment model: another look at Huttenlocher, Hedges, and Vevea (2000)

机译:关于类别调整模型:另一种外观Huttenlocher,Hedges和Vevea(2000)

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Huttenlocher et al. (J Exp Psychol Gen 129:220-241, 2000) introduce the category adjustment model (CAM). Given that participants imperfectly remember stimuli (which we refer to as "targets"), CAM holds that participants maximize accuracy by using information about the distribution of the targets to improve their judgments. CAM predicts that judgments will be a weighted average of the imperfect memory of the target and the mean of the distribution of targets. Huttenlocher et al. (2000) report on three experiments and conclude that CAM is "verified". We attempt to replicate the conditions in Experiment 3 from Huttenlocher et al. (2000). We analyze judgment-level data rather than averaged data. We find evidence of a bias toward a set of recent targets rather than a bias toward the running mean. We do not find evidence of learning. The judgments in our dataset are not consistent with CAM. We discuss other defects in HHV-including dividing by zero. It seems that evidence for CAM is a statistical artifact that appears when researchers analyze data averaged across trials and do not consider a recency bias.
机译:Huttenlocher等。 (j expyscencol Gen 129:220-241,2000)介绍了类别调整模型(CAM)。鉴于参与者不完全记住刺激(我们将其称为“目标”),CAM通过使用有关目标分布的信息来提高其判断,参与者最大限度地提高准确性。 CAM预测判断将是目标不完美记忆的加权平均值以及目标分布的平均值。 Huttenlocher等。 (2000)关于三次实验的报告,并得出结论,CAM是“验证”。我们试图从Huttenlocher等人复制实验3中的条件。 (2000)。我们分析判断级别数据而不是平均数据。我们发现证据表明偏向一套最近的目标,而不是朝着奔跑意味着偏见。我们找不到学习的证据。我们数据集中的判断与CAM不一致。我们讨论HHV中的其他缺陷 - 包括除以零。凸轮的证据似乎是一个统计伪像,当研究人员分析了跨试验的平均数据时出现并且不考虑了新近偏见。

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